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author | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-04-19 00:47:55 +0000 |
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committer | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-04-19 00:47:55 +0000 |
commit | 26a029d407be480d791972afb5975cf62c9360a6 (patch) | |
tree | f435a8308119effd964b339f76abb83a57c29483 /third_party/python/pyrsistent | |
parent | Initial commit. (diff) | |
download | firefox-e51783d008170d9ab27d25da98ca3a38b0a41b67.tar.xz firefox-e51783d008170d9ab27d25da98ca3a38b0a41b67.zip |
Adding upstream version 124.0.1.upstream/124.0.1
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
Diffstat (limited to 'third_party/python/pyrsistent')
35 files changed, 9822 insertions, 0 deletions
diff --git a/third_party/python/pyrsistent/CHANGES.txt b/third_party/python/pyrsistent/CHANGES.txt new file mode 100644 index 0000000000..603b3f2048 --- /dev/null +++ b/third_party/python/pyrsistent/CHANGES.txt @@ -0,0 +1,333 @@ +Revision history +---------------- +0.16.0, 2020-03-24 + * No major updates but Python 2 support no longer guaranteed. + * Fix #192, 'ignore_extra' for 'pvector_field'. Thanks @ss18 for this! + * Fix #191, include LICENCE in distribution. Thanks @johnthagen for this! + * Fix #190, minor MyPy errors. Thanks @Qhesz for this! + +0.15.7, 2020-01-07 + * NOTE! This is the last version of Pyrsistent that officially supports Python 2.X! + * Fix #186, type errors with more recent versions of MyPy. Thanks @qhesz for this! + * Build and test on ARM during CI. Thanks @ossdev07 for this! + * Set absolute imports for python2 compatibility. Thanks @michalvi for this! + +0.15.6, 2019-11-23 + * Fix #182 moduleinit name clash. + +0.15.5, 2019-10-27 + * Fix #179 Fixed 'ignore_extra' factory parameter for pvector. Thanks @ss18 for this! + +0.15.4, 2019-07-27 + * Fix #174, fix a GC traversal bug in pvector evolver C extension. Thanks @till-varoquaux for finding and fixing this! + * Fix #175, pytest 5 compatibility, this is a quick fix, some more work is needed to get coverage working etc. + +0.15.3, 2019-07-07 + * Fix #172, catch all exceptions during extension build to reduce chance of corner cases that prevents installation. + * Fix #171, in PVector equality comparison don's assume that other object has a length, check before calling len. + * Fix #168, write warning about failing build of C extension directly to stderr to avoid that pip silences it. + * Fix #155, update PMapEvolver type stub to better reflect implementation. + +0.15.2, 2019-05-12 + * Fix #166, Propagate 'ignore_extra' param in hierarchy. Thanks @ss18 for this! + * Fix #167, thaw typing. Thanks @nattofriends for this! + * Fix #154, not possible to insert empty pmap as leaf node with transform. + +0.15.1, 2019-04-26 + * Fix #163 installation broken on Python 2 because of fix of #161, thanks @vphilippon for this! Sorry for the + inconvenience. + +0.15.0, 2019-04-25 + * Python 3.4 is no longer officially supported since it is EOL since 2019-03-18. + * Fix #157, major improvements to type hints. Thanks @je-l for working on this and @nattofriend for reviewing the PR! + * Fix #161, installation fails on some Windows platforms because fallback to Python pvector does not work. + Thanks @MaxTaggart for fixing and verifying this! + +0.14.11, 2019-02-21 + * Fix #152 Don't use __builtin_popcount, this hopefully fixes #147 Error in pvectorc.cp37-win_amd64.pyd file, as well. + Thanks @benrg for this! + * Fix #151 Fix compatibility for hypothesis 4. Thanks @felixonmars for this! + +0.14.10, 2019-02-09 + * Fix #148, only require pytest-runner if running tests. Thanks @ccorbacho for this! + +0.14.9, 2019-01-06 + * Fix #144, Compile pvectormodule.c on windows. Thanks @ganwell for this! + +0.14.8, 2018-12-19 + * Fix #142, Improve type stubs. Thanks @arxanas for this! + +0.14.7, 2018-11-20 + * Fix #102, add PEP 561 type annotation stubs for most pyrsistent types. Thanks @nattofriends for this! + +0.14.6, 2018-11-17 + * Fix #135, Type classes for Python 3 type annotations of pyrsistent types. Thanks @nattofriends for this! + * Fix #128, Allow PClass and PRecord to ignore input parameters to constructor that are not part of the spec + instead of blowing up with a type error. Thanks @agberk for this! + +0.14.5, 2018-10-14 + * Fix #137, deprecation warnings in Python 3.7. Thanks @thombashi for this! + * Fix #129, building via setuptools and setup.py. Thanks @galuszkak for this! + +0.14.4, 2018-07-08 + * Fix #133, minor Python 3.7 compatibility issue. Pyrsistent is now officially Python 3.7 compliant! + +v0.14.3, 2018-06-11 + * Fix #123 regression where type names break sequence fields. Thanks @doozr for this! + * Fix #124 using the class name to make AttributeError on __getattr__ more informative for PRecords. + Thanks @neilvyas for this! + * Fix #125 how fields handle type arguments. Thanks @neilvyas for this! + +v0.14.2, 2017-12-06 + * Fix #121, regression in PClass.set() introduced in 0.14.1. + +v0.14.1, 2017-11-27 + * Equality check performance improvements for pvectors and pmaps. Thanks @dtomas for this! + * Avoid calling factories multiple times for fields that do not change, see PR #120 for for + details. Thanks @teepark for this! + +v0.14.0, 2017-10-08 + * Fix #117, pmap now accepts iterators as input to constructor. Thanks @Julian for this! + * Drop support for Python 2.6. Nothing has been done in this release that will explicitly + break pyrsistent for 2.6 but it will not be considered moving forward. Dropping 2.6 + support is the reason for stepping the second decimal instead of the third. + +v0.13.0, 2017-09-01 + * Fix #113, Skip field factories when loading pickled objects. There is a + minor backwards incompatibilty in the behaviour because of this. Thanks + @teepark for fi this! + * Fix #116, negative indexing for pdeques. Thanks @Julian for this! + +v0.12.3, 2017-06-04 + * Fix #83, make it possible to use Python 3 enums as field type without having to wrap it in + a list or tuple. Thanks @douglas-treadwell for this! + +v0.12.2, 2017-05-30 + * Fix #108, now possible to use the values in predicates to transform. Thanks @exarkus for this! + * Fix #107, support multiple level of __invariant__ inheritance. Thanks @exarkus for this! + +v0.12.1, 2017-02-26 + * Fix #97, initialize CheckedPVector from iterator- + * Fix #97, cache hash value on PMap. Thanks @sarum90 for this! + +v0.12.0, 2017-01-06 + * Fix #87, add function get_in() for access to elements in deeply nested structures. + * Fix #91, add method update() to pset and pbag. + * Fix #92, incorrect discard of elements in transform on pvector + * This is a release candidate for 1.0 as I now consider pyrsistent fairly stable. + +v0.11.13, 2016-04-03 + * Fix #84, pvector segfault in CPython 3 when repr of contained object raises Exception. + * Update README to cover for issue described in #83. + +v0.11.12, 2016-02-06 + * Minor modifications of tests to allow testing as requested in #79 and #80. + * Also run CI tests under python 3.5 + +v0.11.11, 2016-01-31 + * #78, include tests in pypi dist. + +v0.11.10, 2015-12-27, NOTE! This release contains a backwards incompatible change + despite only stepping the patch version number. See below. + * Implement #74, attribute access on PClass evolver + * Implement #75, lazily evaluated invariant messages by providing a + callable with no arguments. + * Initial values on fields can now be evaluated on object creation + by providing a callable with no arguments. + + NOTE! If you previously had callables as initial values this change means that those + will be called upon object creation which may not be what you want. As + a temporary workaround a callable returning a callable can be used. This + feature and the concept of initial values will likely change slightly in the future. + See #77 and and #76 for more information. + +v0.11.9, 2015-11-01 + * Added PVector.remove(), thanks @radix for initiating this! + +v0.11.8, 2015-10-18 + * Fix #66, UnicodeDecodeError when doing pip install in environments with ascii encoding as default. + Thanks @foolswood! + * Implement support for multiple types in pmap_field(), pvector_field() and pset_field(). Thanks @itamarst! + +v0.11.7, 2015-10-03 + * Fix #52, occasional SEGFAULTs due to misplaced call to PyObject_GC_Track. Thanks @jkbjh for this! + * Fix #42, complete support for delete. Now also on the C-implementation of the PVectorEvolver. + Thanks @itamarst for contributing a whole bunch of Hypothesis test cases covering the evolver operations! + +v0.11.6, 2015-09-30 + * Add +, -, & and | operations to PBag. Thanks @Futrell for this! + +v0.11.5, 2015-09-29 + * Fix bug introduced in 0.11.4 that prevented multi level inheritance from PClass. + * Make PClassMeta public for friendlier subclassing + +v0.11.4, 2015-09-28 + * Fix #59, make it possible to create weakrefs to all collection types. + Thanks @itamarst for reporting it. + * Fix #58, add __str__ to InvariantException. Thanks @tomprince for reporting it. + +v0.11.3, 2015-09-15 + * Fix #57, support pickling of PClasses and PRecords using pmap_field, pvector_field, and pset_field. + Thanks @radix for reporting this and submitting a fix for it! + +v0.11.2, 2015-09-09 + * Fix bug causing potential element loss when reallocating PMap. Thanks to @jml for finding + this and submitting a PR with a fix! + * Removed python 3.2 test build from Travis. There is nothing breaking 3.2 compatibility in this + release but there will be no effort moving forward to keep the 3.2 compatibility. + +v0.11.1, 2015-08-24 + * Fix #51, PClass.set() broken when used with string+value argument. + * #50, make it possible to specify more than one assertion in an invariant + * #48, make it possible to make recursive type references by using a string + as type specification. + +v0.11.0, 2015-07-11 + * #42, delete() function added to PVector to allow deletion of elements by index + and range. Will perform a full copy of the vector, no structural sharing. + Thanks @radix for helping out with this one! + * Fix #39, explicitly disallow ordering for PMap and PBag, Python 3 style + * Fix #37, PMap.values()/keys()/items() now returns PVectors instead of lists + +v0.10.3, 2015-06-13 + * Fix #40, make it possible to disable the C extension by setting the + PYRSISTENT_NO_C_EXTENSION environment variable. + +v0.10.2, 2015-06-07 + * Fix #38, construction from serialized object for pvector/pset/pmap fields. + +v0.10.1, 2015-04-27 + * Fix broken README.rst + +v10.0.0, 2015-04-27 + * New type PClass, a persistent version of a Python object. Related to issues #30 and #32. + Thanks @exarkun and @radix for input on this one! + * Rename PRecordTypeError -> PTypeError, it is now also raised by PClass + * New convenience functions, pvector_field, pmap_field and pset_field to create PRecord/PClass + fields for checked collections. Issues #26 and #36. Thanks to @itamarst for this! + * Removed deprecated function set_in() on PMap and PVector. + * Removed deprecated factory function pclass. + * Major internal restructuring breaking pyrsistent.py into multiple files. This should + not affect those only using the public interface but if you experience problems please + let me know. + +v0.9.4, 2015-04-20 + * Fix #34, PVector now compares against built in list type + +v0.9.3, 2015-04-06 + * Rename pclass back to immutable and deprecate the usage of the pclass function. PClass will be used by + a new, different type in upcoming releases. + * Documentation strings for the exceptions introduced in 0.9.2. + +v0.9.2, 2015-04-03 + * More informative type errors from checked types, issue #30 + * Support multiple optional types, issue #28 + +v0.9.1, 2015-02-25 + * Multi level serialization for checked types + +v0.9.0, 2015-02-25, Lots of new stuff in this release! + * Checked types, checked versions of PVector, PMap, PSet that support type and invariant specification. + Currently lacking proper documentation but I'm working on it. + * set_in() on PVector and PMap are now deprecated and will be removed in the next release. + Use transform() instead. set_in() has been updated to use transform() for this release + this means that some corner error cases behave slightly different than before. + * Refactoring of the PVector to unify the type. Should not have any user impact as long as + only the public interface of pyrsistent has been used. PVector is now an abstract base class + with which the different implementations are registered. + * Evolvers have been updated to return themselves for evolving operations to allow function chaining. + * Richer exception messages for KeyErrors and IndexErrors specifying the key/index that caused the failure. + Thanks @radix for this. + * Missing attribute on PMaps when accessing with dot-notation now raises an AttributeError instead of a + KeyError. Issue #21. + * New function decorator @mutant that freezes all input arguments to a function and the return value. + * Add __version__ to pyrsistent.py. Issue #23. + * Fix pickling for pset. Issue #24. + +v0.8.0, 2015-01-21 + * New type PRecord. Subtype of PMap that allows explicit, declarative field specification. Thanks @boxed + for inspiration! + * Efficient transformations of arbitrary complexity on PMap and PVector. Thanks @boxed for inspiration! + * Breaking change to the evolver interface. What used to be .pvector(), .pmap() and .pset() + on the different evolvers has now been unified so that all evolvers have one method .persistent() + to produce the persistent counterpart. Sorry for any inconvenience. + * Removed the tests directory from the package. + * PMap and PSet now contains a copy-function to closer mimic the interface of the dict and set. These + functions will simply return a reference to self. + * Removed deprecated alias 'immutable' from pclass. + +v0.7.1, 2015-01-17 + * Fixes #14 where a file executed (unexpectedly) during installation was not python 3 compatible. + +v0.7.0, 2015-01-04, No 1.0, instead a bunch of new stuff and one API breaking change to PMap.remove(). + * Evolvers for pvector, pmap and pset to allow simple and efficient updates of multiple elements + in the collection. See the documentation for a closer description. + * New method mset on pvector to update multiple values in one operation + * Remove deprecated methods merge and merge_with on PMap + * Change behavior of PMap.remove, it will now raise a KeyError if the element is not present. + New method PMap.discard will instead return the original pmap if the element is not present. + This aligns the PMap with how things are done in the PSet and is closer to the behavior of the + built in counterparts. + +v0.6.3, 2014-11-27 + * Python 2.6 support, thanks @wrmsr! + * PMap.merge/merge_with renamed to update/update_with. merge/merge_with remains but will be + removed for 1.0. + * This is a release candidate for 1.0! Please be aware that PMap.merge/merge_with and immutable() + will be removed for 1.0. + +v0.6.2, 2014-11-03 + * Fix typo causing the pure python vector to be used even if the C implementation was + available. Thanks @zerc for finding it! + +v0.6.1, 2014-10-31 + * Renamed 'immutable' to 'pclass' for consistency but left immutable for compatibility. + +v0.6.0, 2014-10-25 + * New data structure, persistent linked list + * New data structure, persistent double ended queue + +v0.5.0, 2014-09-24 + * New data structure, persistent bag / multiset + * New functions freeze and thaw to recursively convert between python + built in data types and corresponding pyrsistent data types. + * All data structures can now be pickled + * New function merge_in on persistent map which allows a user + supplied function to implement the merge strategy. + +v0.4.0, 2014-09-20 + * Full Python 3 support. + * Immutable object implemented. + * Bug fixes in PVector.__repr__() and PMap.__hash__() and index check of PVector. + * Repr changed to be fully cut and paste compatible + * Changed assoc() -> set(), assoc_in() -> set_in(), massoc() -> mset(). + Sorry for the API breaking change but I think those names are more pythonic. + * Improved documentation. + +v0.3.1, 2014-06-29 + * assoc() on PSet renamed back to add() + +v0.3.0, 2014-06-28 + * Full Sequence protocol support for PVector + * Full Mapping protocol support for PMap + * Full Set protocol support for PSet + * assoc_in() support for both PMap and PVector + * merge() support for PMap + * Performance improvements to the PVector C extension speed up allocation + +v0.2.1, 2014-06-21 + * Supply the tests with the distribution + +v0.2.0, 2014-06-21 + * New C extension with an optimized version of the persistent vector + * Updated API slightly + +v0.1.0, 2013-11-10 + * Initial release. + + +TODO (in no particular order) +----------------------------- +- Versioned data structure where the different versions can be accessed by index? +- Ordered sets and maps +- A good performance measurement suite diff --git a/third_party/python/pyrsistent/LICENCE.mit b/third_party/python/pyrsistent/LICENCE.mit new file mode 100644 index 0000000000..6609e4c05a --- /dev/null +++ b/third_party/python/pyrsistent/LICENCE.mit @@ -0,0 +1,22 @@ +Copyright (c) 2019 Tobias Gustafsson + +Permission is hereby granted, free of charge, to any person +obtaining a copy of this software and associated documentation +files (the "Software"), to deal in the Software without +restriction, including without limitation the rights to use, +copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the +Software is furnished to do so, subject to the following +conditions: + +The above copyright notice and this permission notice shall be +included in all copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, +EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES +OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND +NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT +HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, +WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING +FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR +OTHER DEALINGS IN THE SOFTWARE.
\ No newline at end of file diff --git a/third_party/python/pyrsistent/MANIFEST.in b/third_party/python/pyrsistent/MANIFEST.in new file mode 100644 index 0000000000..155c6351bb --- /dev/null +++ b/third_party/python/pyrsistent/MANIFEST.in @@ -0,0 +1,5 @@ +include *.rst +include tests/*_test.py +include tests/memory_profiling.py +include CHANGES.txt +include LICENCE.mit
\ No newline at end of file diff --git a/third_party/python/pyrsistent/PKG-INFO b/third_party/python/pyrsistent/PKG-INFO new file mode 100644 index 0000000000..1d1c159034 --- /dev/null +++ b/third_party/python/pyrsistent/PKG-INFO @@ -0,0 +1,742 @@ +Metadata-Version: 1.1 +Name: pyrsistent +Version: 0.16.0 +Summary: Persistent/Functional/Immutable data structures +Home-page: http://github.com/tobgu/pyrsistent/ +Author: Tobias Gustafsson +Author-email: tobias.l.gustafsson@gmail.com +License: MIT +Description: Pyrsistent + ========== + .. image:: https://travis-ci.org/tobgu/pyrsistent.png?branch=master + :target: https://travis-ci.org/tobgu/pyrsistent + + .. image:: https://badge.fury.io/py/pyrsistent.svg + :target: https://badge.fury.io/py/pyrsistent + + .. image:: https://coveralls.io/repos/tobgu/pyrsistent/badge.svg?branch=master&service=github + :target: https://coveralls.io/github/tobgu/pyrsistent?branch=master + + + .. _Pyrthon: https://www.github.com/tobgu/pyrthon/ + + Pyrsistent is a number of persistent collections (by some referred to as functional data structures). Persistent in + the sense that they are immutable. + + All methods on a data structure that would normally mutate it instead return a new copy of the structure containing the + requested updates. The original structure is left untouched. + + This will simplify the reasoning about what a program does since no hidden side effects ever can take place to these + data structures. You can rest assured that the object you hold a reference to will remain the same throughout its + lifetime and need not worry that somewhere five stack levels below you in the darkest corner of your application + someone has decided to remove that element that you expected to be there. + + Pyrsistent is influenced by persistent data structures such as those found in the standard library of Clojure. The + data structures are designed to share common elements through path copying. + It aims at taking these concepts and make them as pythonic as possible so that they can be easily integrated into any python + program without hassle. + + If you want to go all in on persistent data structures and use literal syntax to define them in your code rather + than function calls check out Pyrthon_. + + Examples + -------- + .. _Sequence: collections_ + .. _Hashable: collections_ + .. _Mapping: collections_ + .. _Mappings: collections_ + .. _Set: collections_ + .. _collections: https://docs.python.org/3/library/collections.abc.html + .. _documentation: http://pyrsistent.readthedocs.org/ + + The collection types and key features currently implemented are: + + * PVector_, similar to a python list + * PMap_, similar to dict + * PSet_, similar to set + * PRecord_, a PMap on steroids with fixed fields, optional type and invariant checking and much more + * PClass_, a Python class fixed fields, optional type and invariant checking and much more + * `Checked collections`_, PVector, PMap and PSet with optional type and invariance checks and more + * PBag, similar to collections.Counter + * PList, a classic singly linked list + * PDeque, similar to collections.deque + * Immutable object type (immutable) built on the named tuple + * freeze_ and thaw_ functions to convert between pythons standard collections and pyrsistent collections. + * Flexible transformations_ of arbitrarily complex structures built from PMaps and PVectors. + + Below are examples of common usage patterns for some of the structures and features. More information and + full documentation for all data structures is available in the documentation_. + + .. _PVector: + + PVector + ~~~~~~~ + With full support for the Sequence_ protocol PVector is meant as a drop in replacement to the built in list from a readers + point of view. Write operations of course differ since no in place mutation is done but naming should be in line + with corresponding operations on the built in list. + + Support for the Hashable_ protocol also means that it can be used as key in Mappings_. + + Appends are amortized O(1). Random access and insert is log32(n) where n is the size of the vector. + + .. code:: python + + >>> from pyrsistent import v, pvector + + # No mutation of vectors once created, instead they + # are "evolved" leaving the original untouched + >>> v1 = v(1, 2, 3) + >>> v2 = v1.append(4) + >>> v3 = v2.set(1, 5) + >>> v1 + pvector([1, 2, 3]) + >>> v2 + pvector([1, 2, 3, 4]) + >>> v3 + pvector([1, 5, 3, 4]) + + # Random access and slicing + >>> v3[1] + 5 + >>> v3[1:3] + pvector([5, 3]) + + # Iteration + >>> list(x + 1 for x in v3) + [2, 6, 4, 5] + >>> pvector(2 * x for x in range(3)) + pvector([0, 2, 4]) + + .. _PMap: + + PMap + ~~~~ + With full support for the Mapping_ protocol PMap is meant as a drop in replacement to the built in dict from a readers point + of view. Support for the Hashable_ protocol also means that it can be used as key in other Mappings_. + + Random access and insert is log32(n) where n is the size of the map. + + .. code:: python + + >>> from pyrsistent import m, pmap, v + + # No mutation of maps once created, instead they are + # "evolved" leaving the original untouched + >>> m1 = m(a=1, b=2) + >>> m2 = m1.set('c', 3) + >>> m3 = m2.set('a', 5) + >>> m1 + pmap({'a': 1, 'b': 2}) + >>> m2 + pmap({'a': 1, 'c': 3, 'b': 2}) + >>> m3 + pmap({'a': 5, 'c': 3, 'b': 2}) + >>> m3['a'] + 5 + + # Evolution of nested persistent structures + >>> m4 = m(a=5, b=6, c=v(1, 2)) + >>> m4.transform(('c', 1), 17) + pmap({'a': 5, 'c': pvector([1, 17]), 'b': 6}) + >>> m5 = m(a=1, b=2) + + # Evolve by merging with other mappings + >>> m5.update(m(a=2, c=3), {'a': 17, 'd': 35}) + pmap({'a': 17, 'c': 3, 'b': 2, 'd': 35}) + >>> pmap({'x': 1, 'y': 2}) + pmap({'y': 3, 'z': 4}) + pmap({'y': 3, 'x': 1, 'z': 4}) + + # Dict-like methods to convert to list and iterate + >>> m3.items() + pvector([('a', 5), ('c', 3), ('b', 2)]) + >>> list(m3) + ['a', 'c', 'b'] + + .. _PSet: + + PSet + ~~~~ + With full support for the Set_ protocol PSet is meant as a drop in replacement to the built in set from a readers point + of view. Support for the Hashable_ protocol also means that it can be used as key in Mappings_. + + Random access and insert is log32(n) where n is the size of the set. + + .. code:: python + + >>> from pyrsistent import s + + # No mutation of sets once created, you know the story... + >>> s1 = s(1, 2, 3, 2) + >>> s2 = s1.add(4) + >>> s3 = s1.remove(1) + >>> s1 + pset([1, 2, 3]) + >>> s2 + pset([1, 2, 3, 4]) + >>> s3 + pset([2, 3]) + + # Full support for set operations + >>> s1 | s(3, 4, 5) + pset([1, 2, 3, 4, 5]) + >>> s1 & s(3, 4, 5) + pset([3]) + >>> s1 < s2 + True + >>> s1 < s(3, 4, 5) + False + + .. _PRecord: + + PRecord + ~~~~~~~ + A PRecord is a PMap with a fixed set of specified fields. Records are declared as python classes inheriting + from PRecord. Because it is a PMap it has full support for all Mapping methods such as iteration and element + access using subscript notation. + + .. code:: python + + >>> from pyrsistent import PRecord, field + >>> class ARecord(PRecord): + ... x = field() + ... + >>> r = ARecord(x=3) + >>> r + ARecord(x=3) + >>> r.x + 3 + >>> r.set(x=2) + ARecord(x=2) + >>> r.set(y=2) + Traceback (most recent call last): + AttributeError: 'y' is not among the specified fields for ARecord + + Type information + **************** + It is possible to add type information to the record to enforce type checks. Multiple allowed types can be specified + by providing an iterable of types. + + .. code:: python + + >>> class BRecord(PRecord): + ... x = field(type=int) + ... y = field(type=(int, type(None))) + ... + >>> BRecord(x=3, y=None) + BRecord(y=None, x=3) + >>> BRecord(x=3.0) + Traceback (most recent call last): + PTypeError: Invalid type for field BRecord.x, was float + + + Custom types (classes) that are iterable should be wrapped in a tuple to prevent their + members being added to the set of valid types. Although Enums in particular are now + supported without wrapping, see #83 for more information. + + Mandatory fields + **************** + Fields are not mandatory by default but can be specified as such. If fields are missing an + *InvariantException* will be thrown which contains information about the missing fields. + + .. code:: python + + >>> from pyrsistent import InvariantException + >>> class CRecord(PRecord): + ... x = field(mandatory=True) + ... + >>> r = CRecord(x=3) + >>> try: + ... r.discard('x') + ... except InvariantException as e: + ... print(e.missing_fields) + ... + ('CRecord.x',) + + Invariants + ********** + It is possible to add invariants that must hold when evolving the record. Invariants can be + specified on both field and record level. If invariants fail an *InvariantException* will be + thrown which contains information about the failing invariants. An invariant function should + return a tuple consisting of a boolean that tells if the invariant holds or not and an object + describing the invariant. This object can later be used to identify which invariant that failed. + + The global invariant function is only executed if all field invariants hold. + + Global invariants are inherited to subclasses. + + .. code:: python + + >>> class RestrictedVector(PRecord): + ... __invariant__ = lambda r: (r.y >= r.x, 'x larger than y') + ... x = field(invariant=lambda x: (x > 0, 'x negative')) + ... y = field(invariant=lambda y: (y > 0, 'y negative')) + ... + >>> r = RestrictedVector(y=3, x=2) + >>> try: + ... r.set(x=-1, y=-2) + ... except InvariantException as e: + ... print(e.invariant_errors) + ... + ('y negative', 'x negative') + >>> try: + ... r.set(x=2, y=1) + ... except InvariantException as e: + ... print(e.invariant_errors) + ... + ('x larger than y',) + + Invariants may also contain multiple assertions. For those cases the invariant function should + return a tuple of invariant tuples as described above. This structure is reflected in the + invariant_errors attribute of the exception which will contain tuples with data from all failed + invariants. Eg: + + .. code:: python + + >>> class EvenX(PRecord): + ... x = field(invariant=lambda x: ((x > 0, 'x negative'), (x % 2 == 0, 'x odd'))) + ... + >>> try: + ... EvenX(x=-1) + ... except InvariantException as e: + ... print(e.invariant_errors) + ... + (('x negative', 'x odd'),) + + + Factories + ********* + It's possible to specify factory functions for fields. The factory function receives whatever + is supplied as field value and the actual returned by the factory is assigned to the field + given that any type and invariant checks hold. + PRecords have a default factory specified as a static function on the class, create(). It takes + a *Mapping* as argument and returns an instance of the specific record. + If a record has fields of type PRecord the create() method of that record will + be called to create the "sub record" if no factory has explicitly been specified to override + this behaviour. + + .. code:: python + + >>> class DRecord(PRecord): + ... x = field(factory=int) + ... + >>> class ERecord(PRecord): + ... d = field(type=DRecord) + ... + >>> ERecord.create({'d': {'x': '1'}}) + ERecord(d=DRecord(x=1)) + + Collection fields + ***************** + It is also possible to have fields with ``pyrsistent`` collections. + + .. code:: python + + >>> from pyrsistent import pset_field, pmap_field, pvector_field + >>> class MultiRecord(PRecord): + ... set_of_ints = pset_field(int) + ... map_int_to_str = pmap_field(int, str) + ... vector_of_strs = pvector_field(str) + ... + + Serialization + ************* + PRecords support serialization back to dicts. Default serialization will take keys and values + "as is" and output them into a dict. It is possible to specify custom serialization functions + to take care of fields that require special treatment. + + .. code:: python + + >>> from datetime import date + >>> class Person(PRecord): + ... name = field(type=unicode) + ... birth_date = field(type=date, + ... serializer=lambda format, d: d.strftime(format['date'])) + ... + >>> john = Person(name=u'John', birth_date=date(1985, 10, 21)) + >>> john.serialize({'date': '%Y-%m-%d'}) + {'birth_date': '1985-10-21', 'name': u'John'} + + + .. _instar: https://github.com/boxed/instar/ + + .. _PClass: + + PClass + ~~~~~~ + A PClass is a python class with a fixed set of specified fields. PClasses are declared as python classes inheriting + from PClass. It is defined the same way that PRecords are and behaves like a PRecord in all aspects except that it + is not a PMap and hence not a collection but rather a plain Python object. + + .. code:: python + + >>> from pyrsistent import PClass, field + >>> class AClass(PClass): + ... x = field() + ... + >>> a = AClass(x=3) + >>> a + AClass(x=3) + >>> a.x + 3 + + + Checked collections + ~~~~~~~~~~~~~~~~~~~ + Checked collections currently come in three flavors: CheckedPVector, CheckedPMap and CheckedPSet. + + .. code:: python + + >>> from pyrsistent import CheckedPVector, CheckedPMap, CheckedPSet, thaw + >>> class Positives(CheckedPSet): + ... __type__ = (long, int) + ... __invariant__ = lambda n: (n >= 0, 'Negative') + ... + >>> class Lottery(PRecord): + ... name = field(type=str) + ... numbers = field(type=Positives, invariant=lambda p: (len(p) > 0, 'No numbers')) + ... + >>> class Lotteries(CheckedPVector): + ... __type__ = Lottery + ... + >>> class LotteriesByDate(CheckedPMap): + ... __key_type__ = date + ... __value_type__ = Lotteries + ... + >>> lotteries = LotteriesByDate.create({date(2015, 2, 15): [{'name': 'SuperLotto', 'numbers': {1, 2, 3}}, + ... {'name': 'MegaLotto', 'numbers': {4, 5, 6}}], + ... date(2015, 2, 16): [{'name': 'SuperLotto', 'numbers': {3, 2, 1}}, + ... {'name': 'MegaLotto', 'numbers': {6, 5, 4}}]}) + >>> lotteries + LotteriesByDate({datetime.date(2015, 2, 15): Lotteries([Lottery(numbers=Positives([1, 2, 3]), name='SuperLotto'), Lottery(numbers=Positives([4, 5, 6]), name='MegaLotto')]), datetime.date(2015, 2, 16): Lotteries([Lottery(numbers=Positives([1, 2, 3]), name='SuperLotto'), Lottery(numbers=Positives([4, 5, 6]), name='MegaLotto')])}) + + # The checked versions support all operations that the corresponding + # unchecked types do + >>> lottery_0215 = lotteries[date(2015, 2, 15)] + >>> lottery_0215.transform([0, 'name'], 'SuperDuperLotto') + Lotteries([Lottery(numbers=Positives([1, 2, 3]), name='SuperDuperLotto'), Lottery(numbers=Positives([4, 5, 6]), name='MegaLotto')]) + + # But also makes asserts that types and invariants hold + >>> lottery_0215.transform([0, 'name'], 999) + Traceback (most recent call last): + PTypeError: Invalid type for field Lottery.name, was int + + >>> lottery_0215.transform([0, 'numbers'], set()) + Traceback (most recent call last): + InvariantException: Field invariant failed + + # They can be converted back to python built ins with either thaw() + # or serialize() (which provides possibilities to customize serialization) + >>> thaw(lottery_0215) + [{'numbers': set([1, 2, 3]), 'name': 'SuperLotto'}, {'numbers': set([4, 5, 6]), 'name': 'MegaLotto'}] + >>> lottery_0215.serialize() + [{'numbers': set([1, 2, 3]), 'name': 'SuperLotto'}, {'numbers': set([4, 5, 6]), 'name': 'MegaLotto'}] + + .. _transformations: + + Transformations + ~~~~~~~~~~~~~~~ + Transformations are inspired by the cool library instar_ for Clojure. They let you evolve PMaps and PVectors + with arbitrarily deep/complex nesting using simple syntax and flexible matching syntax. + + The first argument to transformation is the path that points out the value to transform. The + second is the transformation to perform. If the transformation is callable it will be applied + to the value(s) matching the path. The path may also contain callables. In that case they are + treated as matchers. If the matcher returns True for a specific key it is considered for transformation. + + .. code:: python + + # Basic examples + >>> from pyrsistent import inc, freeze, thaw, rex, ny, discard + >>> v1 = freeze([1, 2, 3, 4, 5]) + >>> v1.transform([2], inc) + pvector([1, 2, 4, 4, 5]) + >>> v1.transform([lambda ix: 0 < ix < 4], 8) + pvector([1, 8, 8, 8, 5]) + >>> v1.transform([lambda ix, v: ix == 0 or v == 5], 0) + pvector([0, 2, 3, 4, 0]) + + # The (a)ny matcher can be used to match anything + >>> v1.transform([ny], 8) + pvector([8, 8, 8, 8, 8]) + + # Regular expressions can be used for matching + >>> scores = freeze({'John': 12, 'Joseph': 34, 'Sara': 23}) + >>> scores.transform([rex('^Jo')], 0) + pmap({'Joseph': 0, 'Sara': 23, 'John': 0}) + + # Transformations can be done on arbitrarily deep structures + >>> news_paper = freeze({'articles': [{'author': 'Sara', 'content': 'A short article'}, + ... {'author': 'Steve', 'content': 'A slightly longer article'}], + ... 'weather': {'temperature': '11C', 'wind': '5m/s'}}) + >>> short_news = news_paper.transform(['articles', ny, 'content'], lambda c: c[:25] + '...' if len(c) > 25 else c) + >>> very_short_news = news_paper.transform(['articles', ny, 'content'], lambda c: c[:15] + '...' if len(c) > 15 else c) + >>> very_short_news.articles[0].content + 'A short article' + >>> very_short_news.articles[1].content + 'A slightly long...' + + # When nothing has been transformed the original data structure is kept + >>> short_news is news_paper + True + >>> very_short_news is news_paper + False + >>> very_short_news.articles[0] is news_paper.articles[0] + True + + # There is a special transformation that can be used to discard elements. Also + # multiple transformations can be applied in one call + >>> thaw(news_paper.transform(['weather'], discard, ['articles', ny, 'content'], discard)) + {'articles': [{'author': 'Sara'}, {'author': 'Steve'}]} + + Evolvers + ~~~~~~~~ + PVector, PMap and PSet all have support for a concept dubbed *evolvers*. An evolver acts like a mutable + view of the underlying persistent data structure with "transaction like" semantics. No updates of the original + data structure is ever performed, it is still fully immutable. + + The evolvers have a very limited API by design to discourage excessive, and inappropriate, usage as that would + take us down the mutable road. In principle only basic mutation and element access functions are supported. + Check out the documentation_ of each data structure for specific examples. + + Examples of when you may want to use an evolver instead of working directly with the data structure include: + + * Multiple updates are done to the same data structure and the intermediate results are of no + interest. In this case using an evolver may be a more efficient and easier to work with. + * You need to pass a vector into a legacy function or a function that you have no control + over which performs in place mutations. In this case pass an evolver instance + instead and then create a new pvector from the evolver once the function returns. + + .. code:: python + + >>> from pyrsistent import v + + # In place mutation as when working with the built in counterpart + >>> v1 = v(1, 2, 3) + >>> e = v1.evolver() + >>> e[1] = 22 + >>> e = e.append(4) + >>> e = e.extend([5, 6]) + >>> e[5] += 1 + >>> len(e) + 6 + + # The evolver is considered *dirty* when it contains changes compared to the underlying vector + >>> e.is_dirty() + True + + # But the underlying pvector still remains untouched + >>> v1 + pvector([1, 2, 3]) + + # Once satisfied with the updates you can produce a new pvector containing the updates. + # The new pvector will share data with the original pvector in the same way that would have + # been done if only using operations on the pvector. + >>> v2 = e.persistent() + >>> v2 + pvector([1, 22, 3, 4, 5, 7]) + + # The evolver is now no longer considered *dirty* as it contains no differences compared to the + # pvector just produced. + >>> e.is_dirty() + False + + # You may continue to work with the same evolver without affecting the content of v2 + >>> e[0] = 11 + + # Or create a new evolver from v2. The two evolvers can be updated independently but will both + # share data with v2 where possible. + >>> e2 = v2.evolver() + >>> e2[0] = 1111 + >>> e.persistent() + pvector([11, 22, 3, 4, 5, 7]) + >>> e2.persistent() + pvector([1111, 22, 3, 4, 5, 7]) + + .. _freeze: + .. _thaw: + + freeze and thaw + ~~~~~~~~~~~~~~~ + These functions are great when your cozy immutable world has to interact with the evil mutable world outside. + + .. code:: python + + >>> from pyrsistent import freeze, thaw, v, m + >>> freeze([1, {'a': 3}]) + pvector([1, pmap({'a': 3})]) + >>> thaw(v(1, m(a=3))) + [1, {'a': 3}] + + Compatibility + ------------- + + Pyrsistent is developed and tested on Python 2.7, 3.5, 3.6, 3.7 and PyPy (Python 2 and 3 compatible). It will most + likely work on all other versions >= 3.4 but no guarantees are given. :) + + Compatibility issues + ~~~~~~~~~~~~~~~~~~~~ + + .. _27: https://github.com/tobgu/pyrsistent/issues/27 + + There is currently one known compatibility issue when comparing built in sets and frozensets to PSets as discussed in 27_. + It affects python 2 versions < 2.7.8 and python 3 versions < 3.4.0 and is due to a bug described in + http://bugs.python.org/issue8743. + + Comparisons will fail or be incorrect when using the set/frozenset as left hand side of the comparison. As a workaround + you need to either upgrade Python to a more recent version, avoid comparing sets/frozensets with PSets or always make + sure to convert both sides of the comparison to the same type before performing the comparison. + + Performance + ----------- + + Pyrsistent is developed with performance in mind. Still, while some operations are nearly on par with their built in, + mutable, counterparts in terms of speed, other operations are slower. In the cases where attempts at + optimizations have been done, speed has generally been valued over space. + + Pyrsistent comes with two API compatible flavors of PVector (on which PMap and PSet are based), one pure Python + implementation and one implemented as a C extension. The latter generally being 2 - 20 times faster than the former. + The C extension will be used automatically when possible. + + The pure python implementation is fully PyPy compatible. Running it under PyPy speeds operations up considerably if + the structures are used heavily (if JITed), for some cases the performance is almost on par with the built in counterparts. + + Type hints + ---------- + + PEP 561 style type hints for use with mypy and various editors are available for most types and functions in pyrsistent. + + Type classes for annotating your own code with pyrsistent types are also available under pyrsistent.typing. + + Installation + ------------ + + pip install pyrsistent + + Documentation + ------------- + + Available at http://pyrsistent.readthedocs.org/ + + Brief presentation available at http://slides.com/tobiasgustafsson/immutability-and-python/ + + Contributors + ------------ + + Tobias Gustafsson https://github.com/tobgu + + Christopher Armstrong https://github.com/radix + + Anders Hovmöller https://github.com/boxed + + Itamar Turner-Trauring https://github.com/itamarst + + Jonathan Lange https://github.com/jml + + Richard Futrell https://github.com/Futrell + + Jakob Hollenstein https://github.com/jkbjh + + David Honour https://github.com/foolswood + + David R. MacIver https://github.com/DRMacIver + + Marcus Ewert https://github.com/sarum90 + + Jean-Paul Calderone https://github.com/exarkun + + Douglas Treadwell https://github.com/douglas-treadwell + + Travis Parker https://github.com/teepark + + Julian Berman https://github.com/Julian + + Dennis Tomas https://github.com/dtomas + + Neil Vyas https://github.com/neilvyas + + doozr https://github.com/doozr + + Kamil Galuszka https://github.com/galuszkak + + Tsuyoshi Hombashi https://github.com/thombashi + + nattofriends https://github.com/nattofriends + + agberk https://github.com/agberk + + Waleed Khan https://github.com/arxanas + + Jean-Louis Fuchs https://github.com/ganwell + + Carlos Corbacho https://github.com/ccorbacho + + Felix Yan https://github.com/felixonmars + + benrg https://github.com/benrg + + Jere Lahelma https://github.com/je-l + + Max Taggart https://github.com/MaxTaggart + + Vincent Philippon https://github.com/vphilippon + + Semen Zhydenko https://github.com/ss18 + + Till Varoquaux https://github.com/till-varoquaux + + Michal Kowalik https://github.com/michalvi + + ossdev07 https://github.com/ossdev07 + + Kerry Olesen https://github.com/qhesz + + johnthagen https://github.com/johnthagen + + Contributing + ------------ + + Want to contribute? That's great! If you experience problems please log them on GitHub. If you want to contribute code, + please fork the repository and submit a pull request. + + Run tests + ~~~~~~~~~ + .. _tox: https://tox.readthedocs.io/en/latest/ + + Tests can be executed using tox_. + + Install tox: ``pip install tox`` + + Run test for Python 2.7: ``tox -epy27`` + + Release + ~~~~~~~ + * Update CHANGES.txt + * Update README with any new contributors and potential info needed. + * Update _pyrsistent_version.py + * python setup.py sdist upload + * Commit and tag with new version: git add -u . && git commit -m 'Prepare version vX.Y.Z' && git tag -a vX.Y.Z -m 'vX.Y.Z' + * Push commit and tags: git push && git push --tags + + Project status + -------------- + Pyrsistent can be considered stable and mature (who knows, there may even be a 1.0 some day :-)). The project is + maintained, bugs fixed, PRs reviewed and merged and new releases made. I currently do not have time for development + of new features or functionality which I don't have use for myself. I'm more than happy to take PRs for new + functionality though! + + There are a bunch of issues marked with ``enhancement`` and ``help wanted`` that contain requests for new functionality + that would be nice to include. The level of difficulty and extend of the issues varies, please reach out to me if you're + interested in working on any of them. + + If you feel that you have a grand master plan for where you would like Pyrsistent to go and have the time to put into + it please don't hesitate to discuss this with me and submit PRs for it. If all goes well I'd be more than happy to add + additional maintainers to the project! + +Platform: UNKNOWN +Classifier: Intended Audience :: Developers +Classifier: License :: OSI Approved :: MIT License +Classifier: Operating System :: OS Independent +Classifier: Programming Language :: Python :: 3.5 +Classifier: Programming Language :: Python :: 3.6 +Classifier: Programming Language :: Python :: 3.7 +Classifier: Programming Language :: Python :: Implementation :: PyPy diff --git a/third_party/python/pyrsistent/README b/third_party/python/pyrsistent/README new file mode 100644 index 0000000000..a4c24e49bd --- /dev/null +++ b/third_party/python/pyrsistent/README @@ -0,0 +1,725 @@ +Pyrsistent +========== +.. image:: https://travis-ci.org/tobgu/pyrsistent.png?branch=master + :target: https://travis-ci.org/tobgu/pyrsistent + +.. image:: https://badge.fury.io/py/pyrsistent.svg + :target: https://badge.fury.io/py/pyrsistent + +.. image:: https://coveralls.io/repos/tobgu/pyrsistent/badge.svg?branch=master&service=github + :target: https://coveralls.io/github/tobgu/pyrsistent?branch=master + + +.. _Pyrthon: https://www.github.com/tobgu/pyrthon/ + +Pyrsistent is a number of persistent collections (by some referred to as functional data structures). Persistent in +the sense that they are immutable. + +All methods on a data structure that would normally mutate it instead return a new copy of the structure containing the +requested updates. The original structure is left untouched. + +This will simplify the reasoning about what a program does since no hidden side effects ever can take place to these +data structures. You can rest assured that the object you hold a reference to will remain the same throughout its +lifetime and need not worry that somewhere five stack levels below you in the darkest corner of your application +someone has decided to remove that element that you expected to be there. + +Pyrsistent is influenced by persistent data structures such as those found in the standard library of Clojure. The +data structures are designed to share common elements through path copying. +It aims at taking these concepts and make them as pythonic as possible so that they can be easily integrated into any python +program without hassle. + +If you want to go all in on persistent data structures and use literal syntax to define them in your code rather +than function calls check out Pyrthon_. + +Examples +-------- +.. _Sequence: collections_ +.. _Hashable: collections_ +.. _Mapping: collections_ +.. _Mappings: collections_ +.. _Set: collections_ +.. _collections: https://docs.python.org/3/library/collections.abc.html +.. _documentation: http://pyrsistent.readthedocs.org/ + +The collection types and key features currently implemented are: + +* PVector_, similar to a python list +* PMap_, similar to dict +* PSet_, similar to set +* PRecord_, a PMap on steroids with fixed fields, optional type and invariant checking and much more +* PClass_, a Python class fixed fields, optional type and invariant checking and much more +* `Checked collections`_, PVector, PMap and PSet with optional type and invariance checks and more +* PBag, similar to collections.Counter +* PList, a classic singly linked list +* PDeque, similar to collections.deque +* Immutable object type (immutable) built on the named tuple +* freeze_ and thaw_ functions to convert between pythons standard collections and pyrsistent collections. +* Flexible transformations_ of arbitrarily complex structures built from PMaps and PVectors. + +Below are examples of common usage patterns for some of the structures and features. More information and +full documentation for all data structures is available in the documentation_. + +.. _PVector: + +PVector +~~~~~~~ +With full support for the Sequence_ protocol PVector is meant as a drop in replacement to the built in list from a readers +point of view. Write operations of course differ since no in place mutation is done but naming should be in line +with corresponding operations on the built in list. + +Support for the Hashable_ protocol also means that it can be used as key in Mappings_. + +Appends are amortized O(1). Random access and insert is log32(n) where n is the size of the vector. + +.. code:: python + + >>> from pyrsistent import v, pvector + + # No mutation of vectors once created, instead they + # are "evolved" leaving the original untouched + >>> v1 = v(1, 2, 3) + >>> v2 = v1.append(4) + >>> v3 = v2.set(1, 5) + >>> v1 + pvector([1, 2, 3]) + >>> v2 + pvector([1, 2, 3, 4]) + >>> v3 + pvector([1, 5, 3, 4]) + + # Random access and slicing + >>> v3[1] + 5 + >>> v3[1:3] + pvector([5, 3]) + + # Iteration + >>> list(x + 1 for x in v3) + [2, 6, 4, 5] + >>> pvector(2 * x for x in range(3)) + pvector([0, 2, 4]) + +.. _PMap: + +PMap +~~~~ +With full support for the Mapping_ protocol PMap is meant as a drop in replacement to the built in dict from a readers point +of view. Support for the Hashable_ protocol also means that it can be used as key in other Mappings_. + +Random access and insert is log32(n) where n is the size of the map. + +.. code:: python + + >>> from pyrsistent import m, pmap, v + + # No mutation of maps once created, instead they are + # "evolved" leaving the original untouched + >>> m1 = m(a=1, b=2) + >>> m2 = m1.set('c', 3) + >>> m3 = m2.set('a', 5) + >>> m1 + pmap({'a': 1, 'b': 2}) + >>> m2 + pmap({'a': 1, 'c': 3, 'b': 2}) + >>> m3 + pmap({'a': 5, 'c': 3, 'b': 2}) + >>> m3['a'] + 5 + + # Evolution of nested persistent structures + >>> m4 = m(a=5, b=6, c=v(1, 2)) + >>> m4.transform(('c', 1), 17) + pmap({'a': 5, 'c': pvector([1, 17]), 'b': 6}) + >>> m5 = m(a=1, b=2) + + # Evolve by merging with other mappings + >>> m5.update(m(a=2, c=3), {'a': 17, 'd': 35}) + pmap({'a': 17, 'c': 3, 'b': 2, 'd': 35}) + >>> pmap({'x': 1, 'y': 2}) + pmap({'y': 3, 'z': 4}) + pmap({'y': 3, 'x': 1, 'z': 4}) + + # Dict-like methods to convert to list and iterate + >>> m3.items() + pvector([('a', 5), ('c', 3), ('b', 2)]) + >>> list(m3) + ['a', 'c', 'b'] + +.. _PSet: + +PSet +~~~~ +With full support for the Set_ protocol PSet is meant as a drop in replacement to the built in set from a readers point +of view. Support for the Hashable_ protocol also means that it can be used as key in Mappings_. + +Random access and insert is log32(n) where n is the size of the set. + +.. code:: python + + >>> from pyrsistent import s + + # No mutation of sets once created, you know the story... + >>> s1 = s(1, 2, 3, 2) + >>> s2 = s1.add(4) + >>> s3 = s1.remove(1) + >>> s1 + pset([1, 2, 3]) + >>> s2 + pset([1, 2, 3, 4]) + >>> s3 + pset([2, 3]) + + # Full support for set operations + >>> s1 | s(3, 4, 5) + pset([1, 2, 3, 4, 5]) + >>> s1 & s(3, 4, 5) + pset([3]) + >>> s1 < s2 + True + >>> s1 < s(3, 4, 5) + False + +.. _PRecord: + +PRecord +~~~~~~~ +A PRecord is a PMap with a fixed set of specified fields. Records are declared as python classes inheriting +from PRecord. Because it is a PMap it has full support for all Mapping methods such as iteration and element +access using subscript notation. + +.. code:: python + + >>> from pyrsistent import PRecord, field + >>> class ARecord(PRecord): + ... x = field() + ... + >>> r = ARecord(x=3) + >>> r + ARecord(x=3) + >>> r.x + 3 + >>> r.set(x=2) + ARecord(x=2) + >>> r.set(y=2) + Traceback (most recent call last): + AttributeError: 'y' is not among the specified fields for ARecord + +Type information +**************** +It is possible to add type information to the record to enforce type checks. Multiple allowed types can be specified +by providing an iterable of types. + +.. code:: python + + >>> class BRecord(PRecord): + ... x = field(type=int) + ... y = field(type=(int, type(None))) + ... + >>> BRecord(x=3, y=None) + BRecord(y=None, x=3) + >>> BRecord(x=3.0) + Traceback (most recent call last): + PTypeError: Invalid type for field BRecord.x, was float + + +Custom types (classes) that are iterable should be wrapped in a tuple to prevent their +members being added to the set of valid types. Although Enums in particular are now +supported without wrapping, see #83 for more information. + +Mandatory fields +**************** +Fields are not mandatory by default but can be specified as such. If fields are missing an +*InvariantException* will be thrown which contains information about the missing fields. + +.. code:: python + + >>> from pyrsistent import InvariantException + >>> class CRecord(PRecord): + ... x = field(mandatory=True) + ... + >>> r = CRecord(x=3) + >>> try: + ... r.discard('x') + ... except InvariantException as e: + ... print(e.missing_fields) + ... + ('CRecord.x',) + +Invariants +********** +It is possible to add invariants that must hold when evolving the record. Invariants can be +specified on both field and record level. If invariants fail an *InvariantException* will be +thrown which contains information about the failing invariants. An invariant function should +return a tuple consisting of a boolean that tells if the invariant holds or not and an object +describing the invariant. This object can later be used to identify which invariant that failed. + +The global invariant function is only executed if all field invariants hold. + +Global invariants are inherited to subclasses. + +.. code:: python + + >>> class RestrictedVector(PRecord): + ... __invariant__ = lambda r: (r.y >= r.x, 'x larger than y') + ... x = field(invariant=lambda x: (x > 0, 'x negative')) + ... y = field(invariant=lambda y: (y > 0, 'y negative')) + ... + >>> r = RestrictedVector(y=3, x=2) + >>> try: + ... r.set(x=-1, y=-2) + ... except InvariantException as e: + ... print(e.invariant_errors) + ... + ('y negative', 'x negative') + >>> try: + ... r.set(x=2, y=1) + ... except InvariantException as e: + ... print(e.invariant_errors) + ... + ('x larger than y',) + +Invariants may also contain multiple assertions. For those cases the invariant function should +return a tuple of invariant tuples as described above. This structure is reflected in the +invariant_errors attribute of the exception which will contain tuples with data from all failed +invariants. Eg: + +.. code:: python + + >>> class EvenX(PRecord): + ... x = field(invariant=lambda x: ((x > 0, 'x negative'), (x % 2 == 0, 'x odd'))) + ... + >>> try: + ... EvenX(x=-1) + ... except InvariantException as e: + ... print(e.invariant_errors) + ... + (('x negative', 'x odd'),) + + +Factories +********* +It's possible to specify factory functions for fields. The factory function receives whatever +is supplied as field value and the actual returned by the factory is assigned to the field +given that any type and invariant checks hold. +PRecords have a default factory specified as a static function on the class, create(). It takes +a *Mapping* as argument and returns an instance of the specific record. +If a record has fields of type PRecord the create() method of that record will +be called to create the "sub record" if no factory has explicitly been specified to override +this behaviour. + +.. code:: python + + >>> class DRecord(PRecord): + ... x = field(factory=int) + ... + >>> class ERecord(PRecord): + ... d = field(type=DRecord) + ... + >>> ERecord.create({'d': {'x': '1'}}) + ERecord(d=DRecord(x=1)) + +Collection fields +***************** +It is also possible to have fields with ``pyrsistent`` collections. + +.. code:: python + + >>> from pyrsistent import pset_field, pmap_field, pvector_field + >>> class MultiRecord(PRecord): + ... set_of_ints = pset_field(int) + ... map_int_to_str = pmap_field(int, str) + ... vector_of_strs = pvector_field(str) + ... + +Serialization +************* +PRecords support serialization back to dicts. Default serialization will take keys and values +"as is" and output them into a dict. It is possible to specify custom serialization functions +to take care of fields that require special treatment. + +.. code:: python + + >>> from datetime import date + >>> class Person(PRecord): + ... name = field(type=unicode) + ... birth_date = field(type=date, + ... serializer=lambda format, d: d.strftime(format['date'])) + ... + >>> john = Person(name=u'John', birth_date=date(1985, 10, 21)) + >>> john.serialize({'date': '%Y-%m-%d'}) + {'birth_date': '1985-10-21', 'name': u'John'} + + +.. _instar: https://github.com/boxed/instar/ + +.. _PClass: + +PClass +~~~~~~ +A PClass is a python class with a fixed set of specified fields. PClasses are declared as python classes inheriting +from PClass. It is defined the same way that PRecords are and behaves like a PRecord in all aspects except that it +is not a PMap and hence not a collection but rather a plain Python object. + +.. code:: python + + >>> from pyrsistent import PClass, field + >>> class AClass(PClass): + ... x = field() + ... + >>> a = AClass(x=3) + >>> a + AClass(x=3) + >>> a.x + 3 + + +Checked collections +~~~~~~~~~~~~~~~~~~~ +Checked collections currently come in three flavors: CheckedPVector, CheckedPMap and CheckedPSet. + +.. code:: python + + >>> from pyrsistent import CheckedPVector, CheckedPMap, CheckedPSet, thaw + >>> class Positives(CheckedPSet): + ... __type__ = (long, int) + ... __invariant__ = lambda n: (n >= 0, 'Negative') + ... + >>> class Lottery(PRecord): + ... name = field(type=str) + ... numbers = field(type=Positives, invariant=lambda p: (len(p) > 0, 'No numbers')) + ... + >>> class Lotteries(CheckedPVector): + ... __type__ = Lottery + ... + >>> class LotteriesByDate(CheckedPMap): + ... __key_type__ = date + ... __value_type__ = Lotteries + ... + >>> lotteries = LotteriesByDate.create({date(2015, 2, 15): [{'name': 'SuperLotto', 'numbers': {1, 2, 3}}, + ... {'name': 'MegaLotto', 'numbers': {4, 5, 6}}], + ... date(2015, 2, 16): [{'name': 'SuperLotto', 'numbers': {3, 2, 1}}, + ... {'name': 'MegaLotto', 'numbers': {6, 5, 4}}]}) + >>> lotteries + LotteriesByDate({datetime.date(2015, 2, 15): Lotteries([Lottery(numbers=Positives([1, 2, 3]), name='SuperLotto'), Lottery(numbers=Positives([4, 5, 6]), name='MegaLotto')]), datetime.date(2015, 2, 16): Lotteries([Lottery(numbers=Positives([1, 2, 3]), name='SuperLotto'), Lottery(numbers=Positives([4, 5, 6]), name='MegaLotto')])}) + + # The checked versions support all operations that the corresponding + # unchecked types do + >>> lottery_0215 = lotteries[date(2015, 2, 15)] + >>> lottery_0215.transform([0, 'name'], 'SuperDuperLotto') + Lotteries([Lottery(numbers=Positives([1, 2, 3]), name='SuperDuperLotto'), Lottery(numbers=Positives([4, 5, 6]), name='MegaLotto')]) + + # But also makes asserts that types and invariants hold + >>> lottery_0215.transform([0, 'name'], 999) + Traceback (most recent call last): + PTypeError: Invalid type for field Lottery.name, was int + + >>> lottery_0215.transform([0, 'numbers'], set()) + Traceback (most recent call last): + InvariantException: Field invariant failed + + # They can be converted back to python built ins with either thaw() + # or serialize() (which provides possibilities to customize serialization) + >>> thaw(lottery_0215) + [{'numbers': set([1, 2, 3]), 'name': 'SuperLotto'}, {'numbers': set([4, 5, 6]), 'name': 'MegaLotto'}] + >>> lottery_0215.serialize() + [{'numbers': set([1, 2, 3]), 'name': 'SuperLotto'}, {'numbers': set([4, 5, 6]), 'name': 'MegaLotto'}] + +.. _transformations: + +Transformations +~~~~~~~~~~~~~~~ +Transformations are inspired by the cool library instar_ for Clojure. They let you evolve PMaps and PVectors +with arbitrarily deep/complex nesting using simple syntax and flexible matching syntax. + +The first argument to transformation is the path that points out the value to transform. The +second is the transformation to perform. If the transformation is callable it will be applied +to the value(s) matching the path. The path may also contain callables. In that case they are +treated as matchers. If the matcher returns True for a specific key it is considered for transformation. + +.. code:: python + + # Basic examples + >>> from pyrsistent import inc, freeze, thaw, rex, ny, discard + >>> v1 = freeze([1, 2, 3, 4, 5]) + >>> v1.transform([2], inc) + pvector([1, 2, 4, 4, 5]) + >>> v1.transform([lambda ix: 0 < ix < 4], 8) + pvector([1, 8, 8, 8, 5]) + >>> v1.transform([lambda ix, v: ix == 0 or v == 5], 0) + pvector([0, 2, 3, 4, 0]) + + # The (a)ny matcher can be used to match anything + >>> v1.transform([ny], 8) + pvector([8, 8, 8, 8, 8]) + + # Regular expressions can be used for matching + >>> scores = freeze({'John': 12, 'Joseph': 34, 'Sara': 23}) + >>> scores.transform([rex('^Jo')], 0) + pmap({'Joseph': 0, 'Sara': 23, 'John': 0}) + + # Transformations can be done on arbitrarily deep structures + >>> news_paper = freeze({'articles': [{'author': 'Sara', 'content': 'A short article'}, + ... {'author': 'Steve', 'content': 'A slightly longer article'}], + ... 'weather': {'temperature': '11C', 'wind': '5m/s'}}) + >>> short_news = news_paper.transform(['articles', ny, 'content'], lambda c: c[:25] + '...' if len(c) > 25 else c) + >>> very_short_news = news_paper.transform(['articles', ny, 'content'], lambda c: c[:15] + '...' if len(c) > 15 else c) + >>> very_short_news.articles[0].content + 'A short article' + >>> very_short_news.articles[1].content + 'A slightly long...' + + # When nothing has been transformed the original data structure is kept + >>> short_news is news_paper + True + >>> very_short_news is news_paper + False + >>> very_short_news.articles[0] is news_paper.articles[0] + True + + # There is a special transformation that can be used to discard elements. Also + # multiple transformations can be applied in one call + >>> thaw(news_paper.transform(['weather'], discard, ['articles', ny, 'content'], discard)) + {'articles': [{'author': 'Sara'}, {'author': 'Steve'}]} + +Evolvers +~~~~~~~~ +PVector, PMap and PSet all have support for a concept dubbed *evolvers*. An evolver acts like a mutable +view of the underlying persistent data structure with "transaction like" semantics. No updates of the original +data structure is ever performed, it is still fully immutable. + +The evolvers have a very limited API by design to discourage excessive, and inappropriate, usage as that would +take us down the mutable road. In principle only basic mutation and element access functions are supported. +Check out the documentation_ of each data structure for specific examples. + +Examples of when you may want to use an evolver instead of working directly with the data structure include: + +* Multiple updates are done to the same data structure and the intermediate results are of no + interest. In this case using an evolver may be a more efficient and easier to work with. +* You need to pass a vector into a legacy function or a function that you have no control + over which performs in place mutations. In this case pass an evolver instance + instead and then create a new pvector from the evolver once the function returns. + +.. code:: python + + >>> from pyrsistent import v + + # In place mutation as when working with the built in counterpart + >>> v1 = v(1, 2, 3) + >>> e = v1.evolver() + >>> e[1] = 22 + >>> e = e.append(4) + >>> e = e.extend([5, 6]) + >>> e[5] += 1 + >>> len(e) + 6 + + # The evolver is considered *dirty* when it contains changes compared to the underlying vector + >>> e.is_dirty() + True + + # But the underlying pvector still remains untouched + >>> v1 + pvector([1, 2, 3]) + + # Once satisfied with the updates you can produce a new pvector containing the updates. + # The new pvector will share data with the original pvector in the same way that would have + # been done if only using operations on the pvector. + >>> v2 = e.persistent() + >>> v2 + pvector([1, 22, 3, 4, 5, 7]) + + # The evolver is now no longer considered *dirty* as it contains no differences compared to the + # pvector just produced. + >>> e.is_dirty() + False + + # You may continue to work with the same evolver without affecting the content of v2 + >>> e[0] = 11 + + # Or create a new evolver from v2. The two evolvers can be updated independently but will both + # share data with v2 where possible. + >>> e2 = v2.evolver() + >>> e2[0] = 1111 + >>> e.persistent() + pvector([11, 22, 3, 4, 5, 7]) + >>> e2.persistent() + pvector([1111, 22, 3, 4, 5, 7]) + +.. _freeze: +.. _thaw: + +freeze and thaw +~~~~~~~~~~~~~~~ +These functions are great when your cozy immutable world has to interact with the evil mutable world outside. + +.. code:: python + + >>> from pyrsistent import freeze, thaw, v, m + >>> freeze([1, {'a': 3}]) + pvector([1, pmap({'a': 3})]) + >>> thaw(v(1, m(a=3))) + [1, {'a': 3}] + +Compatibility +------------- + +Pyrsistent is developed and tested on Python 2.7, 3.5, 3.6, 3.7 and PyPy (Python 2 and 3 compatible). It will most +likely work on all other versions >= 3.4 but no guarantees are given. :) + +Compatibility issues +~~~~~~~~~~~~~~~~~~~~ + +.. _27: https://github.com/tobgu/pyrsistent/issues/27 + +There is currently one known compatibility issue when comparing built in sets and frozensets to PSets as discussed in 27_. +It affects python 2 versions < 2.7.8 and python 3 versions < 3.4.0 and is due to a bug described in +http://bugs.python.org/issue8743. + +Comparisons will fail or be incorrect when using the set/frozenset as left hand side of the comparison. As a workaround +you need to either upgrade Python to a more recent version, avoid comparing sets/frozensets with PSets or always make +sure to convert both sides of the comparison to the same type before performing the comparison. + +Performance +----------- + +Pyrsistent is developed with performance in mind. Still, while some operations are nearly on par with their built in, +mutable, counterparts in terms of speed, other operations are slower. In the cases where attempts at +optimizations have been done, speed has generally been valued over space. + +Pyrsistent comes with two API compatible flavors of PVector (on which PMap and PSet are based), one pure Python +implementation and one implemented as a C extension. The latter generally being 2 - 20 times faster than the former. +The C extension will be used automatically when possible. + +The pure python implementation is fully PyPy compatible. Running it under PyPy speeds operations up considerably if +the structures are used heavily (if JITed), for some cases the performance is almost on par with the built in counterparts. + +Type hints +---------- + +PEP 561 style type hints for use with mypy and various editors are available for most types and functions in pyrsistent. + +Type classes for annotating your own code with pyrsistent types are also available under pyrsistent.typing. + +Installation +------------ + +pip install pyrsistent + +Documentation +------------- + +Available at http://pyrsistent.readthedocs.org/ + +Brief presentation available at http://slides.com/tobiasgustafsson/immutability-and-python/ + +Contributors +------------ + +Tobias Gustafsson https://github.com/tobgu + +Christopher Armstrong https://github.com/radix + +Anders Hovmöller https://github.com/boxed + +Itamar Turner-Trauring https://github.com/itamarst + +Jonathan Lange https://github.com/jml + +Richard Futrell https://github.com/Futrell + +Jakob Hollenstein https://github.com/jkbjh + +David Honour https://github.com/foolswood + +David R. MacIver https://github.com/DRMacIver + +Marcus Ewert https://github.com/sarum90 + +Jean-Paul Calderone https://github.com/exarkun + +Douglas Treadwell https://github.com/douglas-treadwell + +Travis Parker https://github.com/teepark + +Julian Berman https://github.com/Julian + +Dennis Tomas https://github.com/dtomas + +Neil Vyas https://github.com/neilvyas + +doozr https://github.com/doozr + +Kamil Galuszka https://github.com/galuszkak + +Tsuyoshi Hombashi https://github.com/thombashi + +nattofriends https://github.com/nattofriends + +agberk https://github.com/agberk + +Waleed Khan https://github.com/arxanas + +Jean-Louis Fuchs https://github.com/ganwell + +Carlos Corbacho https://github.com/ccorbacho + +Felix Yan https://github.com/felixonmars + +benrg https://github.com/benrg + +Jere Lahelma https://github.com/je-l + +Max Taggart https://github.com/MaxTaggart + +Vincent Philippon https://github.com/vphilippon + +Semen Zhydenko https://github.com/ss18 + +Till Varoquaux https://github.com/till-varoquaux + +Michal Kowalik https://github.com/michalvi + +ossdev07 https://github.com/ossdev07 + +Kerry Olesen https://github.com/qhesz + +johnthagen https://github.com/johnthagen + +Contributing +------------ + +Want to contribute? That's great! If you experience problems please log them on GitHub. If you want to contribute code, +please fork the repository and submit a pull request. + +Run tests +~~~~~~~~~ +.. _tox: https://tox.readthedocs.io/en/latest/ + +Tests can be executed using tox_. + +Install tox: ``pip install tox`` + +Run test for Python 2.7: ``tox -epy27`` + +Release +~~~~~~~ +* Update CHANGES.txt +* Update README with any new contributors and potential info needed. +* Update _pyrsistent_version.py +* python setup.py sdist upload +* Commit and tag with new version: git add -u . && git commit -m 'Prepare version vX.Y.Z' && git tag -a vX.Y.Z -m 'vX.Y.Z' +* Push commit and tags: git push && git push --tags + +Project status +-------------- +Pyrsistent can be considered stable and mature (who knows, there may even be a 1.0 some day :-)). The project is +maintained, bugs fixed, PRs reviewed and merged and new releases made. I currently do not have time for development +of new features or functionality which I don't have use for myself. I'm more than happy to take PRs for new +functionality though! + +There are a bunch of issues marked with ``enhancement`` and ``help wanted`` that contain requests for new functionality +that would be nice to include. The level of difficulty and extend of the issues varies, please reach out to me if you're +interested in working on any of them. + +If you feel that you have a grand master plan for where you would like Pyrsistent to go and have the time to put into +it please don't hesitate to discuss this with me and submit PRs for it. If all goes well I'd be more than happy to add +additional maintainers to the project! diff --git a/third_party/python/pyrsistent/README.rst b/third_party/python/pyrsistent/README.rst new file mode 100644 index 0000000000..a4c24e49bd --- /dev/null +++ b/third_party/python/pyrsistent/README.rst @@ -0,0 +1,725 @@ +Pyrsistent +========== +.. image:: https://travis-ci.org/tobgu/pyrsistent.png?branch=master + :target: https://travis-ci.org/tobgu/pyrsistent + +.. image:: https://badge.fury.io/py/pyrsistent.svg + :target: https://badge.fury.io/py/pyrsistent + +.. image:: https://coveralls.io/repos/tobgu/pyrsistent/badge.svg?branch=master&service=github + :target: https://coveralls.io/github/tobgu/pyrsistent?branch=master + + +.. _Pyrthon: https://www.github.com/tobgu/pyrthon/ + +Pyrsistent is a number of persistent collections (by some referred to as functional data structures). Persistent in +the sense that they are immutable. + +All methods on a data structure that would normally mutate it instead return a new copy of the structure containing the +requested updates. The original structure is left untouched. + +This will simplify the reasoning about what a program does since no hidden side effects ever can take place to these +data structures. You can rest assured that the object you hold a reference to will remain the same throughout its +lifetime and need not worry that somewhere five stack levels below you in the darkest corner of your application +someone has decided to remove that element that you expected to be there. + +Pyrsistent is influenced by persistent data structures such as those found in the standard library of Clojure. The +data structures are designed to share common elements through path copying. +It aims at taking these concepts and make them as pythonic as possible so that they can be easily integrated into any python +program without hassle. + +If you want to go all in on persistent data structures and use literal syntax to define them in your code rather +than function calls check out Pyrthon_. + +Examples +-------- +.. _Sequence: collections_ +.. _Hashable: collections_ +.. _Mapping: collections_ +.. _Mappings: collections_ +.. _Set: collections_ +.. _collections: https://docs.python.org/3/library/collections.abc.html +.. _documentation: http://pyrsistent.readthedocs.org/ + +The collection types and key features currently implemented are: + +* PVector_, similar to a python list +* PMap_, similar to dict +* PSet_, similar to set +* PRecord_, a PMap on steroids with fixed fields, optional type and invariant checking and much more +* PClass_, a Python class fixed fields, optional type and invariant checking and much more +* `Checked collections`_, PVector, PMap and PSet with optional type and invariance checks and more +* PBag, similar to collections.Counter +* PList, a classic singly linked list +* PDeque, similar to collections.deque +* Immutable object type (immutable) built on the named tuple +* freeze_ and thaw_ functions to convert between pythons standard collections and pyrsistent collections. +* Flexible transformations_ of arbitrarily complex structures built from PMaps and PVectors. + +Below are examples of common usage patterns for some of the structures and features. More information and +full documentation for all data structures is available in the documentation_. + +.. _PVector: + +PVector +~~~~~~~ +With full support for the Sequence_ protocol PVector is meant as a drop in replacement to the built in list from a readers +point of view. Write operations of course differ since no in place mutation is done but naming should be in line +with corresponding operations on the built in list. + +Support for the Hashable_ protocol also means that it can be used as key in Mappings_. + +Appends are amortized O(1). Random access and insert is log32(n) where n is the size of the vector. + +.. code:: python + + >>> from pyrsistent import v, pvector + + # No mutation of vectors once created, instead they + # are "evolved" leaving the original untouched + >>> v1 = v(1, 2, 3) + >>> v2 = v1.append(4) + >>> v3 = v2.set(1, 5) + >>> v1 + pvector([1, 2, 3]) + >>> v2 + pvector([1, 2, 3, 4]) + >>> v3 + pvector([1, 5, 3, 4]) + + # Random access and slicing + >>> v3[1] + 5 + >>> v3[1:3] + pvector([5, 3]) + + # Iteration + >>> list(x + 1 for x in v3) + [2, 6, 4, 5] + >>> pvector(2 * x for x in range(3)) + pvector([0, 2, 4]) + +.. _PMap: + +PMap +~~~~ +With full support for the Mapping_ protocol PMap is meant as a drop in replacement to the built in dict from a readers point +of view. Support for the Hashable_ protocol also means that it can be used as key in other Mappings_. + +Random access and insert is log32(n) where n is the size of the map. + +.. code:: python + + >>> from pyrsistent import m, pmap, v + + # No mutation of maps once created, instead they are + # "evolved" leaving the original untouched + >>> m1 = m(a=1, b=2) + >>> m2 = m1.set('c', 3) + >>> m3 = m2.set('a', 5) + >>> m1 + pmap({'a': 1, 'b': 2}) + >>> m2 + pmap({'a': 1, 'c': 3, 'b': 2}) + >>> m3 + pmap({'a': 5, 'c': 3, 'b': 2}) + >>> m3['a'] + 5 + + # Evolution of nested persistent structures + >>> m4 = m(a=5, b=6, c=v(1, 2)) + >>> m4.transform(('c', 1), 17) + pmap({'a': 5, 'c': pvector([1, 17]), 'b': 6}) + >>> m5 = m(a=1, b=2) + + # Evolve by merging with other mappings + >>> m5.update(m(a=2, c=3), {'a': 17, 'd': 35}) + pmap({'a': 17, 'c': 3, 'b': 2, 'd': 35}) + >>> pmap({'x': 1, 'y': 2}) + pmap({'y': 3, 'z': 4}) + pmap({'y': 3, 'x': 1, 'z': 4}) + + # Dict-like methods to convert to list and iterate + >>> m3.items() + pvector([('a', 5), ('c', 3), ('b', 2)]) + >>> list(m3) + ['a', 'c', 'b'] + +.. _PSet: + +PSet +~~~~ +With full support for the Set_ protocol PSet is meant as a drop in replacement to the built in set from a readers point +of view. Support for the Hashable_ protocol also means that it can be used as key in Mappings_. + +Random access and insert is log32(n) where n is the size of the set. + +.. code:: python + + >>> from pyrsistent import s + + # No mutation of sets once created, you know the story... + >>> s1 = s(1, 2, 3, 2) + >>> s2 = s1.add(4) + >>> s3 = s1.remove(1) + >>> s1 + pset([1, 2, 3]) + >>> s2 + pset([1, 2, 3, 4]) + >>> s3 + pset([2, 3]) + + # Full support for set operations + >>> s1 | s(3, 4, 5) + pset([1, 2, 3, 4, 5]) + >>> s1 & s(3, 4, 5) + pset([3]) + >>> s1 < s2 + True + >>> s1 < s(3, 4, 5) + False + +.. _PRecord: + +PRecord +~~~~~~~ +A PRecord is a PMap with a fixed set of specified fields. Records are declared as python classes inheriting +from PRecord. Because it is a PMap it has full support for all Mapping methods such as iteration and element +access using subscript notation. + +.. code:: python + + >>> from pyrsistent import PRecord, field + >>> class ARecord(PRecord): + ... x = field() + ... + >>> r = ARecord(x=3) + >>> r + ARecord(x=3) + >>> r.x + 3 + >>> r.set(x=2) + ARecord(x=2) + >>> r.set(y=2) + Traceback (most recent call last): + AttributeError: 'y' is not among the specified fields for ARecord + +Type information +**************** +It is possible to add type information to the record to enforce type checks. Multiple allowed types can be specified +by providing an iterable of types. + +.. code:: python + + >>> class BRecord(PRecord): + ... x = field(type=int) + ... y = field(type=(int, type(None))) + ... + >>> BRecord(x=3, y=None) + BRecord(y=None, x=3) + >>> BRecord(x=3.0) + Traceback (most recent call last): + PTypeError: Invalid type for field BRecord.x, was float + + +Custom types (classes) that are iterable should be wrapped in a tuple to prevent their +members being added to the set of valid types. Although Enums in particular are now +supported without wrapping, see #83 for more information. + +Mandatory fields +**************** +Fields are not mandatory by default but can be specified as such. If fields are missing an +*InvariantException* will be thrown which contains information about the missing fields. + +.. code:: python + + >>> from pyrsistent import InvariantException + >>> class CRecord(PRecord): + ... x = field(mandatory=True) + ... + >>> r = CRecord(x=3) + >>> try: + ... r.discard('x') + ... except InvariantException as e: + ... print(e.missing_fields) + ... + ('CRecord.x',) + +Invariants +********** +It is possible to add invariants that must hold when evolving the record. Invariants can be +specified on both field and record level. If invariants fail an *InvariantException* will be +thrown which contains information about the failing invariants. An invariant function should +return a tuple consisting of a boolean that tells if the invariant holds or not and an object +describing the invariant. This object can later be used to identify which invariant that failed. + +The global invariant function is only executed if all field invariants hold. + +Global invariants are inherited to subclasses. + +.. code:: python + + >>> class RestrictedVector(PRecord): + ... __invariant__ = lambda r: (r.y >= r.x, 'x larger than y') + ... x = field(invariant=lambda x: (x > 0, 'x negative')) + ... y = field(invariant=lambda y: (y > 0, 'y negative')) + ... + >>> r = RestrictedVector(y=3, x=2) + >>> try: + ... r.set(x=-1, y=-2) + ... except InvariantException as e: + ... print(e.invariant_errors) + ... + ('y negative', 'x negative') + >>> try: + ... r.set(x=2, y=1) + ... except InvariantException as e: + ... print(e.invariant_errors) + ... + ('x larger than y',) + +Invariants may also contain multiple assertions. For those cases the invariant function should +return a tuple of invariant tuples as described above. This structure is reflected in the +invariant_errors attribute of the exception which will contain tuples with data from all failed +invariants. Eg: + +.. code:: python + + >>> class EvenX(PRecord): + ... x = field(invariant=lambda x: ((x > 0, 'x negative'), (x % 2 == 0, 'x odd'))) + ... + >>> try: + ... EvenX(x=-1) + ... except InvariantException as e: + ... print(e.invariant_errors) + ... + (('x negative', 'x odd'),) + + +Factories +********* +It's possible to specify factory functions for fields. The factory function receives whatever +is supplied as field value and the actual returned by the factory is assigned to the field +given that any type and invariant checks hold. +PRecords have a default factory specified as a static function on the class, create(). It takes +a *Mapping* as argument and returns an instance of the specific record. +If a record has fields of type PRecord the create() method of that record will +be called to create the "sub record" if no factory has explicitly been specified to override +this behaviour. + +.. code:: python + + >>> class DRecord(PRecord): + ... x = field(factory=int) + ... + >>> class ERecord(PRecord): + ... d = field(type=DRecord) + ... + >>> ERecord.create({'d': {'x': '1'}}) + ERecord(d=DRecord(x=1)) + +Collection fields +***************** +It is also possible to have fields with ``pyrsistent`` collections. + +.. code:: python + + >>> from pyrsistent import pset_field, pmap_field, pvector_field + >>> class MultiRecord(PRecord): + ... set_of_ints = pset_field(int) + ... map_int_to_str = pmap_field(int, str) + ... vector_of_strs = pvector_field(str) + ... + +Serialization +************* +PRecords support serialization back to dicts. Default serialization will take keys and values +"as is" and output them into a dict. It is possible to specify custom serialization functions +to take care of fields that require special treatment. + +.. code:: python + + >>> from datetime import date + >>> class Person(PRecord): + ... name = field(type=unicode) + ... birth_date = field(type=date, + ... serializer=lambda format, d: d.strftime(format['date'])) + ... + >>> john = Person(name=u'John', birth_date=date(1985, 10, 21)) + >>> john.serialize({'date': '%Y-%m-%d'}) + {'birth_date': '1985-10-21', 'name': u'John'} + + +.. _instar: https://github.com/boxed/instar/ + +.. _PClass: + +PClass +~~~~~~ +A PClass is a python class with a fixed set of specified fields. PClasses are declared as python classes inheriting +from PClass. It is defined the same way that PRecords are and behaves like a PRecord in all aspects except that it +is not a PMap and hence not a collection but rather a plain Python object. + +.. code:: python + + >>> from pyrsistent import PClass, field + >>> class AClass(PClass): + ... x = field() + ... + >>> a = AClass(x=3) + >>> a + AClass(x=3) + >>> a.x + 3 + + +Checked collections +~~~~~~~~~~~~~~~~~~~ +Checked collections currently come in three flavors: CheckedPVector, CheckedPMap and CheckedPSet. + +.. code:: python + + >>> from pyrsistent import CheckedPVector, CheckedPMap, CheckedPSet, thaw + >>> class Positives(CheckedPSet): + ... __type__ = (long, int) + ... __invariant__ = lambda n: (n >= 0, 'Negative') + ... + >>> class Lottery(PRecord): + ... name = field(type=str) + ... numbers = field(type=Positives, invariant=lambda p: (len(p) > 0, 'No numbers')) + ... + >>> class Lotteries(CheckedPVector): + ... __type__ = Lottery + ... + >>> class LotteriesByDate(CheckedPMap): + ... __key_type__ = date + ... __value_type__ = Lotteries + ... + >>> lotteries = LotteriesByDate.create({date(2015, 2, 15): [{'name': 'SuperLotto', 'numbers': {1, 2, 3}}, + ... {'name': 'MegaLotto', 'numbers': {4, 5, 6}}], + ... date(2015, 2, 16): [{'name': 'SuperLotto', 'numbers': {3, 2, 1}}, + ... {'name': 'MegaLotto', 'numbers': {6, 5, 4}}]}) + >>> lotteries + LotteriesByDate({datetime.date(2015, 2, 15): Lotteries([Lottery(numbers=Positives([1, 2, 3]), name='SuperLotto'), Lottery(numbers=Positives([4, 5, 6]), name='MegaLotto')]), datetime.date(2015, 2, 16): Lotteries([Lottery(numbers=Positives([1, 2, 3]), name='SuperLotto'), Lottery(numbers=Positives([4, 5, 6]), name='MegaLotto')])}) + + # The checked versions support all operations that the corresponding + # unchecked types do + >>> lottery_0215 = lotteries[date(2015, 2, 15)] + >>> lottery_0215.transform([0, 'name'], 'SuperDuperLotto') + Lotteries([Lottery(numbers=Positives([1, 2, 3]), name='SuperDuperLotto'), Lottery(numbers=Positives([4, 5, 6]), name='MegaLotto')]) + + # But also makes asserts that types and invariants hold + >>> lottery_0215.transform([0, 'name'], 999) + Traceback (most recent call last): + PTypeError: Invalid type for field Lottery.name, was int + + >>> lottery_0215.transform([0, 'numbers'], set()) + Traceback (most recent call last): + InvariantException: Field invariant failed + + # They can be converted back to python built ins with either thaw() + # or serialize() (which provides possibilities to customize serialization) + >>> thaw(lottery_0215) + [{'numbers': set([1, 2, 3]), 'name': 'SuperLotto'}, {'numbers': set([4, 5, 6]), 'name': 'MegaLotto'}] + >>> lottery_0215.serialize() + [{'numbers': set([1, 2, 3]), 'name': 'SuperLotto'}, {'numbers': set([4, 5, 6]), 'name': 'MegaLotto'}] + +.. _transformations: + +Transformations +~~~~~~~~~~~~~~~ +Transformations are inspired by the cool library instar_ for Clojure. They let you evolve PMaps and PVectors +with arbitrarily deep/complex nesting using simple syntax and flexible matching syntax. + +The first argument to transformation is the path that points out the value to transform. The +second is the transformation to perform. If the transformation is callable it will be applied +to the value(s) matching the path. The path may also contain callables. In that case they are +treated as matchers. If the matcher returns True for a specific key it is considered for transformation. + +.. code:: python + + # Basic examples + >>> from pyrsistent import inc, freeze, thaw, rex, ny, discard + >>> v1 = freeze([1, 2, 3, 4, 5]) + >>> v1.transform([2], inc) + pvector([1, 2, 4, 4, 5]) + >>> v1.transform([lambda ix: 0 < ix < 4], 8) + pvector([1, 8, 8, 8, 5]) + >>> v1.transform([lambda ix, v: ix == 0 or v == 5], 0) + pvector([0, 2, 3, 4, 0]) + + # The (a)ny matcher can be used to match anything + >>> v1.transform([ny], 8) + pvector([8, 8, 8, 8, 8]) + + # Regular expressions can be used for matching + >>> scores = freeze({'John': 12, 'Joseph': 34, 'Sara': 23}) + >>> scores.transform([rex('^Jo')], 0) + pmap({'Joseph': 0, 'Sara': 23, 'John': 0}) + + # Transformations can be done on arbitrarily deep structures + >>> news_paper = freeze({'articles': [{'author': 'Sara', 'content': 'A short article'}, + ... {'author': 'Steve', 'content': 'A slightly longer article'}], + ... 'weather': {'temperature': '11C', 'wind': '5m/s'}}) + >>> short_news = news_paper.transform(['articles', ny, 'content'], lambda c: c[:25] + '...' if len(c) > 25 else c) + >>> very_short_news = news_paper.transform(['articles', ny, 'content'], lambda c: c[:15] + '...' if len(c) > 15 else c) + >>> very_short_news.articles[0].content + 'A short article' + >>> very_short_news.articles[1].content + 'A slightly long...' + + # When nothing has been transformed the original data structure is kept + >>> short_news is news_paper + True + >>> very_short_news is news_paper + False + >>> very_short_news.articles[0] is news_paper.articles[0] + True + + # There is a special transformation that can be used to discard elements. Also + # multiple transformations can be applied in one call + >>> thaw(news_paper.transform(['weather'], discard, ['articles', ny, 'content'], discard)) + {'articles': [{'author': 'Sara'}, {'author': 'Steve'}]} + +Evolvers +~~~~~~~~ +PVector, PMap and PSet all have support for a concept dubbed *evolvers*. An evolver acts like a mutable +view of the underlying persistent data structure with "transaction like" semantics. No updates of the original +data structure is ever performed, it is still fully immutable. + +The evolvers have a very limited API by design to discourage excessive, and inappropriate, usage as that would +take us down the mutable road. In principle only basic mutation and element access functions are supported. +Check out the documentation_ of each data structure for specific examples. + +Examples of when you may want to use an evolver instead of working directly with the data structure include: + +* Multiple updates are done to the same data structure and the intermediate results are of no + interest. In this case using an evolver may be a more efficient and easier to work with. +* You need to pass a vector into a legacy function or a function that you have no control + over which performs in place mutations. In this case pass an evolver instance + instead and then create a new pvector from the evolver once the function returns. + +.. code:: python + + >>> from pyrsistent import v + + # In place mutation as when working with the built in counterpart + >>> v1 = v(1, 2, 3) + >>> e = v1.evolver() + >>> e[1] = 22 + >>> e = e.append(4) + >>> e = e.extend([5, 6]) + >>> e[5] += 1 + >>> len(e) + 6 + + # The evolver is considered *dirty* when it contains changes compared to the underlying vector + >>> e.is_dirty() + True + + # But the underlying pvector still remains untouched + >>> v1 + pvector([1, 2, 3]) + + # Once satisfied with the updates you can produce a new pvector containing the updates. + # The new pvector will share data with the original pvector in the same way that would have + # been done if only using operations on the pvector. + >>> v2 = e.persistent() + >>> v2 + pvector([1, 22, 3, 4, 5, 7]) + + # The evolver is now no longer considered *dirty* as it contains no differences compared to the + # pvector just produced. + >>> e.is_dirty() + False + + # You may continue to work with the same evolver without affecting the content of v2 + >>> e[0] = 11 + + # Or create a new evolver from v2. The two evolvers can be updated independently but will both + # share data with v2 where possible. + >>> e2 = v2.evolver() + >>> e2[0] = 1111 + >>> e.persistent() + pvector([11, 22, 3, 4, 5, 7]) + >>> e2.persistent() + pvector([1111, 22, 3, 4, 5, 7]) + +.. _freeze: +.. _thaw: + +freeze and thaw +~~~~~~~~~~~~~~~ +These functions are great when your cozy immutable world has to interact with the evil mutable world outside. + +.. code:: python + + >>> from pyrsistent import freeze, thaw, v, m + >>> freeze([1, {'a': 3}]) + pvector([1, pmap({'a': 3})]) + >>> thaw(v(1, m(a=3))) + [1, {'a': 3}] + +Compatibility +------------- + +Pyrsistent is developed and tested on Python 2.7, 3.5, 3.6, 3.7 and PyPy (Python 2 and 3 compatible). It will most +likely work on all other versions >= 3.4 but no guarantees are given. :) + +Compatibility issues +~~~~~~~~~~~~~~~~~~~~ + +.. _27: https://github.com/tobgu/pyrsistent/issues/27 + +There is currently one known compatibility issue when comparing built in sets and frozensets to PSets as discussed in 27_. +It affects python 2 versions < 2.7.8 and python 3 versions < 3.4.0 and is due to a bug described in +http://bugs.python.org/issue8743. + +Comparisons will fail or be incorrect when using the set/frozenset as left hand side of the comparison. As a workaround +you need to either upgrade Python to a more recent version, avoid comparing sets/frozensets with PSets or always make +sure to convert both sides of the comparison to the same type before performing the comparison. + +Performance +----------- + +Pyrsistent is developed with performance in mind. Still, while some operations are nearly on par with their built in, +mutable, counterparts in terms of speed, other operations are slower. In the cases where attempts at +optimizations have been done, speed has generally been valued over space. + +Pyrsistent comes with two API compatible flavors of PVector (on which PMap and PSet are based), one pure Python +implementation and one implemented as a C extension. The latter generally being 2 - 20 times faster than the former. +The C extension will be used automatically when possible. + +The pure python implementation is fully PyPy compatible. Running it under PyPy speeds operations up considerably if +the structures are used heavily (if JITed), for some cases the performance is almost on par with the built in counterparts. + +Type hints +---------- + +PEP 561 style type hints for use with mypy and various editors are available for most types and functions in pyrsistent. + +Type classes for annotating your own code with pyrsistent types are also available under pyrsistent.typing. + +Installation +------------ + +pip install pyrsistent + +Documentation +------------- + +Available at http://pyrsistent.readthedocs.org/ + +Brief presentation available at http://slides.com/tobiasgustafsson/immutability-and-python/ + +Contributors +------------ + +Tobias Gustafsson https://github.com/tobgu + +Christopher Armstrong https://github.com/radix + +Anders Hovmöller https://github.com/boxed + +Itamar Turner-Trauring https://github.com/itamarst + +Jonathan Lange https://github.com/jml + +Richard Futrell https://github.com/Futrell + +Jakob Hollenstein https://github.com/jkbjh + +David Honour https://github.com/foolswood + +David R. MacIver https://github.com/DRMacIver + +Marcus Ewert https://github.com/sarum90 + +Jean-Paul Calderone https://github.com/exarkun + +Douglas Treadwell https://github.com/douglas-treadwell + +Travis Parker https://github.com/teepark + +Julian Berman https://github.com/Julian + +Dennis Tomas https://github.com/dtomas + +Neil Vyas https://github.com/neilvyas + +doozr https://github.com/doozr + +Kamil Galuszka https://github.com/galuszkak + +Tsuyoshi Hombashi https://github.com/thombashi + +nattofriends https://github.com/nattofriends + +agberk https://github.com/agberk + +Waleed Khan https://github.com/arxanas + +Jean-Louis Fuchs https://github.com/ganwell + +Carlos Corbacho https://github.com/ccorbacho + +Felix Yan https://github.com/felixonmars + +benrg https://github.com/benrg + +Jere Lahelma https://github.com/je-l + +Max Taggart https://github.com/MaxTaggart + +Vincent Philippon https://github.com/vphilippon + +Semen Zhydenko https://github.com/ss18 + +Till Varoquaux https://github.com/till-varoquaux + +Michal Kowalik https://github.com/michalvi + +ossdev07 https://github.com/ossdev07 + +Kerry Olesen https://github.com/qhesz + +johnthagen https://github.com/johnthagen + +Contributing +------------ + +Want to contribute? That's great! If you experience problems please log them on GitHub. If you want to contribute code, +please fork the repository and submit a pull request. + +Run tests +~~~~~~~~~ +.. _tox: https://tox.readthedocs.io/en/latest/ + +Tests can be executed using tox_. + +Install tox: ``pip install tox`` + +Run test for Python 2.7: ``tox -epy27`` + +Release +~~~~~~~ +* Update CHANGES.txt +* Update README with any new contributors and potential info needed. +* Update _pyrsistent_version.py +* python setup.py sdist upload +* Commit and tag with new version: git add -u . && git commit -m 'Prepare version vX.Y.Z' && git tag -a vX.Y.Z -m 'vX.Y.Z' +* Push commit and tags: git push && git push --tags + +Project status +-------------- +Pyrsistent can be considered stable and mature (who knows, there may even be a 1.0 some day :-)). The project is +maintained, bugs fixed, PRs reviewed and merged and new releases made. I currently do not have time for development +of new features or functionality which I don't have use for myself. I'm more than happy to take PRs for new +functionality though! + +There are a bunch of issues marked with ``enhancement`` and ``help wanted`` that contain requests for new functionality +that would be nice to include. The level of difficulty and extend of the issues varies, please reach out to me if you're +interested in working on any of them. + +If you feel that you have a grand master plan for where you would like Pyrsistent to go and have the time to put into +it please don't hesitate to discuss this with me and submit PRs for it. If all goes well I'd be more than happy to add +additional maintainers to the project! diff --git a/third_party/python/pyrsistent/_pyrsistent_version.py b/third_party/python/pyrsistent/_pyrsistent_version.py new file mode 100644 index 0000000000..8911e95ca7 --- /dev/null +++ b/third_party/python/pyrsistent/_pyrsistent_version.py @@ -0,0 +1 @@ +__version__ = '0.16.0' diff --git a/third_party/python/pyrsistent/pvectorcmodule.c b/third_party/python/pyrsistent/pvectorcmodule.c new file mode 100644 index 0000000000..11a5bd6411 --- /dev/null +++ b/third_party/python/pyrsistent/pvectorcmodule.c @@ -0,0 +1,1642 @@ +#include <Python.h> +#include <structmember.h> + +/* +Persistent/Immutable/Functional vector and helper types. + +Please note that they are anything but immutable at this level since +there is a whole lot of reference counting going on. That's the way +CPython works though and the GIL makes them appear immutable. + +To the programmer using them from Python they appear immutable and +behave immutably at least. + +Naming conventions +------------------ +initpyrsistentc - This is the method that initializes the whole module +pyrsistent_* - Methods part of the interface +<typename>_* - Instance methods of types. For examle PVector_append(...) + +All other methods are camel cased without prefix. All methods are static, none should +require to be exposed outside of this module. +*/ + +#define SHIFT 5 +#define BRANCH_FACTOR (1 << SHIFT) +#define BIT_MASK (BRANCH_FACTOR - 1) + +static PyTypeObject PVectorType; +static PyTypeObject PVectorEvolverType; + +typedef struct { + void *items[BRANCH_FACTOR]; + unsigned int refCount; +} VNode; + +#define NODE_CACHE_MAX_SIZE 1024 + +typedef struct { + unsigned int size; + VNode* nodes[NODE_CACHE_MAX_SIZE]; +} vNodeCache; + +static vNodeCache nodeCache; + +typedef struct { + PyObject_HEAD + unsigned int count; // Perhaps ditch this one in favor of ob_size/Py_SIZE() + unsigned int shift; + VNode *root; + VNode *tail; + PyObject *in_weakreflist; /* List of weak references */ +} PVector; + +typedef struct { + PyObject_HEAD + PVector* originalVector; + PVector* newVector; + PyObject* appendList; +} PVectorEvolver; + + +static PVector* EMPTY_VECTOR = NULL; +static PyObject* transform_fn = NULL; + +static PyObject* transform(PVector* self, PyObject* args) { + if(transform_fn == NULL) { + // transform to avoid circular import problems + transform_fn = PyObject_GetAttrString(PyImport_ImportModule("pyrsistent._transformations"), "transform"); + } + + return PyObject_CallFunctionObjArgs(transform_fn, self, args, NULL); +} + + +// No access to internal members +static PyMemberDef PVector_members[] = { + {NULL} /* Sentinel */ +}; + +#define debug(...) +// #define debug printf + +#define NODE_REF_COUNT(n) ((n)->refCount) +#define SET_NODE_REF_COUNT(n, c) (NODE_REF_COUNT(n) = (c)) +#define INC_NODE_REF_COUNT(n) (NODE_REF_COUNT(n)++) +#define DEC_NODE_REF_COUNT(n) (NODE_REF_COUNT(n)--) + +static VNode* allocNode(void) { + if(nodeCache.size > 0) { + nodeCache.size--; + return nodeCache.nodes[nodeCache.size]; + } + + return PyMem_Malloc(sizeof(VNode)); +} + +static void freeNode(VNode *node) { + if(nodeCache.size < NODE_CACHE_MAX_SIZE) { + nodeCache.nodes[nodeCache.size] = node; + nodeCache.size++; + } else { + PyMem_Free(node); + } +} + +static VNode* newNode(void) { + VNode* result = allocNode(); + memset(result, 0x0, sizeof(VNode)); + SET_NODE_REF_COUNT(result, 1); + debug("newNode() %p\n", result); + return result; +} + +static VNode* copyNode(VNode* source) { + /* NB: Only to be used for internal nodes, eg. nodes that do not + hold direct references to python objects but only to other nodes. */ + int i; + VNode* result = allocNode(); + debug("copyNode() %p\n", result); + memcpy(result->items, source->items, sizeof(source->items)); + + for(i = 0; i < BRANCH_FACTOR; i++) { + // TODO-OPT: Any need to go on when the first NULL has been found? + if(result->items[i] != NULL) { + INC_NODE_REF_COUNT((VNode*)result->items[i]); + } + } + + SET_NODE_REF_COUNT(result, 1); + return result; +} + +static PVector* emptyNewPvec(void); +static PVector* copyPVector(PVector *original); +static void extendWithItem(PVector *newVec, PyObject *item); + +static PyObject *PVectorEvolver_persistent(PVectorEvolver *); +static int PVectorEvolver_set_item(PVectorEvolver *, PyObject*, PyObject*); + +static Py_ssize_t PVector_len(PVector *self) { + return self->count; +} + +/* Convenience macros */ +#define ROOT_NODE_FULL(vec) ((vec->count >> SHIFT) > (1 << vec->shift)) +#define TAIL_OFF(vec) ((vec->count < BRANCH_FACTOR) ? 0 : (((vec->count - 1) >> SHIFT) << SHIFT)) +#define TAIL_SIZE(vec) (vec->count - TAIL_OFF(vec)) +#define PVector_CheckExact(op) (Py_TYPE(op) == &PVectorType) + +static VNode* nodeFor(PVector *self, int i){ + int level; + if((i >= 0) && (i < self->count)) { + if(i >= TAIL_OFF(self)) { + return self->tail; + } + + VNode* node = self->root; + for(level = self->shift; level > 0; level -= SHIFT) { + node = (VNode*) node->items[(i >> level) & BIT_MASK]; + } + + return node; + } + + PyErr_Format(PyExc_IndexError, "Index out of range: %i", i); + return NULL; +} + +static PyObject* _get_item(PVector *self, Py_ssize_t pos) { + VNode* node = nodeFor((PVector*)self, pos); + PyObject *result = NULL; + if(node != NULL) { + result = node->items[pos & BIT_MASK]; + } + return result; +} + +/* + Returns a new reference as specified by the PySequence_GetItem function. +*/ +static PyObject* PVector_get_item(PVector *self, Py_ssize_t pos) { + if (pos < 0) { + pos += self->count; + } + + PyObject* obj = _get_item(self, pos); + Py_XINCREF(obj); + return obj; +} + +static void releaseNode(int level, VNode *node) { + if(node == NULL) { + return; + } + + debug("releaseNode(): node=%p, level=%i, refCount=%i\n", node, level, NODE_REF_COUNT(node)); + + int i; + + DEC_NODE_REF_COUNT(node); + debug("Refcount when trying to release: %u\n", NODE_REF_COUNT(node)); + if(NODE_REF_COUNT(node) == 0) { + if(level > 0) { + for(i = 0; i < BRANCH_FACTOR; i++) { + if(node->items[i] != NULL) { + releaseNode(level - SHIFT, node->items[i]); + } + } + freeNode(node); + } else { + for(i = 0; i < BRANCH_FACTOR; i++) { + Py_XDECREF(node->items[i]); + } + freeNode(node); + } + } + + debug("releaseNode(): Done! node=%p!\n", node); +} + +/* + Returns all references to PyObjects that have been stolen. Also decrements + the internal reference counts used for shared memory structures and deallocates + those if needed. +*/ +static void PVector_dealloc(PVector *self) { + debug("Dealloc(): self=%p, self->count=%u, tail->refCount=%u, root->refCount=%u, self->shift=%u, self->tail=%p, self->root=%p\n", + self, self->count, NODE_REF_COUNT(self->tail), NODE_REF_COUNT(self->root), self->shift, self->tail, self->root); + + if (self->in_weakreflist != NULL) { + PyObject_ClearWeakRefs((PyObject *) self); + } + + PyObject_GC_UnTrack((PyObject*)self); + Py_TRASHCAN_SAFE_BEGIN(self); + + releaseNode(0, self->tail); + releaseNode(self->shift, self->root); + + PyObject_GC_Del(self); + Py_TRASHCAN_SAFE_END(self); +} + +static PyObject *PVector_toList(PVector *self) { + Py_ssize_t i; + PyObject *list = PyList_New(self->count); + for (i = 0; i < self->count; ++i) { + PyObject *o = _get_item(self, i); + Py_INCREF(o); + PyList_SET_ITEM(list, i, o); + } + + return list; +} + + +static PyObject *PVector_repr(PVector *self) { + // Reuse the list repr code, a bit less efficient but saves some code + PyObject *list = PVector_toList(self); + PyObject *list_repr = PyObject_Repr(list); + Py_DECREF(list); + + if(list_repr == NULL) { + // Exception raised during call to repr + return NULL; + } + + // Repr for list implemented differently in python 2 and 3. Need to + // handle this or core dump will occur. +#if PY_MAJOR_VERSION >= 3 + PyObject *s = PyUnicode_FromFormat("%s%U%s", "pvector(", list_repr, ")"); + Py_DECREF(list_repr); +#else + PyObject *s = PyString_FromString("pvector("); + PyString_ConcatAndDel(&s, list_repr); + PyString_ConcatAndDel(&s, PyString_FromString(")")); +#endif + + return s; +} + + +static long PVector_hash(PVector *self) { + // Follows the pattern of the tuple hash + long x, y; + Py_ssize_t i; + long mult = 1000003L; + x = 0x456789L; + for(i=0; i<self->count; i++) { + y = PyObject_Hash(_get_item(self, i)); + if (y == -1) { + return -1; + } + x = (x ^ y) * mult; + mult += (long)(82520L + i + i); + } + + x += 97531L; + if(x == -1) { + x = -2; + } + + return x; +} + +static PyObject* compareSizes(long vlen, long wlen, int op) { + int cmp; + PyObject *res; + switch (op) { + case Py_LT: cmp = vlen < wlen; break; + case Py_LE: cmp = vlen <= wlen; break; + case Py_EQ: cmp = vlen == wlen; break; + case Py_NE: cmp = vlen != wlen; break; + case Py_GT: cmp = vlen > wlen; break; + case Py_GE: cmp = vlen >= wlen; break; + default: return NULL; /* cannot happen */ + } + + if (cmp) { + res = Py_True; + } else { + res = Py_False; + } + + Py_INCREF(res); + return res; +} + +static PyObject* PVector_richcompare(PyObject *v, PyObject *w, int op) { + // Follows the principles of the tuple comparison + PVector *vt, *wt; + Py_ssize_t i; + Py_ssize_t vlen, wlen; + PyObject *list; + PyObject *result; + + if(!PVector_CheckExact(v) || !PVector_CheckExact(w)) { + if(PVector_CheckExact(v)) { + list = PVector_toList((PVector*)v); + result = PyObject_RichCompare(list , w, op); + Py_DECREF(list); + return result; + } + + if(PVector_CheckExact(w)) { + list = PVector_toList((PVector*)w); + result = PyObject_RichCompare(v, list, op); + Py_DECREF(list); + return result; + } + + Py_INCREF(Py_NotImplemented); + return Py_NotImplemented; + } + + if((op == Py_EQ) && (v == w)) { + Py_INCREF(Py_True); + return Py_True; + } + + vt = (PVector *)v; + wt = (PVector *)w; + + vlen = vt->count; + wlen = wt->count; + + if (vlen != wlen) { + if (op == Py_EQ) { + Py_INCREF(Py_False); + return Py_False; + } else if (op == Py_NE) { + Py_INCREF(Py_True); + return Py_True; + } + } + + /* Search for the first index where items are different. */ + PyObject *left = NULL; + PyObject *right = NULL; + for (i = 0; i < vlen && i < wlen; i++) { + left = _get_item(vt, i); + right = _get_item(wt, i); + int k = PyObject_RichCompareBool(left, right, Py_EQ); + if (k < 0) { + return NULL; + } + if (!k) { + break; + } + } + + if (i >= vlen || i >= wlen) { + /* No more items to compare -- compare sizes */ + return compareSizes(vlen, wlen, op); + } + + /* We have an item that differs -- shortcuts for EQ/NE */ + if (op == Py_EQ) { + Py_INCREF(Py_False); + return Py_False; + } else if (op == Py_NE) { + Py_INCREF(Py_True); + return Py_True; + } else { + /* Compare the final item again using the proper operator */ + return PyObject_RichCompare(left, right, op); + } +} + + +static PyObject* PVector_repeat(PVector *self, Py_ssize_t n) { + if (n < 0) { + n = 0; + } + + if ((n == 0) || (self->count == 0)) { + Py_INCREF(EMPTY_VECTOR); + return (PyObject *)EMPTY_VECTOR; + } else if (n == 1) { + Py_INCREF(self); + return (PyObject *)self; + } else if ((self->count * n)/self->count != n) { + return PyErr_NoMemory(); + } else { + int i, j; + PVector *newVec = copyPVector(self); + for(i=0; i<(n-1); i++) { + for(j=0; j<self->count; j++) { + extendWithItem(newVec, PVector_get_item(self, j)); + } + } + return (PyObject*)newVec; + } +} + +static int PVector_traverse(PVector *o, visitproc visit, void *arg) { + // Naive traverse + Py_ssize_t i; + for (i = o->count; --i >= 0; ) { + Py_VISIT(_get_item(o, i)); + } + + return 0; +} + + +static PyObject* PVector_index(PVector *self, PyObject *args) { + // A direct rip-off of the tuple version + Py_ssize_t i, start=0, stop=self->count; + PyObject *value; + + if (!PyArg_ParseTuple(args, "O|O&O&:index", &value, + _PyEval_SliceIndex, &start, + _PyEval_SliceIndex, &stop)) { + return NULL; + } + + if (start < 0) { + start += self->count; + if (start < 0) { + start = 0; + } + } + + if (stop < 0) { + stop += self->count; + if (stop < 0) { + stop = 0; + } + } + + for (i = start; i < stop && i < self->count; i++) { + int cmp = PyObject_RichCompareBool(_get_item(self, i), value, Py_EQ); + if (cmp > 0) { +#if PY_MAJOR_VERSION >= 3 + return PyLong_FromSsize_t(i); +#else + return PyInt_FromSsize_t(i); +#endif + } else if (cmp < 0) { + return NULL; + } + } + + PyErr_SetString(PyExc_ValueError, "PVector.index(x): x not in vector"); + return NULL; +} + +static PyObject* PVector_count(PVector *self, PyObject *value) { + Py_ssize_t count = 0; + Py_ssize_t i; + + for (i = 0; i < self->count; i++) { + int cmp = PyObject_RichCompareBool(_get_item(self, i), value, Py_EQ); + if (cmp > 0) { + count++; + } else if (cmp < 0) { + return NULL; + } + } + +#if PY_MAJOR_VERSION >= 3 + return PyLong_FromSsize_t(count); +#else + return PyInt_FromSsize_t(count); +#endif +} + +static PyObject* PVector_pickle_reduce(PVector *self) { + + PyObject* module = PyImport_ImportModule("pvectorc"); + PyObject* pvector_fn = PyObject_GetAttrString(module, "pvector"); + Py_DECREF(module); + + PyObject *list = PVector_toList(self); + PyObject *arg_tuple = PyTuple_New(1); + PyTuple_SET_ITEM(arg_tuple, 0, list); + + PyObject *result_tuple = PyTuple_New(2); + PyTuple_SET_ITEM(result_tuple, 0, pvector_fn); + PyTuple_SET_ITEM(result_tuple, 1, arg_tuple); + + return result_tuple; +} + +static PVector* rawCopyPVector(PVector* vector) { + PVector* newVector = PyObject_GC_New(PVector, &PVectorType); + newVector->count = vector->count; + newVector->shift = vector->shift; + newVector->root = vector->root; + newVector->tail = vector->tail; + newVector->in_weakreflist = NULL; + PyObject_GC_Track((PyObject*)newVector); + return newVector; +} + +static void initializeEvolver(PVectorEvolver* evolver, PVector* vector, PyObject* appendList) { + // Need to hold a reference to the underlying vector to manage + // the ref counting properly. + evolver->originalVector = vector; + evolver->newVector = vector; + + if(appendList == NULL) { + evolver->appendList = PyList_New(0); + } else { + evolver->appendList = appendList; + } +} + +static PyObject * PVector_evolver(PVector *self) { + PVectorEvolver *evolver = PyObject_GC_New(PVectorEvolver, &PVectorEvolverType); + if (evolver == NULL) { + return NULL; + } + initializeEvolver(evolver, self, NULL); + PyObject_GC_Track(evolver); + Py_INCREF(self); + return (PyObject *)evolver; +} + + +static void copyInsert(void** dest, void** src, Py_ssize_t pos, void *obj) { + memcpy(dest, src, BRANCH_FACTOR * sizeof(void*)); + dest[pos] = obj; +} + +static PyObject* PVector_append(PVector *self, PyObject *obj); + +static PyObject* PVector_transform(PVector *self, PyObject *obj); + +static PyObject* PVector_set(PVector *self, PyObject *obj); + +static PyObject* PVector_mset(PVector *self, PyObject *args); + +static PyObject* PVector_subscript(PVector* self, PyObject* item); + +static PyObject* PVector_extend(PVector *self, PyObject *args); + +static PyObject* PVector_delete(PVector *self, PyObject *args); + +static PyObject* PVector_remove(PVector *self, PyObject *args); + +static PySequenceMethods PVector_sequence_methods = { + (lenfunc)PVector_len, /* sq_length */ + (binaryfunc)PVector_extend, /* sq_concat */ + (ssizeargfunc)PVector_repeat, /* sq_repeat */ + (ssizeargfunc)PVector_get_item, /* sq_item */ + // TODO might want to move the slice function to here + NULL, /* sq_slice */ + NULL, /* sq_ass_item */ + NULL, /* sq_ass_slice */ + NULL, /* sq_contains */ + NULL, /* sq_inplace_concat */ + NULL, /* sq_inplace_repeat */ +}; + +static PyMappingMethods PVector_mapping_methods = { + (lenfunc)PVector_len, + (binaryfunc)PVector_subscript, + NULL +}; + + +static PyMethodDef PVector_methods[] = { + {"append", (PyCFunction)PVector_append, METH_O, "Appends an element"}, + {"set", (PyCFunction)PVector_set, METH_VARARGS, "Inserts an element at the specified position"}, + {"extend", (PyCFunction)PVector_extend, METH_O|METH_COEXIST, "Extend"}, + {"transform", (PyCFunction)PVector_transform, METH_VARARGS, "Apply one or more transformations"}, + {"index", (PyCFunction)PVector_index, METH_VARARGS, "Return first index of value"}, + {"count", (PyCFunction)PVector_count, METH_O, "Return number of occurrences of value"}, + {"__reduce__", (PyCFunction)PVector_pickle_reduce, METH_NOARGS, "Pickle support method"}, + {"evolver", (PyCFunction)PVector_evolver, METH_NOARGS, "Return new evolver for pvector"}, + {"mset", (PyCFunction)PVector_mset, METH_VARARGS, "Inserts multiple elements at the specified positions"}, + {"tolist", (PyCFunction)PVector_toList, METH_NOARGS, "Convert to list"}, + {"delete", (PyCFunction)PVector_delete, METH_VARARGS, "Delete element(s) by index"}, + {"remove", (PyCFunction)PVector_remove, METH_VARARGS, "Remove element(s) by equality"}, + {NULL} +}; + +static PyObject * PVectorIter_iter(PyObject *seq); + +static PyTypeObject PVectorType = { + PyVarObject_HEAD_INIT(NULL, 0) + "pvectorc.PVector", /* tp_name */ + sizeof(PVector), /* tp_basicsize */ + 0, /* tp_itemsize */ + (destructor)PVector_dealloc, /* tp_dealloc */ + 0, /* tp_print */ + 0, /* tp_getattr */ + 0, /* tp_setattr */ + 0, /* tp_compare */ + (reprfunc)PVector_repr, /* tp_repr */ + 0, /* tp_as_number */ + &PVector_sequence_methods, /* tp_as_sequence */ + &PVector_mapping_methods, /* tp_as_mapping */ + (hashfunc)PVector_hash, /* tp_hash */ + 0, /* tp_call */ + 0, /* tp_str */ + 0, /* tp_getattro */ + 0, /* tp_setattro */ + 0, /* tp_as_buffer */ + Py_TPFLAGS_DEFAULT | Py_TPFLAGS_HAVE_GC, /* tp_flags */ + "Persistent vector", /* tp_doc */ + (traverseproc)PVector_traverse, /* tp_traverse */ + 0, /* tp_clear */ + PVector_richcompare, /* tp_richcompare */ + offsetof(PVector, in_weakreflist), /* tp_weaklistoffset */ + PVectorIter_iter, /* tp_iter */ + 0, /* tp_iternext */ + PVector_methods, /* tp_methods */ + PVector_members, /* tp_members */ + 0, /* tp_getset */ + 0, /* tp_base */ + 0, /* tp_dict */ + 0, /* tp_descr_get */ + 0, /* tp_descr_set */ + 0, /* tp_dictoffset */ +}; + +static PyObject* pyrsistent_pvec(PyObject *self, PyObject *args) { + debug("pyrsistent_pvec(): %x\n", args); + + PyObject *argObj = NULL; /* list of arguments */ + + if(!PyArg_ParseTuple(args, "|O", &argObj)) { + return NULL; + } + + if(argObj == NULL) { + Py_INCREF(EMPTY_VECTOR); + return (PyObject*)EMPTY_VECTOR; + } + + return PVector_extend(EMPTY_VECTOR, argObj); +} + +static PVector* emptyNewPvec(void) { + PVector *pvec = PyObject_GC_New(PVector, &PVectorType); + debug("pymem alloc_new %x, ref cnt: %u\n", pvec, pvec->ob_refcnt); + pvec->count = (Py_ssize_t)0; + pvec->shift = SHIFT; + pvec->root = newNode(); + pvec->tail = newNode(); + pvec->in_weakreflist = NULL; + PyObject_GC_Track((PyObject*)pvec); + return pvec; +} + +static void incRefs(PyObject **obj) { + // TODO-OPT: Would it be OK to exit on first NULL? Should not be any + // non NULLs beyond a NULL. + int i; + for(i = 0; i < BRANCH_FACTOR; i++) { + Py_XINCREF(obj[i]); + } +} + + +static PVector* newPvec(unsigned int count, unsigned int shift, VNode *root) { + // TODO-OPT: Introduce object cache + PVector *pvec = PyObject_GC_New(PVector, &PVectorType); + debug("pymem alloc_copy %x, ref cnt: %u\n", pvec, pvec->ob_refcnt); + pvec->count = count; + pvec->shift = shift; + pvec->root = root; + pvec->tail = newNode(); + pvec->in_weakreflist = NULL; + PyObject_GC_Track((PyObject*)pvec); + return pvec; +} + +static VNode* newPath(unsigned int level, VNode* node){ + if(level == 0) { + INC_NODE_REF_COUNT(node); + return node; + } + + VNode* result = newNode(); + result->items[0] = newPath(level - SHIFT, node); + return result; +} + +static VNode* pushTail(unsigned int level, unsigned int count, VNode* parent, VNode* tail) { + int subIndex = ((count - 1) >> level) & BIT_MASK; + VNode* result = copyNode(parent); + VNode* nodeToInsert; + VNode* child; + debug("pushTail(): count = %i, subIndex = %i\n", count, subIndex); + + if(level == SHIFT) { + // We're at the bottom + INC_NODE_REF_COUNT(tail); + nodeToInsert = tail; + } else { + // More levels available in the tree + child = parent->items[subIndex]; + + if(child != NULL) { + nodeToInsert = pushTail(level - SHIFT, count, child, tail); + + // Need to make an adjustment of the ref COUNT for the child node here since + // it was incremented in an earlier stage when the node was copied. Now the child + // node will be part of the path copy so the number of references to the original + // child will not increase at all. + DEC_NODE_REF_COUNT(child); + } else { + nodeToInsert = newPath(level - SHIFT, tail); + } + } + + result->items[subIndex] = nodeToInsert; + return result; +} + +static PVector* copyPVector(PVector *original) { + PVector *newVec = newPvec(original->count, original->shift, original->root); + INC_NODE_REF_COUNT(original->root); + memcpy(newVec->tail->items, original->tail->items, TAIL_SIZE(original) * sizeof(void*)); + incRefs((PyObject**)newVec->tail->items); + return newVec; +} + +/* Does not steal a reference, this must be managed outside of this function */ +static void extendWithItem(PVector *newVec, PyObject *item) { + unsigned int tail_size = TAIL_SIZE(newVec); + + if(tail_size >= BRANCH_FACTOR) { + VNode* new_root; + if(ROOT_NODE_FULL(newVec)) { + new_root = newNode(); + new_root->items[0] = newVec->root; + new_root->items[1] = newPath(newVec->shift, newVec->tail); + newVec->shift += SHIFT; + } else { + new_root = pushTail(newVec->shift, newVec->count, newVec->root, newVec->tail); + releaseNode(newVec->shift, newVec->root); + } + + newVec->root = new_root; + + // Need to adjust the ref count of the old tail here since no new references were + // actually created, we just moved the tail. + DEC_NODE_REF_COUNT(newVec->tail); + newVec->tail = newNode(); + tail_size = 0; + } + + newVec->tail->items[tail_size] = item; + newVec->count++; +} + + +#if PY_MAJOR_VERSION >= 3 +// This was changed in 3.2 but we do not claim compatibility with any older version of python 3. +#define SLICE_CAST +#else +#define SLICE_CAST (PySliceObject *) +#endif + +static PyObject *PVector_subscript(PVector* self, PyObject* item) { + if (PyIndex_Check(item)) { + Py_ssize_t i = PyNumber_AsSsize_t(item, PyExc_IndexError); + if (i == -1 && PyErr_Occurred()) { + return NULL; + } + + return PVector_get_item(self, i); + } else if (PySlice_Check(item)) { + Py_ssize_t start, stop, step, slicelength, cur, i; + if (PySlice_GetIndicesEx(SLICE_CAST item, self->count, + &start, &stop, &step, &slicelength) < 0) { + return NULL; + } + + debug("start=%i, stop=%i, step=%i\n", start, stop, step); + + if (slicelength <= 0) { + Py_INCREF(EMPTY_VECTOR); + return (PyObject*)EMPTY_VECTOR; + } else if((slicelength == self->count) && (step > 0)) { + Py_INCREF(self); + return (PyObject*)self; + } else { + PVector *newVec = copyPVector(EMPTY_VECTOR); + for (cur=start, i=0; i<slicelength; cur += (size_t)step, i++) { + extendWithItem(newVec, PVector_get_item(self, cur)); + } + + return (PyObject*)newVec; + } + } else { + PyErr_Format(PyExc_TypeError, "pvector indices must be integers, not %.200s", Py_TYPE(item)->tp_name); + return NULL; + } +} + +/* A hack to get some of the error handling code away from the function + doing the actual work */ +#define HANDLE_ITERATION_ERROR() \ + if (PyErr_Occurred()) { \ + if (PyErr_ExceptionMatches(PyExc_StopIteration)) { \ + PyErr_Clear(); \ + } else { \ + return NULL; \ + } \ + } + + +/* Returns a new vector that is extended with the iterable b. + Takes a copy of the original vector and performs the extension in place on this + one for efficiency. + + These are some optimizations that could be done to this function, + these are not considered important enough yet though. + - Use the PySequence_Fast ops if the iterable is a list or a tuple (which it + whould probably often be) + - Only copy the original tail if it is not full + - No need to try to increment ref count in tail for the whole tail +*/ +static PyObject* PVector_extend(PVector *self, PyObject *iterable) { + PyObject *it; + PyObject *(*iternext)(PyObject *); + + it = PyObject_GetIter(iterable); + if (it == NULL) { + return NULL; + } + + // TODO-OPT: Use special fast iterator if available + iternext = *Py_TYPE(it)->tp_iternext; + PyObject *item = iternext(it); + if (item == NULL) { + Py_DECREF(it); + HANDLE_ITERATION_ERROR() + Py_INCREF(self); + return (PyObject *)self; + } else { + PVector *newVec = copyPVector(self); + // TODO-OPT test using special case code here for extension to + // avoid recalculating tail length all the time. + while(item != NULL) { + extendWithItem(newVec, item); + item = iternext(it); + } + + Py_DECREF(it); + HANDLE_ITERATION_ERROR() + return (PyObject*)newVec; + } +} + +/* + Steals a reference to the object that is appended to the list. +*/ +static PyObject* PVector_append(PVector *self, PyObject *obj) { + assert (obj != NULL); + + unsigned int tail_size = TAIL_SIZE(self); + debug("append(): count = %u, tail_size = %u\n", self->count, tail_size); + + // Does the new object fit in the tail? If so, take a copy of the tail and + // insert the new element in that. + if(tail_size < BRANCH_FACTOR) { + INC_NODE_REF_COUNT(self->root); + PVector *new_pvec = newPvec(self->count + 1, self->shift, self->root); + // TODO-OPT No need to copy more than the current tail length + // TODO-OPT No need to incRefs for all elements all the time + copyInsert(new_pvec->tail->items, self->tail->items, tail_size, obj); + incRefs((PyObject**)new_pvec->tail->items); + debug("append(): new_pvec=%p, new_pvec->tail=%p, new_pvec->root=%p\n", + new_pvec, new_pvec->tail, new_pvec->root); + + return (PyObject*)new_pvec; + } + + // Tail is full, need to push it into the tree + VNode* new_root; + unsigned int new_shift; + if(ROOT_NODE_FULL(self)) { + new_root = newNode(); + new_root->items[0] = self->root; + INC_NODE_REF_COUNT(self->root); + new_root->items[1] = newPath(self->shift, self->tail); + new_shift = self->shift + SHIFT; + } else { + new_root = pushTail(self->shift, self->count, self->root, self->tail); + new_shift = self->shift; + } + + PVector* pvec = newPvec(self->count + 1, new_shift, new_root); + pvec->tail->items[0] = obj; + Py_XINCREF(obj); + debug("append_push(): pvec=%p, pvec->tail=%p, pvec->root=%p\n", pvec, pvec->tail, pvec->root); + return (PyObject*)pvec; +} + +static VNode* doSet(VNode* node, unsigned int level, unsigned int position, PyObject* value) { + debug("doSet(): level == %i\n", level); + if(level == 0) { + // TODO-OPT: Perhaps an alloc followed by a reset of reference + // count is enough here since we overwrite all subnodes below. + VNode* theNewNode = newNode(); + copyInsert(theNewNode->items, node->items, position & BIT_MASK, value); + incRefs((PyObject**)theNewNode->items); + return theNewNode; + } else { + VNode* theNewNode = copyNode(node); + Py_ssize_t index = (position >> level) & BIT_MASK; + + // Drop reference to this node since we're about to replace it + DEC_NODE_REF_COUNT((VNode*)theNewNode->items[index]); + theNewNode->items[index] = doSet(node->items[index], level - SHIFT, position, value); + return theNewNode; + } +} + + +static PyObject* internalSet(PVector *self, Py_ssize_t position, PyObject *argObj) { + if(position < 0) { + position += self->count; + } + + if((0 <= position) && (position < self->count)) { + if(position >= TAIL_OFF(self)) { + // Reuse the root, replace the tail + INC_NODE_REF_COUNT(self->root); + PVector *new_pvec = newPvec(self->count, self->shift, self->root); + copyInsert(new_pvec->tail->items, self->tail->items, position & BIT_MASK, argObj); + incRefs((PyObject**)new_pvec->tail->items); + return (PyObject*)new_pvec; + } else { + // Keep the tail, replace the root + VNode *newRoot = doSet(self->root, self->shift, position, argObj); + PVector *new_pvec = newPvec(self->count, self->shift, newRoot); + + // Free the tail and replace it with a reference to the tail of the original vector + freeNode(new_pvec->tail); + new_pvec->tail = self->tail; + INC_NODE_REF_COUNT(self->tail); + return (PyObject*)new_pvec; + } + } else if (position == self->count) { + // TODO Remove this case? + return PVector_append(self, argObj); + } else { + PyErr_Format(PyExc_IndexError, "Index out of range: %zd", position); + return NULL; + } +} + +static PyObject* PVector_transform(PVector *self, PyObject *obj) { + return transform(self, obj); +} + +/* + Steals a reference to the object that is inserted in the vector. +*/ +static PyObject* PVector_set(PVector *self, PyObject *args) { + PyObject *argObj = NULL; /* argument to insert */ + Py_ssize_t position; + + /* The n parses for size, the O parses for a Python object */ + if(!PyArg_ParseTuple(args, "nO", &position, &argObj)) { + return NULL; + } + + return internalSet(self, position, argObj); +} + + +static PyObject* PVector_mset(PVector *self, PyObject *args) { + Py_ssize_t size = PyTuple_Size(args); + if(size % 2) { + PyErr_SetString(PyExc_TypeError, "mset expected an even number of arguments"); + return NULL; + } + + PVectorEvolver* evolver = (PVectorEvolver*)PVector_evolver(self); + Py_ssize_t i; + for(i=0; i<size; i+=2) { + if(PVectorEvolver_set_item(evolver, PyTuple_GetItem(args, i), PyTuple_GetItem(args, i + 1)) < 0) { + Py_DECREF(evolver); + return NULL; + } + } + + PyObject* vector = PVectorEvolver_persistent(evolver); + Py_DECREF(evolver); + return vector; +} + + +static PyObject* internalDelete(PVector *self, Py_ssize_t index, PyObject *stop_obj) { + Py_ssize_t stop; + PyObject *list; + PyObject *result; + + if (index < 0) { + index += self->count; + } + + if (stop_obj != NULL) { + if (PyIndex_Check(stop_obj)) { + stop = PyNumber_AsSsize_t(stop_obj, PyExc_IndexError); + if (stop == -1 && PyErr_Occurred()) { + return NULL; + } + } else { + PyErr_Format(PyExc_TypeError, "Stop index must be integer, not %.200s", Py_TYPE(stop_obj)->tp_name); + return NULL; + } + + if (stop < 0) { + stop += self->count; + } + } else { + if (index < 0 || index >= self->count) { + PyErr_SetString(PyExc_IndexError, "delete index out of range"); + return NULL; + } + + stop = index + 1; + } + + list = PVector_toList(self); + if(PyList_SetSlice(list, index, stop, NULL) < 0) { + return NULL; + } + + result = PVector_extend(EMPTY_VECTOR, list); + Py_DECREF(list); + return result; +} + +static PyObject* PVector_delete(PVector *self, PyObject *args) { + Py_ssize_t index; + PyObject *stop_obj = NULL; + + if(!PyArg_ParseTuple(args, "n|O:delete", &index, &stop_obj)) { + return NULL; + } + + return internalDelete(self, index, stop_obj); +} + +static PyObject* PVector_remove(PVector *self, PyObject *args) { + Py_ssize_t index; + PyObject* py_index = PVector_index(self, args); + + if(py_index != NULL) { +#if PY_MAJOR_VERSION >= 3 + index = PyLong_AsSsize_t(py_index); +#else + index = PyInt_AsSsize_t(py_index); +#endif + Py_DECREF(py_index); + return internalDelete(self, index, NULL); + } + + PyErr_SetString(PyExc_ValueError, "PVector.remove(x): x not in vector"); + return NULL; +} + + +/*********************** PVector Iterator **************************/ + +/* +The Sequence class provides us with a default iterator but the runtime +overhead of using that compared to the iterator below is huge. +*/ + +typedef struct { + PyObject_HEAD + Py_ssize_t it_index; + PVector *it_seq; /* Set to NULL when iterator is exhausted */ +} PVectorIter; + +static void PVectorIter_dealloc(PVectorIter *); +static int PVectorIter_traverse(PVectorIter *, visitproc, void *); +static PyObject *PVectorIter_next(PVectorIter *); + +static PyMethodDef PVectorIter_methods[] = { + {NULL, NULL} /* sentinel */ +}; + +static PyTypeObject PVectorIterType = { + PyVarObject_HEAD_INIT(NULL, 0) + "pvector_iterator", /* tp_name */ + sizeof(PVectorIter), /* tp_basicsize */ + 0, /* tp_itemsize */ + /* methods */ + (destructor)PVectorIter_dealloc, /* tp_dealloc */ + 0, /* tp_print */ + 0, /* tp_getattr */ + 0, /* tp_setattr */ + 0, /* tp_compare */ + 0, /* tp_repr */ + 0, /* tp_as_number */ + 0, /* tp_as_sequence */ + 0, /* tp_as_mapping */ + 0, /* tp_hash */ + 0, /* tp_call */ + 0, /* tp_str */ + PyObject_GenericGetAttr, /* tp_getattro */ + 0, /* tp_setattro */ + 0, /* tp_as_buffer */ + Py_TPFLAGS_DEFAULT | Py_TPFLAGS_HAVE_GC, /* tp_flags */ + 0, /* tp_doc */ + (traverseproc)PVectorIter_traverse, /* tp_traverse */ + 0, /* tp_clear */ + 0, /* tp_richcompare */ + 0, /* tp_weaklistoffset */ + PyObject_SelfIter, /* tp_iter */ + (iternextfunc)PVectorIter_next, /* tp_iternext */ + PVectorIter_methods, /* tp_methods */ + 0, /* tp_members */ +}; + +static PyObject *PVectorIter_iter(PyObject *seq) { + PVectorIter *it = PyObject_GC_New(PVectorIter, &PVectorIterType); + if (it == NULL) { + return NULL; + } + + it->it_index = 0; + Py_INCREF(seq); + it->it_seq = (PVector *)seq; + PyObject_GC_Track(it); + return (PyObject *)it; +} + +static void PVectorIter_dealloc(PVectorIter *it) { + PyObject_GC_UnTrack(it); + Py_XDECREF(it->it_seq); + PyObject_GC_Del(it); +} + +static int PVectorIter_traverse(PVectorIter *it, visitproc visit, void *arg) { + Py_VISIT(it->it_seq); + return 0; +} + +static PyObject *PVectorIter_next(PVectorIter *it) { + assert(it != NULL); + PVector *seq = it->it_seq; + if (seq == NULL) { + return NULL; + } + + if (it->it_index < seq->count) { + PyObject *item = _get_item(seq, it->it_index); + ++it->it_index; + Py_INCREF(item); + return item; + } + + Py_DECREF(seq); + it->it_seq = NULL; + return NULL; +} + + +/*********************** PVector Evolver **************************/ + +/* +Evolver to make multi updates easier to work with and more efficient. +*/ + +static void PVectorEvolver_dealloc(PVectorEvolver *); +static PyObject *PVectorEvolver_append(PVectorEvolver *, PyObject *); +static PyObject *PVectorEvolver_extend(PVectorEvolver *, PyObject *); +static PyObject *PVectorEvolver_set(PVectorEvolver *, PyObject *); +static PyObject *PVectorEvolver_delete(PVectorEvolver *self, PyObject *args); +static PyObject *PVectorEvolver_subscript(PVectorEvolver *, PyObject *); +static PyObject *PVectorEvolver_persistent(PVectorEvolver *); +static Py_ssize_t PVectorEvolver_len(PVectorEvolver *); +static PyObject *PVectorEvolver_is_dirty(PVectorEvolver *); +static int PVectorEvolver_traverse(PVectorEvolver *self, visitproc visit, void *arg); + +static PyMappingMethods PVectorEvolver_mapping_methods = { + (lenfunc)PVectorEvolver_len, + (binaryfunc)PVectorEvolver_subscript, + (objobjargproc)PVectorEvolver_set_item, +}; + + +static PyMethodDef PVectorEvolver_methods[] = { + {"append", (PyCFunction)PVectorEvolver_append, METH_O, "Appends an element"}, + {"extend", (PyCFunction)PVectorEvolver_extend, METH_O|METH_COEXIST, "Extend"}, + {"set", (PyCFunction)PVectorEvolver_set, METH_VARARGS, "Set item"}, + {"delete", (PyCFunction)PVectorEvolver_delete, METH_VARARGS, "Delete item"}, + {"persistent", (PyCFunction)PVectorEvolver_persistent, METH_NOARGS, "Create PVector from evolver"}, + {"is_dirty", (PyCFunction)PVectorEvolver_is_dirty, METH_NOARGS, "Check if evolver contains modifications"}, + {NULL, NULL} /* sentinel */ +}; + +static PyTypeObject PVectorEvolverType = { + PyVarObject_HEAD_INIT(NULL, 0) + "pvector_evolver", /* tp_name */ + sizeof(PVectorEvolver), /* tp_basicsize */ + 0, /* tp_itemsize */ + /* methods */ + (destructor)PVectorEvolver_dealloc, /* tp_dealloc */ + 0, /* tp_print */ + 0, /* tp_getattr */ + 0, /* tp_setattr */ + 0, /* tp_compare */ + 0, /* tp_repr */ + 0, /* tp_as_number */ + 0, /* tp_as_sequence */ + &PVectorEvolver_mapping_methods, /* tp_as_mapping */ + 0, /* tp_hash */ + 0, /* tp_call */ + 0, /* tp_str */ + PyObject_GenericGetAttr, /* tp_getattro */ + 0, /* tp_setattro */ + 0, /* tp_as_buffer */ + Py_TPFLAGS_DEFAULT | Py_TPFLAGS_HAVE_GC, /* tp_flags */ + 0, /* tp_doc */ + (traverseproc)PVectorEvolver_traverse, /* tp_traverse */ + 0, /* tp_clear */ + 0, /* tp_richcompare */ + 0, /* tp_weaklistoffset */ + 0, /* tp_iter */ + 0, /* tp_iternext */ + PVectorEvolver_methods, /* tp_methods */ + 0, /* tp_members */ +}; + + +// Indicate that a node is "dirty" (has been updated by the evolver) +// by setting the MSB of the refCount. This will be cleared when +// creating a pvector from the evolver (cleaning it). +#define DIRTY_BIT 0x80000000 +#define REF_COUNT_MASK (~DIRTY_BIT) +#define IS_DIRTY(node) ((node)->refCount & DIRTY_BIT) +#define SET_DIRTY(node) ((node)->refCount |= DIRTY_BIT) +#define CLEAR_DIRTY(node) ((node)->refCount &= REF_COUNT_MASK) + + +static void cleanNodeRecursively(VNode *node, int level) { + debug("Cleaning recursively node=%p, level=%u\n", node, level); + + int i; + CLEAR_DIRTY(node); + SET_NODE_REF_COUNT(node, 1); + if(level > 0) { + for(i = 0; i < BRANCH_FACTOR; i++) { + VNode *nextNode = (VNode*)node->items[i]; + if((nextNode != NULL) && IS_DIRTY(nextNode)) { + cleanNodeRecursively(nextNode, level - SHIFT); + } + } + } +} + +static void cleanVector(PVector *vector) { + // Cleaning the vector means that all dirty indications are cleared + // and that the nodes that were dirty get a ref count of 1 since + // they are brand new. Once cleaned the vector can be released into + // the wild. + if(IS_DIRTY(vector->tail)) { + cleanNodeRecursively(vector->tail, 0); + } else { + INC_NODE_REF_COUNT(vector->tail); + } + + if(IS_DIRTY(vector->root)) { + cleanNodeRecursively(vector->root, vector->shift); + } else { + INC_NODE_REF_COUNT(vector->root); + } +} + +static void PVectorEvolver_dealloc(PVectorEvolver *self) { + PyObject_GC_UnTrack(self); + Py_TRASHCAN_SAFE_BEGIN(self); + + if(self->originalVector != self->newVector) { + cleanVector(self->newVector); + Py_DECREF(self->newVector); + } + + Py_DECREF(self->originalVector); + Py_DECREF(self->appendList); + + PyObject_GC_Del(self); + Py_TRASHCAN_SAFE_END(self); +} + +static PyObject *PVectorEvolver_append(PVectorEvolver *self, PyObject *args) { + if (PyList_Append(self->appendList, args) == 0) { + Py_INCREF(self); + return (PyObject*)self; + } + + return NULL; +} + +static PyObject *PVectorEvolver_extend(PVectorEvolver *self, PyObject *args) { + PyObject *retVal = _PyList_Extend((PyListObject *)self->appendList, args); + if (retVal == NULL) { + return NULL; + } + + Py_DECREF(retVal); + Py_INCREF(self); + return (PyObject*)self; +} + +static PyObject *PVectorEvolver_subscript(PVectorEvolver *self, PyObject *item) { + if (PyIndex_Check(item)) { + Py_ssize_t position = PyNumber_AsSsize_t(item, PyExc_IndexError); + if (position == -1 && PyErr_Occurred()) { + return NULL; + } + + if (position < 0) { + position += self->newVector->count + PyList_GET_SIZE(self->appendList); + } + + if(0 <= position && position < self->newVector->count) { + PyObject *result = _get_item(self->newVector, position); + Py_XINCREF(result); + return result; + } else if (0 <= position && position < (self->newVector->count + PyList_GET_SIZE(self->appendList))) { + PyObject *result = PyList_GetItem(self->appendList, position - self->newVector->count); + Py_INCREF(result); + return result; + } else { + PyErr_SetString(PyExc_IndexError, "Index out of range"); + } + } else { + PyErr_Format(PyExc_TypeError, "Indices must be integers, not %.200s", item->ob_type->tp_name); + } + + return NULL; +} + +static VNode* doSetWithDirty(VNode* node, unsigned int level, unsigned int position, PyObject* value) { + VNode* resultNode; + debug("doSetWithDirty(): level == %i\n", level); + if(level == 0) { + if(!IS_DIRTY(node)) { + resultNode = allocNode(); + copyInsert(resultNode->items, node->items, position & BIT_MASK, value); + incRefs((PyObject**)resultNode->items); + SET_DIRTY(resultNode); + } else { + resultNode = node; + Py_INCREF(value); + Py_DECREF(resultNode->items[position & BIT_MASK]); + resultNode->items[position & BIT_MASK] = value; + } + } else { + if(!IS_DIRTY(node)) { + resultNode = copyNode(node); + SET_DIRTY(resultNode); + } else { + resultNode = node; + } + + Py_ssize_t index = (position >> level) & BIT_MASK; + VNode* oldNode = (VNode*)resultNode->items[index]; + resultNode->items[index] = doSetWithDirty(resultNode->items[index], level - SHIFT, position, value); + + if(resultNode->items[index] != oldNode) { + // Node replaced, drop references to old node + DEC_NODE_REF_COUNT(oldNode); + } + } + + return resultNode; +} + +/* + Steals a reference to the object that is inserted in the vector. +*/ +static PyObject *PVectorEvolver_set(PVectorEvolver *self, PyObject *args) { + PyObject *argObj = NULL; /* argument to insert */ + PyObject *position = NULL; + + /* The n parses for size, the O parses for a Python object */ + if(!PyArg_ParseTuple(args, "OO", &position, &argObj)) { + return NULL; + } + + if(PVectorEvolver_set_item(self, position, argObj) < 0) { + return NULL; + } + + Py_INCREF(self); + return (PyObject*)self; +} + +static PyObject *PVectorEvolver_delete(PVectorEvolver *self, PyObject *args) { + PyObject *position = NULL; + + /* The n parses for size, the O parses for a Python object */ + if(!PyArg_ParseTuple(args, "O", &position)) { + return NULL; + } + + if(PVectorEvolver_set_item(self, position, NULL) < 0) { + return NULL; + } + + Py_INCREF(self); + return (PyObject*)self; +} + + +static int internalPVectorDelete(PVectorEvolver *self, Py_ssize_t position) { + // Delete element. Should be unusual. Simple but expensive operation + // that reuses the delete code for the vector. Realize the vector, delete on it and + // then reset the evolver to work on the new vector. + PVector *temp = (PVector*)PVectorEvolver_persistent(self); + PVector *temp2 = (PVector*)internalDelete(temp, position, NULL); + Py_DECREF(temp); + + if(temp2 == NULL) { + return -1; + } + + Py_DECREF(self->originalVector); + self->originalVector = temp2; + self->newVector = self->originalVector; + return 0; +} + +static int PVectorEvolver_set_item(PVectorEvolver *self, PyObject* item, PyObject* value) { + if (PyIndex_Check(item)) { + Py_ssize_t position = PyNumber_AsSsize_t(item, PyExc_IndexError); + if (position == -1 && PyErr_Occurred()) { + return -1; + } + + if (position < 0) { + position += self->newVector->count + PyList_GET_SIZE(self->appendList); + } + + if((0 <= position) && (position < self->newVector->count)) { + if(self->originalVector == self->newVector) { + // Create new vector since we're about to modify the original + self->newVector = rawCopyPVector(self->originalVector); + } + + if(value != NULL) { + if(position < TAIL_OFF(self->newVector)) { + self->newVector->root = doSetWithDirty(self->newVector->root, self->newVector->shift, position, value); + } else { + self->newVector->tail = doSetWithDirty(self->newVector->tail, 0, position, value); + } + + return 0; + } + + return internalPVectorDelete(self, position); + } else if((0 <= position) && (position < (self->newVector->count + PyList_GET_SIZE(self->appendList)))) { + if (value != NULL) { + int result = PyList_SetItem(self->appendList, position - self->newVector->count, value); + if(result == 0) { + Py_INCREF(value); + } + return result; + } + + return internalPVectorDelete(self, position); + } else if((0 <= position) + && (position < (self->newVector->count + PyList_GET_SIZE(self->appendList) + 1)) + && (value != NULL)) { + return PyList_Append(self->appendList, value); + } else { + PyErr_Format(PyExc_IndexError, "Index out of range: %zd", position); + } + } else { + PyErr_Format(PyExc_TypeError, "Indices must be integers, not %.200s", item->ob_type->tp_name); + } + return -1; +} + +static PyObject *PVectorEvolver_persistent(PVectorEvolver *self) { + PVector *resultVector; + if(self->newVector != self->originalVector) { + cleanVector(self->newVector); + Py_DECREF(self->originalVector); + } + + resultVector = self->newVector; + + if(PyList_GET_SIZE(self->appendList)) { + PVector *oldVector = resultVector; + resultVector = (PVector*)PVector_extend(resultVector, self->appendList); + Py_DECREF(oldVector); + Py_DECREF(self->appendList); + self->appendList = NULL; + } + + initializeEvolver(self, resultVector, self->appendList); + Py_INCREF(resultVector); + return (PyObject*)resultVector; +} + +static Py_ssize_t PVectorEvolver_len(PVectorEvolver *self) { + return self->newVector->count + PyList_GET_SIZE(self->appendList); +} + +static PyObject* PVectorEvolver_is_dirty(PVectorEvolver *self) { + if((self->newVector != self->originalVector) || (PyList_GET_SIZE(self->appendList) > 0)) { + Py_INCREF(Py_True); + return Py_True; + } + + Py_INCREF(Py_False); + return Py_False; +} + +static int PVectorEvolver_traverse(PVectorEvolver *self, visitproc visit, void *arg) { + Py_VISIT(self->newVector); + if (self->newVector != self->originalVector) { + Py_VISIT(self->originalVector); + } + Py_VISIT(self->appendList); + return 0; +} + +static PyMethodDef PyrsistentMethods[] = { + {"pvector", pyrsistent_pvec, METH_VARARGS, + "pvector([iterable])\n" + "Create a new persistent vector containing the elements in iterable.\n\n" + ">>> v1 = pvector([1, 2, 3])\n" + ">>> v1\n" + "pvector([1, 2, 3])"}, + {NULL, NULL, 0, NULL} +}; + + +/********************* Python module initialization ************************/ + +#if PY_MAJOR_VERSION >= 3 + static struct PyModuleDef moduledef = { + PyModuleDef_HEAD_INIT, + "pvectorc", /* m_name */ + "Persistent vector", /* m_doc */ + -1, /* m_size */ + PyrsistentMethods, /* m_methods */ + NULL, /* m_reload */ + NULL, /* m_traverse */ + NULL, /* m_clear */ + NULL, /* m_free */ + }; +#endif + +static PyObject* pyrsistent_pvectorc_moduleinit(void) { + PyObject* m; + + // Only allow creation/initialization through factory method pvec + PVectorType.tp_init = NULL; + PVectorType.tp_new = NULL; + + if (PyType_Ready(&PVectorType) < 0) { + return NULL; + } + if (PyType_Ready(&PVectorIterType) < 0) { + return NULL; + } + if (PyType_Ready(&PVectorEvolverType) < 0) { + return NULL; + } + + +#if PY_MAJOR_VERSION >= 3 + m = PyModule_Create(&moduledef); +#else + m = Py_InitModule3("pvectorc", PyrsistentMethods, "Persistent vector"); +#endif + + if (m == NULL) { + return NULL; + } + + if(EMPTY_VECTOR == NULL) { + EMPTY_VECTOR = emptyNewPvec(); + } + + nodeCache.size = 0; + + Py_INCREF(&PVectorType); + PyModule_AddObject(m, "PVector", (PyObject *)&PVectorType); + + return m; +} + +#if PY_MAJOR_VERSION >= 3 +PyMODINIT_FUNC PyInit_pvectorc(void) { + return pyrsistent_pvectorc_moduleinit(); +} +#else +PyMODINIT_FUNC initpvectorc(void) { + pyrsistent_pvectorc_moduleinit(); +} +#endif diff --git a/third_party/python/pyrsistent/pyrsistent.egg-info/PKG-INFO b/third_party/python/pyrsistent/pyrsistent.egg-info/PKG-INFO new file mode 100644 index 0000000000..1d1c159034 --- /dev/null +++ b/third_party/python/pyrsistent/pyrsistent.egg-info/PKG-INFO @@ -0,0 +1,742 @@ +Metadata-Version: 1.1 +Name: pyrsistent +Version: 0.16.0 +Summary: Persistent/Functional/Immutable data structures +Home-page: http://github.com/tobgu/pyrsistent/ +Author: Tobias Gustafsson +Author-email: tobias.l.gustafsson@gmail.com +License: MIT +Description: Pyrsistent + ========== + .. image:: https://travis-ci.org/tobgu/pyrsistent.png?branch=master + :target: https://travis-ci.org/tobgu/pyrsistent + + .. image:: https://badge.fury.io/py/pyrsistent.svg + :target: https://badge.fury.io/py/pyrsistent + + .. image:: https://coveralls.io/repos/tobgu/pyrsistent/badge.svg?branch=master&service=github + :target: https://coveralls.io/github/tobgu/pyrsistent?branch=master + + + .. _Pyrthon: https://www.github.com/tobgu/pyrthon/ + + Pyrsistent is a number of persistent collections (by some referred to as functional data structures). Persistent in + the sense that they are immutable. + + All methods on a data structure that would normally mutate it instead return a new copy of the structure containing the + requested updates. The original structure is left untouched. + + This will simplify the reasoning about what a program does since no hidden side effects ever can take place to these + data structures. You can rest assured that the object you hold a reference to will remain the same throughout its + lifetime and need not worry that somewhere five stack levels below you in the darkest corner of your application + someone has decided to remove that element that you expected to be there. + + Pyrsistent is influenced by persistent data structures such as those found in the standard library of Clojure. The + data structures are designed to share common elements through path copying. + It aims at taking these concepts and make them as pythonic as possible so that they can be easily integrated into any python + program without hassle. + + If you want to go all in on persistent data structures and use literal syntax to define them in your code rather + than function calls check out Pyrthon_. + + Examples + -------- + .. _Sequence: collections_ + .. _Hashable: collections_ + .. _Mapping: collections_ + .. _Mappings: collections_ + .. _Set: collections_ + .. _collections: https://docs.python.org/3/library/collections.abc.html + .. _documentation: http://pyrsistent.readthedocs.org/ + + The collection types and key features currently implemented are: + + * PVector_, similar to a python list + * PMap_, similar to dict + * PSet_, similar to set + * PRecord_, a PMap on steroids with fixed fields, optional type and invariant checking and much more + * PClass_, a Python class fixed fields, optional type and invariant checking and much more + * `Checked collections`_, PVector, PMap and PSet with optional type and invariance checks and more + * PBag, similar to collections.Counter + * PList, a classic singly linked list + * PDeque, similar to collections.deque + * Immutable object type (immutable) built on the named tuple + * freeze_ and thaw_ functions to convert between pythons standard collections and pyrsistent collections. + * Flexible transformations_ of arbitrarily complex structures built from PMaps and PVectors. + + Below are examples of common usage patterns for some of the structures and features. More information and + full documentation for all data structures is available in the documentation_. + + .. _PVector: + + PVector + ~~~~~~~ + With full support for the Sequence_ protocol PVector is meant as a drop in replacement to the built in list from a readers + point of view. Write operations of course differ since no in place mutation is done but naming should be in line + with corresponding operations on the built in list. + + Support for the Hashable_ protocol also means that it can be used as key in Mappings_. + + Appends are amortized O(1). Random access and insert is log32(n) where n is the size of the vector. + + .. code:: python + + >>> from pyrsistent import v, pvector + + # No mutation of vectors once created, instead they + # are "evolved" leaving the original untouched + >>> v1 = v(1, 2, 3) + >>> v2 = v1.append(4) + >>> v3 = v2.set(1, 5) + >>> v1 + pvector([1, 2, 3]) + >>> v2 + pvector([1, 2, 3, 4]) + >>> v3 + pvector([1, 5, 3, 4]) + + # Random access and slicing + >>> v3[1] + 5 + >>> v3[1:3] + pvector([5, 3]) + + # Iteration + >>> list(x + 1 for x in v3) + [2, 6, 4, 5] + >>> pvector(2 * x for x in range(3)) + pvector([0, 2, 4]) + + .. _PMap: + + PMap + ~~~~ + With full support for the Mapping_ protocol PMap is meant as a drop in replacement to the built in dict from a readers point + of view. Support for the Hashable_ protocol also means that it can be used as key in other Mappings_. + + Random access and insert is log32(n) where n is the size of the map. + + .. code:: python + + >>> from pyrsistent import m, pmap, v + + # No mutation of maps once created, instead they are + # "evolved" leaving the original untouched + >>> m1 = m(a=1, b=2) + >>> m2 = m1.set('c', 3) + >>> m3 = m2.set('a', 5) + >>> m1 + pmap({'a': 1, 'b': 2}) + >>> m2 + pmap({'a': 1, 'c': 3, 'b': 2}) + >>> m3 + pmap({'a': 5, 'c': 3, 'b': 2}) + >>> m3['a'] + 5 + + # Evolution of nested persistent structures + >>> m4 = m(a=5, b=6, c=v(1, 2)) + >>> m4.transform(('c', 1), 17) + pmap({'a': 5, 'c': pvector([1, 17]), 'b': 6}) + >>> m5 = m(a=1, b=2) + + # Evolve by merging with other mappings + >>> m5.update(m(a=2, c=3), {'a': 17, 'd': 35}) + pmap({'a': 17, 'c': 3, 'b': 2, 'd': 35}) + >>> pmap({'x': 1, 'y': 2}) + pmap({'y': 3, 'z': 4}) + pmap({'y': 3, 'x': 1, 'z': 4}) + + # Dict-like methods to convert to list and iterate + >>> m3.items() + pvector([('a', 5), ('c', 3), ('b', 2)]) + >>> list(m3) + ['a', 'c', 'b'] + + .. _PSet: + + PSet + ~~~~ + With full support for the Set_ protocol PSet is meant as a drop in replacement to the built in set from a readers point + of view. Support for the Hashable_ protocol also means that it can be used as key in Mappings_. + + Random access and insert is log32(n) where n is the size of the set. + + .. code:: python + + >>> from pyrsistent import s + + # No mutation of sets once created, you know the story... + >>> s1 = s(1, 2, 3, 2) + >>> s2 = s1.add(4) + >>> s3 = s1.remove(1) + >>> s1 + pset([1, 2, 3]) + >>> s2 + pset([1, 2, 3, 4]) + >>> s3 + pset([2, 3]) + + # Full support for set operations + >>> s1 | s(3, 4, 5) + pset([1, 2, 3, 4, 5]) + >>> s1 & s(3, 4, 5) + pset([3]) + >>> s1 < s2 + True + >>> s1 < s(3, 4, 5) + False + + .. _PRecord: + + PRecord + ~~~~~~~ + A PRecord is a PMap with a fixed set of specified fields. Records are declared as python classes inheriting + from PRecord. Because it is a PMap it has full support for all Mapping methods such as iteration and element + access using subscript notation. + + .. code:: python + + >>> from pyrsistent import PRecord, field + >>> class ARecord(PRecord): + ... x = field() + ... + >>> r = ARecord(x=3) + >>> r + ARecord(x=3) + >>> r.x + 3 + >>> r.set(x=2) + ARecord(x=2) + >>> r.set(y=2) + Traceback (most recent call last): + AttributeError: 'y' is not among the specified fields for ARecord + + Type information + **************** + It is possible to add type information to the record to enforce type checks. Multiple allowed types can be specified + by providing an iterable of types. + + .. code:: python + + >>> class BRecord(PRecord): + ... x = field(type=int) + ... y = field(type=(int, type(None))) + ... + >>> BRecord(x=3, y=None) + BRecord(y=None, x=3) + >>> BRecord(x=3.0) + Traceback (most recent call last): + PTypeError: Invalid type for field BRecord.x, was float + + + Custom types (classes) that are iterable should be wrapped in a tuple to prevent their + members being added to the set of valid types. Although Enums in particular are now + supported without wrapping, see #83 for more information. + + Mandatory fields + **************** + Fields are not mandatory by default but can be specified as such. If fields are missing an + *InvariantException* will be thrown which contains information about the missing fields. + + .. code:: python + + >>> from pyrsistent import InvariantException + >>> class CRecord(PRecord): + ... x = field(mandatory=True) + ... + >>> r = CRecord(x=3) + >>> try: + ... r.discard('x') + ... except InvariantException as e: + ... print(e.missing_fields) + ... + ('CRecord.x',) + + Invariants + ********** + It is possible to add invariants that must hold when evolving the record. Invariants can be + specified on both field and record level. If invariants fail an *InvariantException* will be + thrown which contains information about the failing invariants. An invariant function should + return a tuple consisting of a boolean that tells if the invariant holds or not and an object + describing the invariant. This object can later be used to identify which invariant that failed. + + The global invariant function is only executed if all field invariants hold. + + Global invariants are inherited to subclasses. + + .. code:: python + + >>> class RestrictedVector(PRecord): + ... __invariant__ = lambda r: (r.y >= r.x, 'x larger than y') + ... x = field(invariant=lambda x: (x > 0, 'x negative')) + ... y = field(invariant=lambda y: (y > 0, 'y negative')) + ... + >>> r = RestrictedVector(y=3, x=2) + >>> try: + ... r.set(x=-1, y=-2) + ... except InvariantException as e: + ... print(e.invariant_errors) + ... + ('y negative', 'x negative') + >>> try: + ... r.set(x=2, y=1) + ... except InvariantException as e: + ... print(e.invariant_errors) + ... + ('x larger than y',) + + Invariants may also contain multiple assertions. For those cases the invariant function should + return a tuple of invariant tuples as described above. This structure is reflected in the + invariant_errors attribute of the exception which will contain tuples with data from all failed + invariants. Eg: + + .. code:: python + + >>> class EvenX(PRecord): + ... x = field(invariant=lambda x: ((x > 0, 'x negative'), (x % 2 == 0, 'x odd'))) + ... + >>> try: + ... EvenX(x=-1) + ... except InvariantException as e: + ... print(e.invariant_errors) + ... + (('x negative', 'x odd'),) + + + Factories + ********* + It's possible to specify factory functions for fields. The factory function receives whatever + is supplied as field value and the actual returned by the factory is assigned to the field + given that any type and invariant checks hold. + PRecords have a default factory specified as a static function on the class, create(). It takes + a *Mapping* as argument and returns an instance of the specific record. + If a record has fields of type PRecord the create() method of that record will + be called to create the "sub record" if no factory has explicitly been specified to override + this behaviour. + + .. code:: python + + >>> class DRecord(PRecord): + ... x = field(factory=int) + ... + >>> class ERecord(PRecord): + ... d = field(type=DRecord) + ... + >>> ERecord.create({'d': {'x': '1'}}) + ERecord(d=DRecord(x=1)) + + Collection fields + ***************** + It is also possible to have fields with ``pyrsistent`` collections. + + .. code:: python + + >>> from pyrsistent import pset_field, pmap_field, pvector_field + >>> class MultiRecord(PRecord): + ... set_of_ints = pset_field(int) + ... map_int_to_str = pmap_field(int, str) + ... vector_of_strs = pvector_field(str) + ... + + Serialization + ************* + PRecords support serialization back to dicts. Default serialization will take keys and values + "as is" and output them into a dict. It is possible to specify custom serialization functions + to take care of fields that require special treatment. + + .. code:: python + + >>> from datetime import date + >>> class Person(PRecord): + ... name = field(type=unicode) + ... birth_date = field(type=date, + ... serializer=lambda format, d: d.strftime(format['date'])) + ... + >>> john = Person(name=u'John', birth_date=date(1985, 10, 21)) + >>> john.serialize({'date': '%Y-%m-%d'}) + {'birth_date': '1985-10-21', 'name': u'John'} + + + .. _instar: https://github.com/boxed/instar/ + + .. _PClass: + + PClass + ~~~~~~ + A PClass is a python class with a fixed set of specified fields. PClasses are declared as python classes inheriting + from PClass. It is defined the same way that PRecords are and behaves like a PRecord in all aspects except that it + is not a PMap and hence not a collection but rather a plain Python object. + + .. code:: python + + >>> from pyrsistent import PClass, field + >>> class AClass(PClass): + ... x = field() + ... + >>> a = AClass(x=3) + >>> a + AClass(x=3) + >>> a.x + 3 + + + Checked collections + ~~~~~~~~~~~~~~~~~~~ + Checked collections currently come in three flavors: CheckedPVector, CheckedPMap and CheckedPSet. + + .. code:: python + + >>> from pyrsistent import CheckedPVector, CheckedPMap, CheckedPSet, thaw + >>> class Positives(CheckedPSet): + ... __type__ = (long, int) + ... __invariant__ = lambda n: (n >= 0, 'Negative') + ... + >>> class Lottery(PRecord): + ... name = field(type=str) + ... numbers = field(type=Positives, invariant=lambda p: (len(p) > 0, 'No numbers')) + ... + >>> class Lotteries(CheckedPVector): + ... __type__ = Lottery + ... + >>> class LotteriesByDate(CheckedPMap): + ... __key_type__ = date + ... __value_type__ = Lotteries + ... + >>> lotteries = LotteriesByDate.create({date(2015, 2, 15): [{'name': 'SuperLotto', 'numbers': {1, 2, 3}}, + ... {'name': 'MegaLotto', 'numbers': {4, 5, 6}}], + ... date(2015, 2, 16): [{'name': 'SuperLotto', 'numbers': {3, 2, 1}}, + ... {'name': 'MegaLotto', 'numbers': {6, 5, 4}}]}) + >>> lotteries + LotteriesByDate({datetime.date(2015, 2, 15): Lotteries([Lottery(numbers=Positives([1, 2, 3]), name='SuperLotto'), Lottery(numbers=Positives([4, 5, 6]), name='MegaLotto')]), datetime.date(2015, 2, 16): Lotteries([Lottery(numbers=Positives([1, 2, 3]), name='SuperLotto'), Lottery(numbers=Positives([4, 5, 6]), name='MegaLotto')])}) + + # The checked versions support all operations that the corresponding + # unchecked types do + >>> lottery_0215 = lotteries[date(2015, 2, 15)] + >>> lottery_0215.transform([0, 'name'], 'SuperDuperLotto') + Lotteries([Lottery(numbers=Positives([1, 2, 3]), name='SuperDuperLotto'), Lottery(numbers=Positives([4, 5, 6]), name='MegaLotto')]) + + # But also makes asserts that types and invariants hold + >>> lottery_0215.transform([0, 'name'], 999) + Traceback (most recent call last): + PTypeError: Invalid type for field Lottery.name, was int + + >>> lottery_0215.transform([0, 'numbers'], set()) + Traceback (most recent call last): + InvariantException: Field invariant failed + + # They can be converted back to python built ins with either thaw() + # or serialize() (which provides possibilities to customize serialization) + >>> thaw(lottery_0215) + [{'numbers': set([1, 2, 3]), 'name': 'SuperLotto'}, {'numbers': set([4, 5, 6]), 'name': 'MegaLotto'}] + >>> lottery_0215.serialize() + [{'numbers': set([1, 2, 3]), 'name': 'SuperLotto'}, {'numbers': set([4, 5, 6]), 'name': 'MegaLotto'}] + + .. _transformations: + + Transformations + ~~~~~~~~~~~~~~~ + Transformations are inspired by the cool library instar_ for Clojure. They let you evolve PMaps and PVectors + with arbitrarily deep/complex nesting using simple syntax and flexible matching syntax. + + The first argument to transformation is the path that points out the value to transform. The + second is the transformation to perform. If the transformation is callable it will be applied + to the value(s) matching the path. The path may also contain callables. In that case they are + treated as matchers. If the matcher returns True for a specific key it is considered for transformation. + + .. code:: python + + # Basic examples + >>> from pyrsistent import inc, freeze, thaw, rex, ny, discard + >>> v1 = freeze([1, 2, 3, 4, 5]) + >>> v1.transform([2], inc) + pvector([1, 2, 4, 4, 5]) + >>> v1.transform([lambda ix: 0 < ix < 4], 8) + pvector([1, 8, 8, 8, 5]) + >>> v1.transform([lambda ix, v: ix == 0 or v == 5], 0) + pvector([0, 2, 3, 4, 0]) + + # The (a)ny matcher can be used to match anything + >>> v1.transform([ny], 8) + pvector([8, 8, 8, 8, 8]) + + # Regular expressions can be used for matching + >>> scores = freeze({'John': 12, 'Joseph': 34, 'Sara': 23}) + >>> scores.transform([rex('^Jo')], 0) + pmap({'Joseph': 0, 'Sara': 23, 'John': 0}) + + # Transformations can be done on arbitrarily deep structures + >>> news_paper = freeze({'articles': [{'author': 'Sara', 'content': 'A short article'}, + ... {'author': 'Steve', 'content': 'A slightly longer article'}], + ... 'weather': {'temperature': '11C', 'wind': '5m/s'}}) + >>> short_news = news_paper.transform(['articles', ny, 'content'], lambda c: c[:25] + '...' if len(c) > 25 else c) + >>> very_short_news = news_paper.transform(['articles', ny, 'content'], lambda c: c[:15] + '...' if len(c) > 15 else c) + >>> very_short_news.articles[0].content + 'A short article' + >>> very_short_news.articles[1].content + 'A slightly long...' + + # When nothing has been transformed the original data structure is kept + >>> short_news is news_paper + True + >>> very_short_news is news_paper + False + >>> very_short_news.articles[0] is news_paper.articles[0] + True + + # There is a special transformation that can be used to discard elements. Also + # multiple transformations can be applied in one call + >>> thaw(news_paper.transform(['weather'], discard, ['articles', ny, 'content'], discard)) + {'articles': [{'author': 'Sara'}, {'author': 'Steve'}]} + + Evolvers + ~~~~~~~~ + PVector, PMap and PSet all have support for a concept dubbed *evolvers*. An evolver acts like a mutable + view of the underlying persistent data structure with "transaction like" semantics. No updates of the original + data structure is ever performed, it is still fully immutable. + + The evolvers have a very limited API by design to discourage excessive, and inappropriate, usage as that would + take us down the mutable road. In principle only basic mutation and element access functions are supported. + Check out the documentation_ of each data structure for specific examples. + + Examples of when you may want to use an evolver instead of working directly with the data structure include: + + * Multiple updates are done to the same data structure and the intermediate results are of no + interest. In this case using an evolver may be a more efficient and easier to work with. + * You need to pass a vector into a legacy function or a function that you have no control + over which performs in place mutations. In this case pass an evolver instance + instead and then create a new pvector from the evolver once the function returns. + + .. code:: python + + >>> from pyrsistent import v + + # In place mutation as when working with the built in counterpart + >>> v1 = v(1, 2, 3) + >>> e = v1.evolver() + >>> e[1] = 22 + >>> e = e.append(4) + >>> e = e.extend([5, 6]) + >>> e[5] += 1 + >>> len(e) + 6 + + # The evolver is considered *dirty* when it contains changes compared to the underlying vector + >>> e.is_dirty() + True + + # But the underlying pvector still remains untouched + >>> v1 + pvector([1, 2, 3]) + + # Once satisfied with the updates you can produce a new pvector containing the updates. + # The new pvector will share data with the original pvector in the same way that would have + # been done if only using operations on the pvector. + >>> v2 = e.persistent() + >>> v2 + pvector([1, 22, 3, 4, 5, 7]) + + # The evolver is now no longer considered *dirty* as it contains no differences compared to the + # pvector just produced. + >>> e.is_dirty() + False + + # You may continue to work with the same evolver without affecting the content of v2 + >>> e[0] = 11 + + # Or create a new evolver from v2. The two evolvers can be updated independently but will both + # share data with v2 where possible. + >>> e2 = v2.evolver() + >>> e2[0] = 1111 + >>> e.persistent() + pvector([11, 22, 3, 4, 5, 7]) + >>> e2.persistent() + pvector([1111, 22, 3, 4, 5, 7]) + + .. _freeze: + .. _thaw: + + freeze and thaw + ~~~~~~~~~~~~~~~ + These functions are great when your cozy immutable world has to interact with the evil mutable world outside. + + .. code:: python + + >>> from pyrsistent import freeze, thaw, v, m + >>> freeze([1, {'a': 3}]) + pvector([1, pmap({'a': 3})]) + >>> thaw(v(1, m(a=3))) + [1, {'a': 3}] + + Compatibility + ------------- + + Pyrsistent is developed and tested on Python 2.7, 3.5, 3.6, 3.7 and PyPy (Python 2 and 3 compatible). It will most + likely work on all other versions >= 3.4 but no guarantees are given. :) + + Compatibility issues + ~~~~~~~~~~~~~~~~~~~~ + + .. _27: https://github.com/tobgu/pyrsistent/issues/27 + + There is currently one known compatibility issue when comparing built in sets and frozensets to PSets as discussed in 27_. + It affects python 2 versions < 2.7.8 and python 3 versions < 3.4.0 and is due to a bug described in + http://bugs.python.org/issue8743. + + Comparisons will fail or be incorrect when using the set/frozenset as left hand side of the comparison. As a workaround + you need to either upgrade Python to a more recent version, avoid comparing sets/frozensets with PSets or always make + sure to convert both sides of the comparison to the same type before performing the comparison. + + Performance + ----------- + + Pyrsistent is developed with performance in mind. Still, while some operations are nearly on par with their built in, + mutable, counterparts in terms of speed, other operations are slower. In the cases where attempts at + optimizations have been done, speed has generally been valued over space. + + Pyrsistent comes with two API compatible flavors of PVector (on which PMap and PSet are based), one pure Python + implementation and one implemented as a C extension. The latter generally being 2 - 20 times faster than the former. + The C extension will be used automatically when possible. + + The pure python implementation is fully PyPy compatible. Running it under PyPy speeds operations up considerably if + the structures are used heavily (if JITed), for some cases the performance is almost on par with the built in counterparts. + + Type hints + ---------- + + PEP 561 style type hints for use with mypy and various editors are available for most types and functions in pyrsistent. + + Type classes for annotating your own code with pyrsistent types are also available under pyrsistent.typing. + + Installation + ------------ + + pip install pyrsistent + + Documentation + ------------- + + Available at http://pyrsistent.readthedocs.org/ + + Brief presentation available at http://slides.com/tobiasgustafsson/immutability-and-python/ + + Contributors + ------------ + + Tobias Gustafsson https://github.com/tobgu + + Christopher Armstrong https://github.com/radix + + Anders Hovmöller https://github.com/boxed + + Itamar Turner-Trauring https://github.com/itamarst + + Jonathan Lange https://github.com/jml + + Richard Futrell https://github.com/Futrell + + Jakob Hollenstein https://github.com/jkbjh + + David Honour https://github.com/foolswood + + David R. MacIver https://github.com/DRMacIver + + Marcus Ewert https://github.com/sarum90 + + Jean-Paul Calderone https://github.com/exarkun + + Douglas Treadwell https://github.com/douglas-treadwell + + Travis Parker https://github.com/teepark + + Julian Berman https://github.com/Julian + + Dennis Tomas https://github.com/dtomas + + Neil Vyas https://github.com/neilvyas + + doozr https://github.com/doozr + + Kamil Galuszka https://github.com/galuszkak + + Tsuyoshi Hombashi https://github.com/thombashi + + nattofriends https://github.com/nattofriends + + agberk https://github.com/agberk + + Waleed Khan https://github.com/arxanas + + Jean-Louis Fuchs https://github.com/ganwell + + Carlos Corbacho https://github.com/ccorbacho + + Felix Yan https://github.com/felixonmars + + benrg https://github.com/benrg + + Jere Lahelma https://github.com/je-l + + Max Taggart https://github.com/MaxTaggart + + Vincent Philippon https://github.com/vphilippon + + Semen Zhydenko https://github.com/ss18 + + Till Varoquaux https://github.com/till-varoquaux + + Michal Kowalik https://github.com/michalvi + + ossdev07 https://github.com/ossdev07 + + Kerry Olesen https://github.com/qhesz + + johnthagen https://github.com/johnthagen + + Contributing + ------------ + + Want to contribute? That's great! If you experience problems please log them on GitHub. If you want to contribute code, + please fork the repository and submit a pull request. + + Run tests + ~~~~~~~~~ + .. _tox: https://tox.readthedocs.io/en/latest/ + + Tests can be executed using tox_. + + Install tox: ``pip install tox`` + + Run test for Python 2.7: ``tox -epy27`` + + Release + ~~~~~~~ + * Update CHANGES.txt + * Update README with any new contributors and potential info needed. + * Update _pyrsistent_version.py + * python setup.py sdist upload + * Commit and tag with new version: git add -u . && git commit -m 'Prepare version vX.Y.Z' && git tag -a vX.Y.Z -m 'vX.Y.Z' + * Push commit and tags: git push && git push --tags + + Project status + -------------- + Pyrsistent can be considered stable and mature (who knows, there may even be a 1.0 some day :-)). The project is + maintained, bugs fixed, PRs reviewed and merged and new releases made. I currently do not have time for development + of new features or functionality which I don't have use for myself. I'm more than happy to take PRs for new + functionality though! + + There are a bunch of issues marked with ``enhancement`` and ``help wanted`` that contain requests for new functionality + that would be nice to include. The level of difficulty and extend of the issues varies, please reach out to me if you're + interested in working on any of them. + + If you feel that you have a grand master plan for where you would like Pyrsistent to go and have the time to put into + it please don't hesitate to discuss this with me and submit PRs for it. If all goes well I'd be more than happy to add + additional maintainers to the project! + +Platform: UNKNOWN +Classifier: Intended Audience :: Developers +Classifier: License :: OSI Approved :: MIT License +Classifier: Operating System :: OS Independent +Classifier: Programming Language :: Python :: 3.5 +Classifier: Programming Language :: Python :: 3.6 +Classifier: Programming Language :: Python :: 3.7 +Classifier: Programming Language :: Python :: Implementation :: PyPy diff --git a/third_party/python/pyrsistent/pyrsistent.egg-info/SOURCES.txt b/third_party/python/pyrsistent/pyrsistent.egg-info/SOURCES.txt new file mode 100644 index 0000000000..9d3cc0a8d6 --- /dev/null +++ b/third_party/python/pyrsistent/pyrsistent.egg-info/SOURCES.txt @@ -0,0 +1,53 @@ +CHANGES.txt +LICENCE.mit +MANIFEST.in +README +README.rst +_pyrsistent_version.py +pvectorcmodule.c +setup.cfg +setup.py +pyrsistent/__init__.py +pyrsistent/__init__.pyi +pyrsistent/_checked_types.py +pyrsistent/_compat.py +pyrsistent/_field_common.py +pyrsistent/_helpers.py +pyrsistent/_immutable.py +pyrsistent/_pbag.py +pyrsistent/_pclass.py +pyrsistent/_pdeque.py +pyrsistent/_plist.py +pyrsistent/_pmap.py +pyrsistent/_precord.py +pyrsistent/_pset.py +pyrsistent/_pvector.py +pyrsistent/_toolz.py +pyrsistent/_transformations.py +pyrsistent/py.typed +pyrsistent/typing.py +pyrsistent/typing.pyi +pyrsistent.egg-info/PKG-INFO +pyrsistent.egg-info/SOURCES.txt +pyrsistent.egg-info/dependency_links.txt +pyrsistent.egg-info/requires.txt +pyrsistent.egg-info/top_level.txt +tests/bag_test.py +tests/checked_map_test.py +tests/checked_set_test.py +tests/checked_vector_test.py +tests/class_test.py +tests/deque_test.py +tests/field_test.py +tests/freeze_test.py +tests/hypothesis_vector_test.py +tests/immutable_object_test.py +tests/list_test.py +tests/map_test.py +tests/memory_profiling.py +tests/record_test.py +tests/regression_test.py +tests/set_test.py +tests/toolz_test.py +tests/transform_test.py +tests/vector_test.py
\ No newline at end of file diff --git a/third_party/python/pyrsistent/pyrsistent.egg-info/dependency_links.txt b/third_party/python/pyrsistent/pyrsistent.egg-info/dependency_links.txt new file mode 100644 index 0000000000..8b13789179 --- /dev/null +++ b/third_party/python/pyrsistent/pyrsistent.egg-info/dependency_links.txt @@ -0,0 +1 @@ + diff --git a/third_party/python/pyrsistent/pyrsistent.egg-info/requires.txt b/third_party/python/pyrsistent/pyrsistent.egg-info/requires.txt new file mode 100644 index 0000000000..ffe2fce498 --- /dev/null +++ b/third_party/python/pyrsistent/pyrsistent.egg-info/requires.txt @@ -0,0 +1 @@ +six diff --git a/third_party/python/pyrsistent/pyrsistent.egg-info/top_level.txt b/third_party/python/pyrsistent/pyrsistent.egg-info/top_level.txt new file mode 100644 index 0000000000..f2460728a9 --- /dev/null +++ b/third_party/python/pyrsistent/pyrsistent.egg-info/top_level.txt @@ -0,0 +1,3 @@ +_pyrsistent_version +pvectorc +pyrsistent diff --git a/third_party/python/pyrsistent/pyrsistent/__init__.py b/third_party/python/pyrsistent/pyrsistent/__init__.py new file mode 100644 index 0000000000..be299658f3 --- /dev/null +++ b/third_party/python/pyrsistent/pyrsistent/__init__.py @@ -0,0 +1,47 @@ +# -*- coding: utf-8 -*- + +from pyrsistent._pmap import pmap, m, PMap + +from pyrsistent._pvector import pvector, v, PVector + +from pyrsistent._pset import pset, s, PSet + +from pyrsistent._pbag import pbag, b, PBag + +from pyrsistent._plist import plist, l, PList + +from pyrsistent._pdeque import pdeque, dq, PDeque + +from pyrsistent._checked_types import ( + CheckedPMap, CheckedPVector, CheckedPSet, InvariantException, CheckedKeyTypeError, + CheckedValueTypeError, CheckedType, optional) + +from pyrsistent._field_common import ( + field, PTypeError, pset_field, pmap_field, pvector_field) + +from pyrsistent._precord import PRecord + +from pyrsistent._pclass import PClass, PClassMeta + +from pyrsistent._immutable import immutable + +from pyrsistent._helpers import freeze, thaw, mutant + +from pyrsistent._transformations import inc, discard, rex, ny + +from pyrsistent._toolz import get_in + + +__all__ = ('pmap', 'm', 'PMap', + 'pvector', 'v', 'PVector', + 'pset', 's', 'PSet', + 'pbag', 'b', 'PBag', + 'plist', 'l', 'PList', + 'pdeque', 'dq', 'PDeque', + 'CheckedPMap', 'CheckedPVector', 'CheckedPSet', 'InvariantException', 'CheckedKeyTypeError', 'CheckedValueTypeError', 'CheckedType', 'optional', + 'PRecord', 'field', 'pset_field', 'pmap_field', 'pvector_field', + 'PClass', 'PClassMeta', + 'immutable', + 'freeze', 'thaw', 'mutant', + 'get_in', + 'inc', 'discard', 'rex', 'ny') diff --git a/third_party/python/pyrsistent/pyrsistent/__init__.pyi b/third_party/python/pyrsistent/pyrsistent/__init__.pyi new file mode 100644 index 0000000000..5909f7991a --- /dev/null +++ b/third_party/python/pyrsistent/pyrsistent/__init__.pyi @@ -0,0 +1,213 @@ +# flake8: noqa: E704 +# from https://gist.github.com/WuTheFWasThat/091a17d4b5cab597dfd5d4c2d96faf09 +# Stubs for pyrsistent (Python 3.6) + +from typing import Any +from typing import AnyStr +from typing import Callable +from typing import Iterable +from typing import Iterator +from typing import List +from typing import Optional +from typing import Mapping +from typing import MutableMapping +from typing import Sequence +from typing import Set +from typing import Union +from typing import Tuple +from typing import Type +from typing import TypeVar +from typing import overload + +# see commit 08519aa for explanation of the re-export +from pyrsistent.typing import CheckedKeyTypeError as CheckedKeyTypeError +from pyrsistent.typing import CheckedPMap as CheckedPMap +from pyrsistent.typing import CheckedPSet as CheckedPSet +from pyrsistent.typing import CheckedPVector as CheckedPVector +from pyrsistent.typing import CheckedType as CheckedType +from pyrsistent.typing import CheckedValueTypeError as CheckedValueTypeError +from pyrsistent.typing import InvariantException as InvariantException +from pyrsistent.typing import PClass as PClass +from pyrsistent.typing import PBag as PBag +from pyrsistent.typing import PDeque as PDeque +from pyrsistent.typing import PList as PList +from pyrsistent.typing import PMap as PMap +from pyrsistent.typing import PMapEvolver as PMapEvolver +from pyrsistent.typing import PSet as PSet +from pyrsistent.typing import PSetEvolver as PSetEvolver +from pyrsistent.typing import PTypeError as PTypeError +from pyrsistent.typing import PVector as PVector +from pyrsistent.typing import PVectorEvolver as PVectorEvolver + +T = TypeVar('T') +KT = TypeVar('KT') +VT = TypeVar('VT') + +def pmap(initial: Union[Mapping[KT, VT], Iterable[Tuple[KT, VT]]] = {}, pre_size: int = 0) -> PMap[KT, VT]: ... +def m(**kwargs: VT) -> PMap[str, VT]: ... + +def pvector(iterable: Iterable[T] = ...) -> PVector[T]: ... +def v(*iterable: T) -> PVector[T]: ... + +def pset(iterable: Iterable[T] = (), pre_size: int = 8) -> PSet[T]: ... +def s(*iterable: T) -> PSet[T]: ... + +# see class_test.py for use cases +Invariant = Tuple[bool, Optional[Union[str, Callable[[], str]]]] + +@overload +def field( + type: Union[Type[T], Sequence[Type[T]]] = ..., + invariant: Callable[[Any], Union[Invariant, Iterable[Invariant]]] = lambda _: (True, None), + initial: Any = object(), + mandatory: bool = False, + factory: Callable[[Any], T] = lambda x: x, + serializer: Callable[[Any, T], Any] = lambda _, value: value, +) -> T: ... +# The actual return value (_PField) is irrelevant after a PRecord has been instantiated, +# see https://github.com/tobgu/pyrsistent/blob/master/pyrsistent/_precord.py#L10 +@overload +def field( + type: Any = ..., + invariant: Callable[[Any], Union[Invariant, Iterable[Invariant]]] = lambda _: (True, None), + initial: Any = object(), + mandatory: bool = False, + factory: Callable[[Any], Any] = lambda x: x, + serializer: Callable[[Any, Any], Any] = lambda _, value: value, +) -> Any: ... + +# Use precise types for the simplest use cases, but fall back to Any for +# everything else. See record_test.py for the wide range of possible types for +# item_type +@overload +def pset_field( + item_type: Type[T], + optional: bool = False, + initial: Iterable[T] = ..., +) -> PSet[T]: ... +@overload +def pset_field( + item_type: Any, + optional: bool = False, + initial: Any = (), +) -> PSet[Any]: ... + +@overload +def pmap_field( + key_type: Type[KT], + value_type: Type[VT], + optional: bool = False, + invariant: Callable[[Any], Tuple[bool, Optional[str]]] = lambda _: (True, None), +) -> PMap[KT, VT]: ... +@overload +def pmap_field( + key_type: Any, + value_type: Any, + optional: bool = False, + invariant: Callable[[Any], Tuple[bool, Optional[str]]] = lambda _: (True, None), +) -> PMap[Any, Any]: ... + +@overload +def pvector_field( + item_type: Type[T], + optional: bool = False, + initial: Iterable[T] = ..., +) -> PVector[T]: ... +@overload +def pvector_field( + item_type: Any, + optional: bool = False, + initial: Any = (), +) -> PVector[Any]: ... + +def pbag(elements: Iterable[T]) -> PBag[T]: ... +def b(*elements: T) -> PBag[T]: ... + +def plist(iterable: Iterable[T] = (), reverse: bool = False) -> PList[T]: ... +def l(*elements: T) -> PList[T]: ... + +def pdeque(iterable: Optional[Iterable[T]] = None, maxlen: Optional[int] = None) -> PDeque[T]: ... +def dq(*iterable: T) -> PDeque[T]: ... + +@overload +def optional(type: T) -> Tuple[T, Type[None]]: ... +@overload +def optional(*typs: Any) -> Tuple[Any, ...]: ... + +T_PRecord = TypeVar('T_PRecord', bound='PRecord') +class PRecord(PMap[AnyStr, Any]): + _precord_fields: Mapping + _precord_initial_values: Mapping + + def __hash__(self) -> int: ... + def __init__(self, **kwargs: Any) -> None: ... + def __iter__(self) -> Iterator[Any]: ... + def __len__(self) -> int: ... + @classmethod + def create( + cls: Type[T_PRecord], + kwargs: Mapping, + _factory_fields: Optional[Iterable] = None, + ignore_extra: bool = False, + ) -> T_PRecord: ... + # This is OK because T_PRecord is a concrete type + def discard(self: T_PRecord, key: KT) -> T_PRecord: ... + def remove(self: T_PRecord, key: KT) -> T_PRecord: ... + + def serialize(self, format: Optional[Any] = ...) -> MutableMapping: ... + + # From pyrsistent documentation: + # This set function differs slightly from that in the PMap + # class. First of all it accepts key-value pairs. Second it accepts multiple key-value + # pairs to perform one, atomic, update of multiple fields. + @overload + def set(self, key: KT, val: VT) -> Any: ... + @overload + def set(self, **kwargs: VT) -> Any: ... + +def immutable( + members: Union[str, Iterable[str]] = '', + name: str = 'Immutable', + verbose: bool = False, +) -> Tuple: ... # actually a namedtuple + +# ignore mypy warning "Overloaded function signatures 1 and 5 overlap with +# incompatible return types" +@overload +def freeze(o: Mapping[KT, VT]) -> PMap[KT, VT]: ... # type: ignore +@overload +def freeze(o: List[T]) -> PVector[T]: ... # type: ignore +@overload +def freeze(o: Tuple[T, ...]) -> Tuple[T, ...]: ... +@overload +def freeze(o: Set[T]) -> PSet[T]: ... # type: ignore +@overload +def freeze(o: T) -> T: ... + + +@overload +def thaw(o: PMap[KT, VT]) -> MutableMapping[KT, VT]: ... # type: ignore +@overload +def thaw(o: PVector[T]) -> List[T]: ... # type: ignore +@overload +def thaw(o: Tuple[T, ...]) -> Tuple[T, ...]: ... +# collections.abc.MutableSet is kind of garbage: +# https://stackoverflow.com/questions/24977898/why-does-collections-mutableset-not-bestow-an-update-method +@overload +def thaw(o: PSet[T]) -> Set[T]: ... # type: ignore +@overload +def thaw(o: T) -> T: ... + +def mutant(fn: Callable) -> Callable: ... + +def inc(x: int) -> int: ... +@overload +def discard(evolver: PMapEvolver[KT, VT], key: KT) -> None: ... +@overload +def discard(evolver: PVectorEvolver[T], key: int) -> None: ... +@overload +def discard(evolver: PSetEvolver[T], key: T) -> None: ... +def rex(expr: str) -> Callable[[Any], bool]: ... +def ny(_: Any) -> bool: ... + +def get_in(keys: Iterable, coll: Mapping, default: Optional[Any] = None, no_default: bool = False) -> Any: ... diff --git a/third_party/python/pyrsistent/pyrsistent/_checked_types.py b/third_party/python/pyrsistent/pyrsistent/_checked_types.py new file mode 100644 index 0000000000..293d989f13 --- /dev/null +++ b/third_party/python/pyrsistent/pyrsistent/_checked_types.py @@ -0,0 +1,542 @@ +from ._compat import Iterable +import six + +from pyrsistent._compat import Enum, string_types +from pyrsistent._pmap import PMap, pmap +from pyrsistent._pset import PSet, pset +from pyrsistent._pvector import PythonPVector, python_pvector + + +class CheckedType(object): + """ + Marker class to enable creation and serialization of checked object graphs. + """ + __slots__ = () + + @classmethod + def create(cls, source_data, _factory_fields=None): + raise NotImplementedError() + + def serialize(self, format=None): + raise NotImplementedError() + + +def _restore_pickle(cls, data): + return cls.create(data, _factory_fields=set()) + + +class InvariantException(Exception): + """ + Exception raised from a :py:class:`CheckedType` when invariant tests fail or when a mandatory + field is missing. + + Contains two fields of interest: + invariant_errors, a tuple of error data for the failing invariants + missing_fields, a tuple of strings specifying the missing names + """ + + def __init__(self, error_codes=(), missing_fields=(), *args, **kwargs): + self.invariant_errors = tuple(e() if callable(e) else e for e in error_codes) + self.missing_fields = missing_fields + super(InvariantException, self).__init__(*args, **kwargs) + + def __str__(self): + return super(InvariantException, self).__str__() + \ + ", invariant_errors=[{invariant_errors}], missing_fields=[{missing_fields}]".format( + invariant_errors=', '.join(str(e) for e in self.invariant_errors), + missing_fields=', '.join(self.missing_fields)) + + +_preserved_iterable_types = ( + Enum, +) +"""Some types are themselves iterable, but we want to use the type itself and +not its members for the type specification. This defines a set of such types +that we explicitly preserve. + +Note that strings are not such types because the string inputs we pass in are +values, not types. +""" + + +def maybe_parse_user_type(t): + """Try to coerce a user-supplied type directive into a list of types. + + This function should be used in all places where a user specifies a type, + for consistency. + + The policy for what defines valid user input should be clear from the implementation. + """ + is_type = isinstance(t, type) + is_preserved = isinstance(t, type) and issubclass(t, _preserved_iterable_types) + is_string = isinstance(t, string_types) + is_iterable = isinstance(t, Iterable) + + if is_preserved: + return [t] + elif is_string: + return [t] + elif is_type and not is_iterable: + return [t] + elif is_iterable: + # Recur to validate contained types as well. + ts = t + return tuple(e for t in ts for e in maybe_parse_user_type(t)) + else: + # If this raises because `t` cannot be formatted, so be it. + raise TypeError( + 'Type specifications must be types or strings. Input: {}'.format(t) + ) + + +def maybe_parse_many_user_types(ts): + # Just a different name to communicate that you're parsing multiple user + # inputs. `maybe_parse_user_type` handles the iterable case anyway. + return maybe_parse_user_type(ts) + + +def _store_types(dct, bases, destination_name, source_name): + maybe_types = maybe_parse_many_user_types([ + d[source_name] + for d in ([dct] + [b.__dict__ for b in bases]) if source_name in d + ]) + + dct[destination_name] = maybe_types + + +def _merge_invariant_results(result): + verdict = True + data = [] + for verd, dat in result: + if not verd: + verdict = False + data.append(dat) + + return verdict, tuple(data) + + +def wrap_invariant(invariant): + # Invariant functions may return the outcome of several tests + # In those cases the results have to be merged before being passed + # back to the client. + def f(*args, **kwargs): + result = invariant(*args, **kwargs) + if isinstance(result[0], bool): + return result + + return _merge_invariant_results(result) + + return f + + +def _all_dicts(bases, seen=None): + """ + Yield each class in ``bases`` and each of their base classes. + """ + if seen is None: + seen = set() + for cls in bases: + if cls in seen: + continue + seen.add(cls) + yield cls.__dict__ + for b in _all_dicts(cls.__bases__, seen): + yield b + + +def store_invariants(dct, bases, destination_name, source_name): + # Invariants are inherited + invariants = [] + for ns in [dct] + list(_all_dicts(bases)): + try: + invariant = ns[source_name] + except KeyError: + continue + invariants.append(invariant) + + if not all(callable(invariant) for invariant in invariants): + raise TypeError('Invariants must be callable') + dct[destination_name] = tuple(wrap_invariant(inv) for inv in invariants) + + +class _CheckedTypeMeta(type): + def __new__(mcs, name, bases, dct): + _store_types(dct, bases, '_checked_types', '__type__') + store_invariants(dct, bases, '_checked_invariants', '__invariant__') + + def default_serializer(self, _, value): + if isinstance(value, CheckedType): + return value.serialize() + return value + + dct.setdefault('__serializer__', default_serializer) + + dct['__slots__'] = () + + return super(_CheckedTypeMeta, mcs).__new__(mcs, name, bases, dct) + + +class CheckedTypeError(TypeError): + def __init__(self, source_class, expected_types, actual_type, actual_value, *args, **kwargs): + super(CheckedTypeError, self).__init__(*args, **kwargs) + self.source_class = source_class + self.expected_types = expected_types + self.actual_type = actual_type + self.actual_value = actual_value + + +class CheckedKeyTypeError(CheckedTypeError): + """ + Raised when trying to set a value using a key with a type that doesn't match the declared type. + + Attributes: + source_class -- The class of the collection + expected_types -- Allowed types + actual_type -- The non matching type + actual_value -- Value of the variable with the non matching type + """ + pass + + +class CheckedValueTypeError(CheckedTypeError): + """ + Raised when trying to set a value using a key with a type that doesn't match the declared type. + + Attributes: + source_class -- The class of the collection + expected_types -- Allowed types + actual_type -- The non matching type + actual_value -- Value of the variable with the non matching type + """ + pass + + +def _get_class(type_name): + module_name, class_name = type_name.rsplit('.', 1) + module = __import__(module_name, fromlist=[class_name]) + return getattr(module, class_name) + + +def get_type(typ): + if isinstance(typ, type): + return typ + + return _get_class(typ) + + +def get_types(typs): + return [get_type(typ) for typ in typs] + + +def _check_types(it, expected_types, source_class, exception_type=CheckedValueTypeError): + if expected_types: + for e in it: + if not any(isinstance(e, get_type(t)) for t in expected_types): + actual_type = type(e) + msg = "Type {source_class} can only be used with {expected_types}, not {actual_type}".format( + source_class=source_class.__name__, + expected_types=tuple(get_type(et).__name__ for et in expected_types), + actual_type=actual_type.__name__) + raise exception_type(source_class, expected_types, actual_type, e, msg) + + +def _invariant_errors(elem, invariants): + return [data for valid, data in (invariant(elem) for invariant in invariants) if not valid] + + +def _invariant_errors_iterable(it, invariants): + return sum([_invariant_errors(elem, invariants) for elem in it], []) + + +def optional(*typs): + """ Convenience function to specify that a value may be of any of the types in type 'typs' or None """ + return tuple(typs) + (type(None),) + + +def _checked_type_create(cls, source_data, _factory_fields=None, ignore_extra=False): + if isinstance(source_data, cls): + return source_data + + # Recursively apply create methods of checked types if the types of the supplied data + # does not match any of the valid types. + types = get_types(cls._checked_types) + checked_type = next((t for t in types if issubclass(t, CheckedType)), None) + if checked_type: + return cls([checked_type.create(data, ignore_extra=ignore_extra) + if not any(isinstance(data, t) for t in types) else data + for data in source_data]) + + return cls(source_data) + +@six.add_metaclass(_CheckedTypeMeta) +class CheckedPVector(PythonPVector, CheckedType): + """ + A CheckedPVector is a PVector which allows specifying type and invariant checks. + + >>> class Positives(CheckedPVector): + ... __type__ = (int, float) + ... __invariant__ = lambda n: (n >= 0, 'Negative') + ... + >>> Positives([1, 2, 3]) + Positives([1, 2, 3]) + """ + + __slots__ = () + + def __new__(cls, initial=()): + if type(initial) == PythonPVector: + return super(CheckedPVector, cls).__new__(cls, initial._count, initial._shift, initial._root, initial._tail) + + return CheckedPVector.Evolver(cls, python_pvector()).extend(initial).persistent() + + def set(self, key, value): + return self.evolver().set(key, value).persistent() + + def append(self, val): + return self.evolver().append(val).persistent() + + def extend(self, it): + return self.evolver().extend(it).persistent() + + create = classmethod(_checked_type_create) + + def serialize(self, format=None): + serializer = self.__serializer__ + return list(serializer(format, v) for v in self) + + def __reduce__(self): + # Pickling support + return _restore_pickle, (self.__class__, list(self),) + + class Evolver(PythonPVector.Evolver): + __slots__ = ('_destination_class', '_invariant_errors') + + def __init__(self, destination_class, vector): + super(CheckedPVector.Evolver, self).__init__(vector) + self._destination_class = destination_class + self._invariant_errors = [] + + def _check(self, it): + _check_types(it, self._destination_class._checked_types, self._destination_class) + error_data = _invariant_errors_iterable(it, self._destination_class._checked_invariants) + self._invariant_errors.extend(error_data) + + def __setitem__(self, key, value): + self._check([value]) + return super(CheckedPVector.Evolver, self).__setitem__(key, value) + + def append(self, elem): + self._check([elem]) + return super(CheckedPVector.Evolver, self).append(elem) + + def extend(self, it): + it = list(it) + self._check(it) + return super(CheckedPVector.Evolver, self).extend(it) + + def persistent(self): + if self._invariant_errors: + raise InvariantException(error_codes=self._invariant_errors) + + result = self._orig_pvector + if self.is_dirty() or (self._destination_class != type(self._orig_pvector)): + pv = super(CheckedPVector.Evolver, self).persistent().extend(self._extra_tail) + result = self._destination_class(pv) + self._reset(result) + + return result + + def __repr__(self): + return self.__class__.__name__ + "({0})".format(self.tolist()) + + __str__ = __repr__ + + def evolver(self): + return CheckedPVector.Evolver(self.__class__, self) + + +@six.add_metaclass(_CheckedTypeMeta) +class CheckedPSet(PSet, CheckedType): + """ + A CheckedPSet is a PSet which allows specifying type and invariant checks. + + >>> class Positives(CheckedPSet): + ... __type__ = (int, float) + ... __invariant__ = lambda n: (n >= 0, 'Negative') + ... + >>> Positives([1, 2, 3]) + Positives([1, 2, 3]) + """ + + __slots__ = () + + def __new__(cls, initial=()): + if type(initial) is PMap: + return super(CheckedPSet, cls).__new__(cls, initial) + + evolver = CheckedPSet.Evolver(cls, pset()) + for e in initial: + evolver.add(e) + + return evolver.persistent() + + def __repr__(self): + return self.__class__.__name__ + super(CheckedPSet, self).__repr__()[4:] + + def __str__(self): + return self.__repr__() + + def serialize(self, format=None): + serializer = self.__serializer__ + return set(serializer(format, v) for v in self) + + create = classmethod(_checked_type_create) + + def __reduce__(self): + # Pickling support + return _restore_pickle, (self.__class__, list(self),) + + def evolver(self): + return CheckedPSet.Evolver(self.__class__, self) + + class Evolver(PSet._Evolver): + __slots__ = ('_destination_class', '_invariant_errors') + + def __init__(self, destination_class, original_set): + super(CheckedPSet.Evolver, self).__init__(original_set) + self._destination_class = destination_class + self._invariant_errors = [] + + def _check(self, it): + _check_types(it, self._destination_class._checked_types, self._destination_class) + error_data = _invariant_errors_iterable(it, self._destination_class._checked_invariants) + self._invariant_errors.extend(error_data) + + def add(self, element): + self._check([element]) + self._pmap_evolver[element] = True + return self + + def persistent(self): + if self._invariant_errors: + raise InvariantException(error_codes=self._invariant_errors) + + if self.is_dirty() or self._destination_class != type(self._original_pset): + return self._destination_class(self._pmap_evolver.persistent()) + + return self._original_pset + + +class _CheckedMapTypeMeta(type): + def __new__(mcs, name, bases, dct): + _store_types(dct, bases, '_checked_key_types', '__key_type__') + _store_types(dct, bases, '_checked_value_types', '__value_type__') + store_invariants(dct, bases, '_checked_invariants', '__invariant__') + + def default_serializer(self, _, key, value): + sk = key + if isinstance(key, CheckedType): + sk = key.serialize() + + sv = value + if isinstance(value, CheckedType): + sv = value.serialize() + + return sk, sv + + dct.setdefault('__serializer__', default_serializer) + + dct['__slots__'] = () + + return super(_CheckedMapTypeMeta, mcs).__new__(mcs, name, bases, dct) + +# Marker object +_UNDEFINED_CHECKED_PMAP_SIZE = object() + + +@six.add_metaclass(_CheckedMapTypeMeta) +class CheckedPMap(PMap, CheckedType): + """ + A CheckedPMap is a PMap which allows specifying type and invariant checks. + + >>> class IntToFloatMap(CheckedPMap): + ... __key_type__ = int + ... __value_type__ = float + ... __invariant__ = lambda k, v: (int(v) == k, 'Invalid mapping') + ... + >>> IntToFloatMap({1: 1.5, 2: 2.25}) + IntToFloatMap({1: 1.5, 2: 2.25}) + """ + + __slots__ = () + + def __new__(cls, initial={}, size=_UNDEFINED_CHECKED_PMAP_SIZE): + if size is not _UNDEFINED_CHECKED_PMAP_SIZE: + return super(CheckedPMap, cls).__new__(cls, size, initial) + + evolver = CheckedPMap.Evolver(cls, pmap()) + for k, v in initial.items(): + evolver.set(k, v) + + return evolver.persistent() + + def evolver(self): + return CheckedPMap.Evolver(self.__class__, self) + + def __repr__(self): + return self.__class__.__name__ + "({0})".format(str(dict(self))) + + __str__ = __repr__ + + def serialize(self, format=None): + serializer = self.__serializer__ + return dict(serializer(format, k, v) for k, v in self.items()) + + @classmethod + def create(cls, source_data, _factory_fields=None): + if isinstance(source_data, cls): + return source_data + + # Recursively apply create methods of checked types if the types of the supplied data + # does not match any of the valid types. + key_types = get_types(cls._checked_key_types) + checked_key_type = next((t for t in key_types if issubclass(t, CheckedType)), None) + value_types = get_types(cls._checked_value_types) + checked_value_type = next((t for t in value_types if issubclass(t, CheckedType)), None) + + if checked_key_type or checked_value_type: + return cls(dict((checked_key_type.create(key) if checked_key_type and not any(isinstance(key, t) for t in key_types) else key, + checked_value_type.create(value) if checked_value_type and not any(isinstance(value, t) for t in value_types) else value) + for key, value in source_data.items())) + + return cls(source_data) + + def __reduce__(self): + # Pickling support + return _restore_pickle, (self.__class__, dict(self),) + + class Evolver(PMap._Evolver): + __slots__ = ('_destination_class', '_invariant_errors') + + def __init__(self, destination_class, original_map): + super(CheckedPMap.Evolver, self).__init__(original_map) + self._destination_class = destination_class + self._invariant_errors = [] + + def set(self, key, value): + _check_types([key], self._destination_class._checked_key_types, self._destination_class, CheckedKeyTypeError) + _check_types([value], self._destination_class._checked_value_types, self._destination_class) + self._invariant_errors.extend(data for valid, data in (invariant(key, value) + for invariant in self._destination_class._checked_invariants) + if not valid) + + return super(CheckedPMap.Evolver, self).set(key, value) + + def persistent(self): + if self._invariant_errors: + raise InvariantException(error_codes=self._invariant_errors) + + if self.is_dirty() or type(self._original_pmap) != self._destination_class: + return self._destination_class(self._buckets_evolver.persistent(), self._size) + + return self._original_pmap diff --git a/third_party/python/pyrsistent/pyrsistent/_compat.py b/third_party/python/pyrsistent/pyrsistent/_compat.py new file mode 100644 index 0000000000..e728586afe --- /dev/null +++ b/third_party/python/pyrsistent/pyrsistent/_compat.py @@ -0,0 +1,31 @@ +from six import string_types + + +# enum compat +try: + from enum import Enum +except: + class Enum(object): pass + # no objects will be instances of this class + +# collections compat +try: + from collections.abc import ( + Container, + Hashable, + Iterable, + Mapping, + Sequence, + Set, + Sized, + ) +except ImportError: + from collections import ( + Container, + Hashable, + Iterable, + Mapping, + Sequence, + Set, + Sized, + ) diff --git a/third_party/python/pyrsistent/pyrsistent/_field_common.py b/third_party/python/pyrsistent/pyrsistent/_field_common.py new file mode 100644 index 0000000000..ca1cccd43c --- /dev/null +++ b/third_party/python/pyrsistent/pyrsistent/_field_common.py @@ -0,0 +1,330 @@ +import six +import sys + +from pyrsistent._checked_types import ( + CheckedPMap, + CheckedPSet, + CheckedPVector, + CheckedType, + InvariantException, + _restore_pickle, + get_type, + maybe_parse_user_type, + maybe_parse_many_user_types, +) +from pyrsistent._checked_types import optional as optional_type +from pyrsistent._checked_types import wrap_invariant +import inspect + +PY2 = sys.version_info[0] < 3 + + +def set_fields(dct, bases, name): + dct[name] = dict(sum([list(b.__dict__.get(name, {}).items()) for b in bases], [])) + + for k, v in list(dct.items()): + if isinstance(v, _PField): + dct[name][k] = v + del dct[k] + + +def check_global_invariants(subject, invariants): + error_codes = tuple(error_code for is_ok, error_code in + (invariant(subject) for invariant in invariants) if not is_ok) + if error_codes: + raise InvariantException(error_codes, (), 'Global invariant failed') + + +def serialize(serializer, format, value): + if isinstance(value, CheckedType) and serializer is PFIELD_NO_SERIALIZER: + return value.serialize(format) + + return serializer(format, value) + + +def check_type(destination_cls, field, name, value): + if field.type and not any(isinstance(value, get_type(t)) for t in field.type): + actual_type = type(value) + message = "Invalid type for field {0}.{1}, was {2}".format(destination_cls.__name__, name, actual_type.__name__) + raise PTypeError(destination_cls, name, field.type, actual_type, message) + + +def is_type_cls(type_cls, field_type): + if type(field_type) is set: + return True + types = tuple(field_type) + if len(types) == 0: + return False + return issubclass(get_type(types[0]), type_cls) + + +def is_field_ignore_extra_complaint(type_cls, field, ignore_extra): + # ignore_extra param has default False value, for speed purpose no need to propagate False + if not ignore_extra: + return False + + if not is_type_cls(type_cls, field.type): + return False + + if PY2: + return 'ignore_extra' in inspect.getargspec(field.factory).args + else: + return 'ignore_extra' in inspect.signature(field.factory).parameters + + + +class _PField(object): + __slots__ = ('type', 'invariant', 'initial', 'mandatory', '_factory', 'serializer') + + def __init__(self, type, invariant, initial, mandatory, factory, serializer): + self.type = type + self.invariant = invariant + self.initial = initial + self.mandatory = mandatory + self._factory = factory + self.serializer = serializer + + @property + def factory(self): + # If no factory is specified and the type is another CheckedType use the factory method of that CheckedType + if self._factory is PFIELD_NO_FACTORY and len(self.type) == 1: + typ = get_type(tuple(self.type)[0]) + if issubclass(typ, CheckedType): + return typ.create + + return self._factory + +PFIELD_NO_TYPE = () +PFIELD_NO_INVARIANT = lambda _: (True, None) +PFIELD_NO_FACTORY = lambda x: x +PFIELD_NO_INITIAL = object() +PFIELD_NO_SERIALIZER = lambda _, value: value + + +def field(type=PFIELD_NO_TYPE, invariant=PFIELD_NO_INVARIANT, initial=PFIELD_NO_INITIAL, + mandatory=False, factory=PFIELD_NO_FACTORY, serializer=PFIELD_NO_SERIALIZER): + """ + Field specification factory for :py:class:`PRecord`. + + :param type: a type or iterable with types that are allowed for this field + :param invariant: a function specifying an invariant that must hold for the field + :param initial: value of field if not specified when instantiating the record + :param mandatory: boolean specifying if the field is mandatory or not + :param factory: function called when field is set. + :param serializer: function that returns a serialized version of the field + """ + + # NB: We have to check this predicate separately from the predicates in + # `maybe_parse_user_type` et al. because this one is related to supporting + # the argspec for `field`, while those are related to supporting the valid + # ways to specify types. + + # Multiple types must be passed in one of the following containers. Note + # that a type that is a subclass of one of these containers, like a + # `collections.namedtuple`, will work as expected, since we check + # `isinstance` and not `issubclass`. + if isinstance(type, (list, set, tuple)): + types = set(maybe_parse_many_user_types(type)) + else: + types = set(maybe_parse_user_type(type)) + + invariant_function = wrap_invariant(invariant) if invariant != PFIELD_NO_INVARIANT and callable(invariant) else invariant + field = _PField(type=types, invariant=invariant_function, initial=initial, + mandatory=mandatory, factory=factory, serializer=serializer) + + _check_field_parameters(field) + + return field + + +def _check_field_parameters(field): + for t in field.type: + if not isinstance(t, type) and not isinstance(t, six.string_types): + raise TypeError('Type parameter expected, not {0}'.format(type(t))) + + if field.initial is not PFIELD_NO_INITIAL and \ + not callable(field.initial) and \ + field.type and not any(isinstance(field.initial, t) for t in field.type): + raise TypeError('Initial has invalid type {0}'.format(type(field.initial))) + + if not callable(field.invariant): + raise TypeError('Invariant must be callable') + + if not callable(field.factory): + raise TypeError('Factory must be callable') + + if not callable(field.serializer): + raise TypeError('Serializer must be callable') + + +class PTypeError(TypeError): + """ + Raised when trying to assign a value with a type that doesn't match the declared type. + + Attributes: + source_class -- The class of the record + field -- Field name + expected_types -- Types allowed for the field + actual_type -- The non matching type + """ + def __init__(self, source_class, field, expected_types, actual_type, *args, **kwargs): + super(PTypeError, self).__init__(*args, **kwargs) + self.source_class = source_class + self.field = field + self.expected_types = expected_types + self.actual_type = actual_type + + +SEQ_FIELD_TYPE_SUFFIXES = { + CheckedPVector: "PVector", + CheckedPSet: "PSet", +} + +# Global dictionary to hold auto-generated field types: used for unpickling +_seq_field_types = {} + +def _restore_seq_field_pickle(checked_class, item_type, data): + """Unpickling function for auto-generated PVec/PSet field types.""" + type_ = _seq_field_types[checked_class, item_type] + return _restore_pickle(type_, data) + +def _types_to_names(types): + """Convert a tuple of types to a human-readable string.""" + return "".join(get_type(typ).__name__.capitalize() for typ in types) + +def _make_seq_field_type(checked_class, item_type): + """Create a subclass of the given checked class with the given item type.""" + type_ = _seq_field_types.get((checked_class, item_type)) + if type_ is not None: + return type_ + + class TheType(checked_class): + __type__ = item_type + + def __reduce__(self): + return (_restore_seq_field_pickle, + (checked_class, item_type, list(self))) + + suffix = SEQ_FIELD_TYPE_SUFFIXES[checked_class] + TheType.__name__ = _types_to_names(TheType._checked_types) + suffix + _seq_field_types[checked_class, item_type] = TheType + return TheType + +def _sequence_field(checked_class, item_type, optional, initial): + """ + Create checked field for either ``PSet`` or ``PVector``. + + :param checked_class: ``CheckedPSet`` or ``CheckedPVector``. + :param item_type: The required type for the items in the set. + :param optional: If true, ``None`` can be used as a value for + this field. + :param initial: Initial value to pass to factory. + + :return: A ``field`` containing a checked class. + """ + TheType = _make_seq_field_type(checked_class, item_type) + + if optional: + def factory(argument, _factory_fields=None, ignore_extra=False): + if argument is None: + return None + else: + return TheType.create(argument, _factory_fields=_factory_fields, ignore_extra=ignore_extra) + else: + factory = TheType.create + + return field(type=optional_type(TheType) if optional else TheType, + factory=factory, mandatory=True, + initial=factory(initial)) + + +def pset_field(item_type, optional=False, initial=()): + """ + Create checked ``PSet`` field. + + :param item_type: The required type for the items in the set. + :param optional: If true, ``None`` can be used as a value for + this field. + :param initial: Initial value to pass to factory if no value is given + for the field. + + :return: A ``field`` containing a ``CheckedPSet`` of the given type. + """ + return _sequence_field(CheckedPSet, item_type, optional, + initial) + + +def pvector_field(item_type, optional=False, initial=()): + """ + Create checked ``PVector`` field. + + :param item_type: The required type for the items in the vector. + :param optional: If true, ``None`` can be used as a value for + this field. + :param initial: Initial value to pass to factory if no value is given + for the field. + + :return: A ``field`` containing a ``CheckedPVector`` of the given type. + """ + return _sequence_field(CheckedPVector, item_type, optional, + initial) + + +_valid = lambda item: (True, "") + + +# Global dictionary to hold auto-generated field types: used for unpickling +_pmap_field_types = {} + +def _restore_pmap_field_pickle(key_type, value_type, data): + """Unpickling function for auto-generated PMap field types.""" + type_ = _pmap_field_types[key_type, value_type] + return _restore_pickle(type_, data) + +def _make_pmap_field_type(key_type, value_type): + """Create a subclass of CheckedPMap with the given key and value types.""" + type_ = _pmap_field_types.get((key_type, value_type)) + if type_ is not None: + return type_ + + class TheMap(CheckedPMap): + __key_type__ = key_type + __value_type__ = value_type + + def __reduce__(self): + return (_restore_pmap_field_pickle, + (self.__key_type__, self.__value_type__, dict(self))) + + TheMap.__name__ = "{0}To{1}PMap".format( + _types_to_names(TheMap._checked_key_types), + _types_to_names(TheMap._checked_value_types)) + _pmap_field_types[key_type, value_type] = TheMap + return TheMap + + +def pmap_field(key_type, value_type, optional=False, invariant=PFIELD_NO_INVARIANT): + """ + Create a checked ``PMap`` field. + + :param key: The required type for the keys of the map. + :param value: The required type for the values of the map. + :param optional: If true, ``None`` can be used as a value for + this field. + :param invariant: Pass-through to ``field``. + + :return: A ``field`` containing a ``CheckedPMap``. + """ + TheMap = _make_pmap_field_type(key_type, value_type) + + if optional: + def factory(argument): + if argument is None: + return None + else: + return TheMap.create(argument) + else: + factory = TheMap.create + + return field(mandatory=True, initial=TheMap(), + type=optional_type(TheMap) if optional else TheMap, + factory=factory, invariant=invariant) diff --git a/third_party/python/pyrsistent/pyrsistent/_helpers.py b/third_party/python/pyrsistent/pyrsistent/_helpers.py new file mode 100644 index 0000000000..c9c58feac5 --- /dev/null +++ b/third_party/python/pyrsistent/pyrsistent/_helpers.py @@ -0,0 +1,82 @@ +from functools import wraps +import six +from pyrsistent._pmap import PMap, pmap +from pyrsistent._pset import PSet, pset +from pyrsistent._pvector import PVector, pvector + + +def freeze(o): + """ + Recursively convert simple Python containers into pyrsistent versions + of those containers. + + - list is converted to pvector, recursively + - dict is converted to pmap, recursively on values (but not keys) + - set is converted to pset, but not recursively + - tuple is converted to tuple, recursively. + + Sets and dict keys are not recursively frozen because they do not contain + mutable data by convention. The main exception to this rule is that + dict keys and set elements are often instances of mutable objects that + support hash-by-id, which this function can't convert anyway. + + >>> freeze(set([1, 2])) + pset([1, 2]) + >>> freeze([1, {'a': 3}]) + pvector([1, pmap({'a': 3})]) + >>> freeze((1, [])) + (1, pvector([])) + """ + typ = type(o) + if typ is dict: + return pmap(dict((k, freeze(v)) for k, v in six.iteritems(o))) + if typ is list: + return pvector(map(freeze, o)) + if typ is tuple: + return tuple(map(freeze, o)) + if typ is set: + return pset(o) + return o + + +def thaw(o): + """ + Recursively convert pyrsistent containers into simple Python containers. + + - pvector is converted to list, recursively + - pmap is converted to dict, recursively on values (but not keys) + - pset is converted to set, but not recursively + - tuple is converted to tuple, recursively. + + >>> from pyrsistent import s, m, v + >>> thaw(s(1, 2)) + {1, 2} + >>> thaw(v(1, m(a=3))) + [1, {'a': 3}] + >>> thaw((1, v())) + (1, []) + """ + if isinstance(o, PVector): + return list(map(thaw, o)) + if isinstance(o, PMap): + return dict((k, thaw(v)) for k, v in o.iteritems()) + if isinstance(o, PSet): + return set(o) + if type(o) is tuple: + return tuple(map(thaw, o)) + return o + + +def mutant(fn): + """ + Convenience decorator to isolate mutation to within the decorated function (with respect + to the input arguments). + + All arguments to the decorated function will be frozen so that they are guaranteed not to change. + The return value is also frozen. + """ + @wraps(fn) + def inner_f(*args, **kwargs): + return freeze(fn(*[freeze(e) for e in args], **dict(freeze(item) for item in kwargs.items()))) + + return inner_f diff --git a/third_party/python/pyrsistent/pyrsistent/_immutable.py b/third_party/python/pyrsistent/pyrsistent/_immutable.py new file mode 100644 index 0000000000..a89bd7552f --- /dev/null +++ b/third_party/python/pyrsistent/pyrsistent/_immutable.py @@ -0,0 +1,105 @@ +import sys + +import six + + +def immutable(members='', name='Immutable', verbose=False): + """ + Produces a class that either can be used standalone or as a base class for persistent classes. + + This is a thin wrapper around a named tuple. + + Constructing a type and using it to instantiate objects: + + >>> Point = immutable('x, y', name='Point') + >>> p = Point(1, 2) + >>> p2 = p.set(x=3) + >>> p + Point(x=1, y=2) + >>> p2 + Point(x=3, y=2) + + Inheriting from a constructed type. In this case no type name needs to be supplied: + + >>> class PositivePoint(immutable('x, y')): + ... __slots__ = tuple() + ... def __new__(cls, x, y): + ... if x > 0 and y > 0: + ... return super(PositivePoint, cls).__new__(cls, x, y) + ... raise Exception('Coordinates must be positive!') + ... + >>> p = PositivePoint(1, 2) + >>> p.set(x=3) + PositivePoint(x=3, y=2) + >>> p.set(y=-3) + Traceback (most recent call last): + Exception: Coordinates must be positive! + + The persistent class also supports the notion of frozen members. The value of a frozen member + cannot be updated. For example it could be used to implement an ID that should remain the same + over time. A frozen member is denoted by a trailing underscore. + + >>> Point = immutable('x, y, id_', name='Point') + >>> p = Point(1, 2, id_=17) + >>> p.set(x=3) + Point(x=3, y=2, id_=17) + >>> p.set(id_=18) + Traceback (most recent call last): + AttributeError: Cannot set frozen members id_ + """ + + if isinstance(members, six.string_types): + members = members.replace(',', ' ').split() + + def frozen_member_test(): + frozen_members = ["'%s'" % f for f in members if f.endswith('_')] + if frozen_members: + return """ + frozen_fields = fields_to_modify & set([{frozen_members}]) + if frozen_fields: + raise AttributeError('Cannot set frozen members %s' % ', '.join(frozen_fields)) + """.format(frozen_members=', '.join(frozen_members)) + + return '' + + verbose_string = "" + if sys.version_info < (3, 7): + # Verbose is no longer supported in Python 3.7 + verbose_string = ", verbose={verbose}".format(verbose=verbose) + + quoted_members = ', '.join("'%s'" % m for m in members) + template = """ +class {class_name}(namedtuple('ImmutableBase', [{quoted_members}]{verbose_string})): + __slots__ = tuple() + + def __repr__(self): + return super({class_name}, self).__repr__().replace('ImmutableBase', self.__class__.__name__) + + def set(self, **kwargs): + if not kwargs: + return self + + fields_to_modify = set(kwargs.keys()) + if not fields_to_modify <= {member_set}: + raise AttributeError("'%s' is not a member" % ', '.join(fields_to_modify - {member_set})) + + {frozen_member_test} + + return self.__class__.__new__(self.__class__, *map(kwargs.pop, [{quoted_members}], self)) +""".format(quoted_members=quoted_members, + member_set="set([%s])" % quoted_members if quoted_members else 'set()', + frozen_member_test=frozen_member_test(), + verbose_string=verbose_string, + class_name=name) + + if verbose: + print(template) + + from collections import namedtuple + namespace = dict(namedtuple=namedtuple, __name__='pyrsistent_immutable') + try: + six.exec_(template, namespace) + except SyntaxError as e: + raise SyntaxError(e.message + ':\n' + template) + + return namespace[name]
\ No newline at end of file diff --git a/third_party/python/pyrsistent/pyrsistent/_pbag.py b/third_party/python/pyrsistent/pyrsistent/_pbag.py new file mode 100644 index 0000000000..9905e9a6e3 --- /dev/null +++ b/third_party/python/pyrsistent/pyrsistent/_pbag.py @@ -0,0 +1,267 @@ +from ._compat import Container, Iterable, Sized, Hashable +from functools import reduce +from pyrsistent._pmap import pmap + + +def _add_to_counters(counters, element): + return counters.set(element, counters.get(element, 0) + 1) + + +class PBag(object): + """ + A persistent bag/multiset type. + + Requires elements to be hashable, and allows duplicates, but has no + ordering. Bags are hashable. + + Do not instantiate directly, instead use the factory functions :py:func:`b` + or :py:func:`pbag` to create an instance. + + Some examples: + + >>> s = pbag([1, 2, 3, 1]) + >>> s2 = s.add(4) + >>> s3 = s2.remove(1) + >>> s + pbag([1, 1, 2, 3]) + >>> s2 + pbag([1, 1, 2, 3, 4]) + >>> s3 + pbag([1, 2, 3, 4]) + """ + + __slots__ = ('_counts', '__weakref__') + + def __init__(self, counts): + self._counts = counts + + def add(self, element): + """ + Add an element to the bag. + + >>> s = pbag([1]) + >>> s2 = s.add(1) + >>> s3 = s.add(2) + >>> s2 + pbag([1, 1]) + >>> s3 + pbag([1, 2]) + """ + return PBag(_add_to_counters(self._counts, element)) + + def update(self, iterable): + """ + Update bag with all elements in iterable. + + >>> s = pbag([1]) + >>> s.update([1, 2]) + pbag([1, 1, 2]) + """ + if iterable: + return PBag(reduce(_add_to_counters, iterable, self._counts)) + + return self + + def remove(self, element): + """ + Remove an element from the bag. + + >>> s = pbag([1, 1, 2]) + >>> s2 = s.remove(1) + >>> s3 = s.remove(2) + >>> s2 + pbag([1, 2]) + >>> s3 + pbag([1, 1]) + """ + if element not in self._counts: + raise KeyError(element) + elif self._counts[element] == 1: + newc = self._counts.remove(element) + else: + newc = self._counts.set(element, self._counts[element] - 1) + return PBag(newc) + + def count(self, element): + """ + Return the number of times an element appears. + + + >>> pbag([]).count('non-existent') + 0 + >>> pbag([1, 1, 2]).count(1) + 2 + """ + return self._counts.get(element, 0) + + def __len__(self): + """ + Return the length including duplicates. + + >>> len(pbag([1, 1, 2])) + 3 + """ + return sum(self._counts.itervalues()) + + def __iter__(self): + """ + Return an iterator of all elements, including duplicates. + + >>> list(pbag([1, 1, 2])) + [1, 1, 2] + >>> list(pbag([1, 2])) + [1, 2] + """ + for elt, count in self._counts.iteritems(): + for i in range(count): + yield elt + + def __contains__(self, elt): + """ + Check if an element is in the bag. + + >>> 1 in pbag([1, 1, 2]) + True + >>> 0 in pbag([1, 2]) + False + """ + return elt in self._counts + + def __repr__(self): + return "pbag({0})".format(list(self)) + + def __eq__(self, other): + """ + Check if two bags are equivalent, honoring the number of duplicates, + and ignoring insertion order. + + >>> pbag([1, 1, 2]) == pbag([1, 2]) + False + >>> pbag([2, 1, 0]) == pbag([0, 1, 2]) + True + """ + if type(other) is not PBag: + raise TypeError("Can only compare PBag with PBags") + return self._counts == other._counts + + def __lt__(self, other): + raise TypeError('PBags are not orderable') + + __le__ = __lt__ + __gt__ = __lt__ + __ge__ = __lt__ + + # Multiset-style operations similar to collections.Counter + + def __add__(self, other): + """ + Combine elements from two PBags. + + >>> pbag([1, 2, 2]) + pbag([2, 3, 3]) + pbag([1, 2, 2, 2, 3, 3]) + """ + if not isinstance(other, PBag): + return NotImplemented + result = self._counts.evolver() + for elem, other_count in other._counts.iteritems(): + result[elem] = self.count(elem) + other_count + return PBag(result.persistent()) + + def __sub__(self, other): + """ + Remove elements from one PBag that are present in another. + + >>> pbag([1, 2, 2, 2, 3]) - pbag([2, 3, 3, 4]) + pbag([1, 2, 2]) + """ + if not isinstance(other, PBag): + return NotImplemented + result = self._counts.evolver() + for elem, other_count in other._counts.iteritems(): + newcount = self.count(elem) - other_count + if newcount > 0: + result[elem] = newcount + elif elem in self: + result.remove(elem) + return PBag(result.persistent()) + + def __or__(self, other): + """ + Union: Keep elements that are present in either of two PBags. + + >>> pbag([1, 2, 2, 2]) | pbag([2, 3, 3]) + pbag([1, 2, 2, 2, 3, 3]) + """ + if not isinstance(other, PBag): + return NotImplemented + result = self._counts.evolver() + for elem, other_count in other._counts.iteritems(): + count = self.count(elem) + newcount = max(count, other_count) + result[elem] = newcount + return PBag(result.persistent()) + + def __and__(self, other): + """ + Intersection: Only keep elements that are present in both PBags. + + >>> pbag([1, 2, 2, 2]) & pbag([2, 3, 3]) + pbag([2]) + """ + if not isinstance(other, PBag): + return NotImplemented + result = pmap().evolver() + for elem, count in self._counts.iteritems(): + newcount = min(count, other.count(elem)) + if newcount > 0: + result[elem] = newcount + return PBag(result.persistent()) + + def __hash__(self): + """ + Hash based on value of elements. + + >>> m = pmap({pbag([1, 2]): "it's here!"}) + >>> m[pbag([2, 1])] + "it's here!" + >>> pbag([1, 1, 2]) in m + False + """ + return hash(self._counts) + + +Container.register(PBag) +Iterable.register(PBag) +Sized.register(PBag) +Hashable.register(PBag) + + +def b(*elements): + """ + Construct a persistent bag. + + Takes an arbitrary number of arguments to insert into the new persistent + bag. + + >>> b(1, 2, 3, 2) + pbag([1, 2, 2, 3]) + """ + return pbag(elements) + + +def pbag(elements): + """ + Convert an iterable to a persistent bag. + + Takes an iterable with elements to insert. + + >>> pbag([1, 2, 3, 2]) + pbag([1, 2, 2, 3]) + """ + if not elements: + return _EMPTY_PBAG + return PBag(reduce(_add_to_counters, elements, pmap())) + + +_EMPTY_PBAG = PBag(pmap()) + diff --git a/third_party/python/pyrsistent/pyrsistent/_pclass.py b/third_party/python/pyrsistent/pyrsistent/_pclass.py new file mode 100644 index 0000000000..a437f71648 --- /dev/null +++ b/third_party/python/pyrsistent/pyrsistent/_pclass.py @@ -0,0 +1,264 @@ +import six +from pyrsistent._checked_types import (InvariantException, CheckedType, _restore_pickle, store_invariants) +from pyrsistent._field_common import ( + set_fields, check_type, is_field_ignore_extra_complaint, PFIELD_NO_INITIAL, serialize, check_global_invariants +) +from pyrsistent._transformations import transform + + +def _is_pclass(bases): + return len(bases) == 1 and bases[0] == CheckedType + + +class PClassMeta(type): + def __new__(mcs, name, bases, dct): + set_fields(dct, bases, name='_pclass_fields') + store_invariants(dct, bases, '_pclass_invariants', '__invariant__') + dct['__slots__'] = ('_pclass_frozen',) + tuple(key for key in dct['_pclass_fields']) + + # There must only be one __weakref__ entry in the inheritance hierarchy, + # lets put it on the top level class. + if _is_pclass(bases): + dct['__slots__'] += ('__weakref__',) + + return super(PClassMeta, mcs).__new__(mcs, name, bases, dct) + +_MISSING_VALUE = object() + + +def _check_and_set_attr(cls, field, name, value, result, invariant_errors): + check_type(cls, field, name, value) + is_ok, error_code = field.invariant(value) + if not is_ok: + invariant_errors.append(error_code) + else: + setattr(result, name, value) + + +@six.add_metaclass(PClassMeta) +class PClass(CheckedType): + """ + A PClass is a python class with a fixed set of specified fields. PClasses are declared as python classes inheriting + from PClass. It is defined the same way that PRecords are and behaves like a PRecord in all aspects except that it + is not a PMap and hence not a collection but rather a plain Python object. + + + More documentation and examples of PClass usage is available at https://github.com/tobgu/pyrsistent + """ + def __new__(cls, **kwargs): # Support *args? + result = super(PClass, cls).__new__(cls) + factory_fields = kwargs.pop('_factory_fields', None) + ignore_extra = kwargs.pop('ignore_extra', None) + missing_fields = [] + invariant_errors = [] + for name, field in cls._pclass_fields.items(): + if name in kwargs: + if factory_fields is None or name in factory_fields: + if is_field_ignore_extra_complaint(PClass, field, ignore_extra): + value = field.factory(kwargs[name], ignore_extra=ignore_extra) + else: + value = field.factory(kwargs[name]) + else: + value = kwargs[name] + _check_and_set_attr(cls, field, name, value, result, invariant_errors) + del kwargs[name] + elif field.initial is not PFIELD_NO_INITIAL: + initial = field.initial() if callable(field.initial) else field.initial + _check_and_set_attr( + cls, field, name, initial, result, invariant_errors) + elif field.mandatory: + missing_fields.append('{0}.{1}'.format(cls.__name__, name)) + + if invariant_errors or missing_fields: + raise InvariantException(tuple(invariant_errors), tuple(missing_fields), 'Field invariant failed') + + if kwargs: + raise AttributeError("'{0}' are not among the specified fields for {1}".format( + ', '.join(kwargs), cls.__name__)) + + check_global_invariants(result, cls._pclass_invariants) + + result._pclass_frozen = True + return result + + def set(self, *args, **kwargs): + """ + Set a field in the instance. Returns a new instance with the updated value. The original instance remains + unmodified. Accepts key-value pairs or single string representing the field name and a value. + + >>> from pyrsistent import PClass, field + >>> class AClass(PClass): + ... x = field() + ... + >>> a = AClass(x=1) + >>> a2 = a.set(x=2) + >>> a3 = a.set('x', 3) + >>> a + AClass(x=1) + >>> a2 + AClass(x=2) + >>> a3 + AClass(x=3) + """ + if args: + kwargs[args[0]] = args[1] + + factory_fields = set(kwargs) + + for key in self._pclass_fields: + if key not in kwargs: + value = getattr(self, key, _MISSING_VALUE) + if value is not _MISSING_VALUE: + kwargs[key] = value + + return self.__class__(_factory_fields=factory_fields, **kwargs) + + @classmethod + def create(cls, kwargs, _factory_fields=None, ignore_extra=False): + """ + Factory method. Will create a new PClass of the current type and assign the values + specified in kwargs. + + :param ignore_extra: A boolean which when set to True will ignore any keys which appear in kwargs that are not + in the set of fields on the PClass. + """ + if isinstance(kwargs, cls): + return kwargs + + if ignore_extra: + kwargs = {k: kwargs[k] for k in cls._pclass_fields if k in kwargs} + + return cls(_factory_fields=_factory_fields, ignore_extra=ignore_extra, **kwargs) + + def serialize(self, format=None): + """ + Serialize the current PClass using custom serializer functions for fields where + such have been supplied. + """ + result = {} + for name in self._pclass_fields: + value = getattr(self, name, _MISSING_VALUE) + if value is not _MISSING_VALUE: + result[name] = serialize(self._pclass_fields[name].serializer, format, value) + + return result + + def transform(self, *transformations): + """ + Apply transformations to the currency PClass. For more details on transformations see + the documentation for PMap. Transformations on PClasses do not support key matching + since the PClass is not a collection. Apart from that the transformations available + for other persistent types work as expected. + """ + return transform(self, transformations) + + def __eq__(self, other): + if isinstance(other, self.__class__): + for name in self._pclass_fields: + if getattr(self, name, _MISSING_VALUE) != getattr(other, name, _MISSING_VALUE): + return False + + return True + + return NotImplemented + + def __ne__(self, other): + return not self == other + + def __hash__(self): + # May want to optimize this by caching the hash somehow + return hash(tuple((key, getattr(self, key, _MISSING_VALUE)) for key in self._pclass_fields)) + + def __setattr__(self, key, value): + if getattr(self, '_pclass_frozen', False): + raise AttributeError("Can't set attribute, key={0}, value={1}".format(key, value)) + + super(PClass, self).__setattr__(key, value) + + def __delattr__(self, key): + raise AttributeError("Can't delete attribute, key={0}, use remove()".format(key)) + + def _to_dict(self): + result = {} + for key in self._pclass_fields: + value = getattr(self, key, _MISSING_VALUE) + if value is not _MISSING_VALUE: + result[key] = value + + return result + + def __repr__(self): + return "{0}({1})".format(self.__class__.__name__, + ', '.join('{0}={1}'.format(k, repr(v)) for k, v in self._to_dict().items())) + + def __reduce__(self): + # Pickling support + data = dict((key, getattr(self, key)) for key in self._pclass_fields if hasattr(self, key)) + return _restore_pickle, (self.__class__, data,) + + def evolver(self): + """ + Returns an evolver for this object. + """ + return _PClassEvolver(self, self._to_dict()) + + def remove(self, name): + """ + Remove attribute given by name from the current instance. Raises AttributeError if the + attribute doesn't exist. + """ + evolver = self.evolver() + del evolver[name] + return evolver.persistent() + + +class _PClassEvolver(object): + __slots__ = ('_pclass_evolver_original', '_pclass_evolver_data', '_pclass_evolver_data_is_dirty', '_factory_fields') + + def __init__(self, original, initial_dict): + self._pclass_evolver_original = original + self._pclass_evolver_data = initial_dict + self._pclass_evolver_data_is_dirty = False + self._factory_fields = set() + + def __getitem__(self, item): + return self._pclass_evolver_data[item] + + def set(self, key, value): + if self._pclass_evolver_data.get(key, _MISSING_VALUE) is not value: + self._pclass_evolver_data[key] = value + self._factory_fields.add(key) + self._pclass_evolver_data_is_dirty = True + + return self + + def __setitem__(self, key, value): + self.set(key, value) + + def remove(self, item): + if item in self._pclass_evolver_data: + del self._pclass_evolver_data[item] + self._factory_fields.discard(item) + self._pclass_evolver_data_is_dirty = True + return self + + raise AttributeError(item) + + def __delitem__(self, item): + self.remove(item) + + def persistent(self): + if self._pclass_evolver_data_is_dirty: + return self._pclass_evolver_original.__class__(_factory_fields=self._factory_fields, + **self._pclass_evolver_data) + + return self._pclass_evolver_original + + def __setattr__(self, key, value): + if key not in self.__slots__: + self.set(key, value) + else: + super(_PClassEvolver, self).__setattr__(key, value) + + def __getattr__(self, item): + return self[item] diff --git a/third_party/python/pyrsistent/pyrsistent/_pdeque.py b/third_party/python/pyrsistent/pyrsistent/_pdeque.py new file mode 100644 index 0000000000..5147b3fa6a --- /dev/null +++ b/third_party/python/pyrsistent/pyrsistent/_pdeque.py @@ -0,0 +1,376 @@ +from ._compat import Sequence, Hashable +from itertools import islice, chain +from numbers import Integral +from pyrsistent._plist import plist + + +class PDeque(object): + """ + Persistent double ended queue (deque). Allows quick appends and pops in both ends. Implemented + using two persistent lists. + + A maximum length can be specified to create a bounded queue. + + Fully supports the Sequence and Hashable protocols including indexing and slicing but + if you need fast random access go for the PVector instead. + + Do not instantiate directly, instead use the factory functions :py:func:`dq` or :py:func:`pdeque` to + create an instance. + + Some examples: + + >>> x = pdeque([1, 2, 3]) + >>> x.left + 1 + >>> x.right + 3 + >>> x[0] == x.left + True + >>> x[-1] == x.right + True + >>> x.pop() + pdeque([1, 2]) + >>> x.pop() == x[:-1] + True + >>> x.popleft() + pdeque([2, 3]) + >>> x.append(4) + pdeque([1, 2, 3, 4]) + >>> x.appendleft(4) + pdeque([4, 1, 2, 3]) + + >>> y = pdeque([1, 2, 3], maxlen=3) + >>> y.append(4) + pdeque([2, 3, 4], maxlen=3) + >>> y.appendleft(4) + pdeque([4, 1, 2], maxlen=3) + """ + __slots__ = ('_left_list', '_right_list', '_length', '_maxlen', '__weakref__') + + def __new__(cls, left_list, right_list, length, maxlen=None): + instance = super(PDeque, cls).__new__(cls) + instance._left_list = left_list + instance._right_list = right_list + instance._length = length + + if maxlen is not None: + if not isinstance(maxlen, Integral): + raise TypeError('An integer is required as maxlen') + + if maxlen < 0: + raise ValueError("maxlen must be non-negative") + + instance._maxlen = maxlen + return instance + + @property + def right(self): + """ + Rightmost element in dqueue. + """ + return PDeque._tip_from_lists(self._right_list, self._left_list) + + @property + def left(self): + """ + Leftmost element in dqueue. + """ + return PDeque._tip_from_lists(self._left_list, self._right_list) + + @staticmethod + def _tip_from_lists(primary_list, secondary_list): + if primary_list: + return primary_list.first + + if secondary_list: + return secondary_list[-1] + + raise IndexError('No elements in empty deque') + + def __iter__(self): + return chain(self._left_list, self._right_list.reverse()) + + def __repr__(self): + return "pdeque({0}{1})".format(list(self), + ', maxlen={0}'.format(self._maxlen) if self._maxlen is not None else '') + __str__ = __repr__ + + @property + def maxlen(self): + """ + Maximum length of the queue. + """ + return self._maxlen + + def pop(self, count=1): + """ + Return new deque with rightmost element removed. Popping the empty queue + will return the empty queue. A optional count can be given to indicate the + number of elements to pop. Popping with a negative index is the same as + popleft. Executes in amortized O(k) where k is the number of elements to pop. + + >>> pdeque([1, 2]).pop() + pdeque([1]) + >>> pdeque([1, 2]).pop(2) + pdeque([]) + >>> pdeque([1, 2]).pop(-1) + pdeque([2]) + """ + if count < 0: + return self.popleft(-count) + + new_right_list, new_left_list = PDeque._pop_lists(self._right_list, self._left_list, count) + return PDeque(new_left_list, new_right_list, max(self._length - count, 0), self._maxlen) + + def popleft(self, count=1): + """ + Return new deque with leftmost element removed. Otherwise functionally + equivalent to pop(). + + >>> pdeque([1, 2]).popleft() + pdeque([2]) + """ + if count < 0: + return self.pop(-count) + + new_left_list, new_right_list = PDeque._pop_lists(self._left_list, self._right_list, count) + return PDeque(new_left_list, new_right_list, max(self._length - count, 0), self._maxlen) + + @staticmethod + def _pop_lists(primary_list, secondary_list, count): + new_primary_list = primary_list + new_secondary_list = secondary_list + + while count > 0 and (new_primary_list or new_secondary_list): + count -= 1 + if new_primary_list.rest: + new_primary_list = new_primary_list.rest + elif new_primary_list: + new_primary_list = new_secondary_list.reverse() + new_secondary_list = plist() + else: + new_primary_list = new_secondary_list.reverse().rest + new_secondary_list = plist() + + return new_primary_list, new_secondary_list + + def _is_empty(self): + return not self._left_list and not self._right_list + + def __lt__(self, other): + if not isinstance(other, PDeque): + return NotImplemented + + return tuple(self) < tuple(other) + + def __eq__(self, other): + if not isinstance(other, PDeque): + return NotImplemented + + if tuple(self) == tuple(other): + # Sanity check of the length value since it is redundant (there for performance) + assert len(self) == len(other) + return True + + return False + + def __hash__(self): + return hash(tuple(self)) + + def __len__(self): + return self._length + + def append(self, elem): + """ + Return new deque with elem as the rightmost element. + + >>> pdeque([1, 2]).append(3) + pdeque([1, 2, 3]) + """ + new_left_list, new_right_list, new_length = self._append(self._left_list, self._right_list, elem) + return PDeque(new_left_list, new_right_list, new_length, self._maxlen) + + def appendleft(self, elem): + """ + Return new deque with elem as the leftmost element. + + >>> pdeque([1, 2]).appendleft(3) + pdeque([3, 1, 2]) + """ + new_right_list, new_left_list, new_length = self._append(self._right_list, self._left_list, elem) + return PDeque(new_left_list, new_right_list, new_length, self._maxlen) + + def _append(self, primary_list, secondary_list, elem): + if self._maxlen is not None and self._length == self._maxlen: + if self._maxlen == 0: + return primary_list, secondary_list, 0 + new_primary_list, new_secondary_list = PDeque._pop_lists(primary_list, secondary_list, 1) + return new_primary_list, new_secondary_list.cons(elem), self._length + + return primary_list, secondary_list.cons(elem), self._length + 1 + + @staticmethod + def _extend_list(the_list, iterable): + count = 0 + for elem in iterable: + the_list = the_list.cons(elem) + count += 1 + + return the_list, count + + def _extend(self, primary_list, secondary_list, iterable): + new_primary_list, extend_count = PDeque._extend_list(primary_list, iterable) + new_secondary_list = secondary_list + current_len = self._length + extend_count + if self._maxlen is not None and current_len > self._maxlen: + pop_len = current_len - self._maxlen + new_secondary_list, new_primary_list = PDeque._pop_lists(new_secondary_list, new_primary_list, pop_len) + extend_count -= pop_len + + return new_primary_list, new_secondary_list, extend_count + + def extend(self, iterable): + """ + Return new deque with all elements of iterable appended to the right. + + >>> pdeque([1, 2]).extend([3, 4]) + pdeque([1, 2, 3, 4]) + """ + new_right_list, new_left_list, extend_count = self._extend(self._right_list, self._left_list, iterable) + return PDeque(new_left_list, new_right_list, self._length + extend_count, self._maxlen) + + def extendleft(self, iterable): + """ + Return new deque with all elements of iterable appended to the left. + + NB! The elements will be inserted in reverse order compared to the order in the iterable. + + >>> pdeque([1, 2]).extendleft([3, 4]) + pdeque([4, 3, 1, 2]) + """ + new_left_list, new_right_list, extend_count = self._extend(self._left_list, self._right_list, iterable) + return PDeque(new_left_list, new_right_list, self._length + extend_count, self._maxlen) + + def count(self, elem): + """ + Return the number of elements equal to elem present in the queue + + >>> pdeque([1, 2, 1]).count(1) + 2 + """ + return self._left_list.count(elem) + self._right_list.count(elem) + + def remove(self, elem): + """ + Return new deque with first element from left equal to elem removed. If no such element is found + a ValueError is raised. + + >>> pdeque([2, 1, 2]).remove(2) + pdeque([1, 2]) + """ + try: + return PDeque(self._left_list.remove(elem), self._right_list, self._length - 1) + except ValueError: + # Value not found in left list, try the right list + try: + # This is severely inefficient with a double reverse, should perhaps implement a remove_last()? + return PDeque(self._left_list, + self._right_list.reverse().remove(elem).reverse(), self._length - 1) + except ValueError: + raise ValueError('{0} not found in PDeque'.format(elem)) + + def reverse(self): + """ + Return reversed deque. + + >>> pdeque([1, 2, 3]).reverse() + pdeque([3, 2, 1]) + + Also supports the standard python reverse function. + + >>> reversed(pdeque([1, 2, 3])) + pdeque([3, 2, 1]) + """ + return PDeque(self._right_list, self._left_list, self._length) + __reversed__ = reverse + + def rotate(self, steps): + """ + Return deque with elements rotated steps steps. + + >>> x = pdeque([1, 2, 3]) + >>> x.rotate(1) + pdeque([3, 1, 2]) + >>> x.rotate(-2) + pdeque([3, 1, 2]) + """ + popped_deque = self.pop(steps) + if steps >= 0: + return popped_deque.extendleft(islice(self.reverse(), steps)) + + return popped_deque.extend(islice(self, -steps)) + + def __reduce__(self): + # Pickling support + return pdeque, (list(self), self._maxlen) + + def __getitem__(self, index): + if isinstance(index, slice): + if index.step is not None and index.step != 1: + # Too difficult, no structural sharing possible + return pdeque(tuple(self)[index], maxlen=self._maxlen) + + result = self + if index.start is not None: + result = result.popleft(index.start % self._length) + if index.stop is not None: + result = result.pop(self._length - (index.stop % self._length)) + + return result + + if not isinstance(index, Integral): + raise TypeError("'%s' object cannot be interpreted as an index" % type(index).__name__) + + if index >= 0: + return self.popleft(index).left + + shifted = len(self) + index + if shifted < 0: + raise IndexError( + "pdeque index {0} out of range {1}".format(index, len(self)), + ) + return self.popleft(shifted).left + + index = Sequence.index + +Sequence.register(PDeque) +Hashable.register(PDeque) + + +def pdeque(iterable=(), maxlen=None): + """ + Return deque containing the elements of iterable. If maxlen is specified then + len(iterable) - maxlen elements are discarded from the left to if len(iterable) > maxlen. + + >>> pdeque([1, 2, 3]) + pdeque([1, 2, 3]) + >>> pdeque([1, 2, 3, 4], maxlen=2) + pdeque([3, 4], maxlen=2) + """ + t = tuple(iterable) + if maxlen is not None: + t = t[-maxlen:] + length = len(t) + pivot = int(length / 2) + left = plist(t[:pivot]) + right = plist(t[pivot:], reverse=True) + return PDeque(left, right, length, maxlen) + +def dq(*elements): + """ + Return deque containing all arguments. + + >>> dq(1, 2, 3) + pdeque([1, 2, 3]) + """ + return pdeque(elements) diff --git a/third_party/python/pyrsistent/pyrsistent/_plist.py b/third_party/python/pyrsistent/pyrsistent/_plist.py new file mode 100644 index 0000000000..8b4267f5e3 --- /dev/null +++ b/third_party/python/pyrsistent/pyrsistent/_plist.py @@ -0,0 +1,313 @@ +from ._compat import Sequence, Hashable +from numbers import Integral +from functools import reduce + + +class _PListBuilder(object): + """ + Helper class to allow construction of a list without + having to reverse it in the end. + """ + __slots__ = ('_head', '_tail') + + def __init__(self): + self._head = _EMPTY_PLIST + self._tail = _EMPTY_PLIST + + def _append(self, elem, constructor): + if not self._tail: + self._head = constructor(elem) + self._tail = self._head + else: + self._tail.rest = constructor(elem) + self._tail = self._tail.rest + + return self._head + + def append_elem(self, elem): + return self._append(elem, lambda e: PList(e, _EMPTY_PLIST)) + + def append_plist(self, pl): + return self._append(pl, lambda l: l) + + def build(self): + return self._head + + +class _PListBase(object): + __slots__ = ('__weakref__',) + + # Selected implementations can be taken straight from the Sequence + # class, other are less suitable. Especially those that work with + # index lookups. + count = Sequence.count + index = Sequence.index + + def __reduce__(self): + # Pickling support + return plist, (list(self),) + + def __len__(self): + """ + Return the length of the list, computed by traversing it. + + This is obviously O(n) but with the current implementation + where a list is also a node the overhead of storing the length + in every node would be quite significant. + """ + return sum(1 for _ in self) + + def __repr__(self): + return "plist({0})".format(list(self)) + __str__ = __repr__ + + def cons(self, elem): + """ + Return a new list with elem inserted as new head. + + >>> plist([1, 2]).cons(3) + plist([3, 1, 2]) + """ + return PList(elem, self) + + def mcons(self, iterable): + """ + Return a new list with all elements of iterable repeatedly cons:ed to the current list. + NB! The elements will be inserted in the reverse order of the iterable. + Runs in O(len(iterable)). + + >>> plist([1, 2]).mcons([3, 4]) + plist([4, 3, 1, 2]) + """ + head = self + for elem in iterable: + head = head.cons(elem) + + return head + + def reverse(self): + """ + Return a reversed version of list. Runs in O(n) where n is the length of the list. + + >>> plist([1, 2, 3]).reverse() + plist([3, 2, 1]) + + Also supports the standard reversed function. + + >>> reversed(plist([1, 2, 3])) + plist([3, 2, 1]) + """ + result = plist() + head = self + while head: + result = result.cons(head.first) + head = head.rest + + return result + __reversed__ = reverse + + def split(self, index): + """ + Spilt the list at position specified by index. Returns a tuple containing the + list up until index and the list after the index. Runs in O(index). + + >>> plist([1, 2, 3, 4]).split(2) + (plist([1, 2]), plist([3, 4])) + """ + lb = _PListBuilder() + right_list = self + i = 0 + while right_list and i < index: + lb.append_elem(right_list.first) + right_list = right_list.rest + i += 1 + + if not right_list: + # Just a small optimization in the cases where no split occurred + return self, _EMPTY_PLIST + + return lb.build(), right_list + + def __iter__(self): + li = self + while li: + yield li.first + li = li.rest + + def __lt__(self, other): + if not isinstance(other, _PListBase): + return NotImplemented + + return tuple(self) < tuple(other) + + def __eq__(self, other): + """ + Traverses the lists, checking equality of elements. + + This is an O(n) operation, but preserves the standard semantics of list equality. + """ + if not isinstance(other, _PListBase): + return NotImplemented + + self_head = self + other_head = other + while self_head and other_head: + if not self_head.first == other_head.first: + return False + self_head = self_head.rest + other_head = other_head.rest + + return not self_head and not other_head + + def __getitem__(self, index): + # Don't use this this data structure if you plan to do a lot of indexing, it is + # very inefficient! Use a PVector instead! + + if isinstance(index, slice): + if index.start is not None and index.stop is None and (index.step is None or index.step == 1): + return self._drop(index.start) + + # Take the easy way out for all other slicing cases, not much structural reuse possible anyway + return plist(tuple(self)[index]) + + if not isinstance(index, Integral): + raise TypeError("'%s' object cannot be interpreted as an index" % type(index).__name__) + + if index < 0: + # NB: O(n)! + index += len(self) + + try: + return self._drop(index).first + except AttributeError: + raise IndexError("PList index out of range") + + def _drop(self, count): + if count < 0: + raise IndexError("PList index out of range") + + head = self + while count > 0: + head = head.rest + count -= 1 + + return head + + def __hash__(self): + return hash(tuple(self)) + + def remove(self, elem): + """ + Return new list with first element equal to elem removed. O(k) where k is the position + of the element that is removed. + + Raises ValueError if no matching element is found. + + >>> plist([1, 2, 1]).remove(1) + plist([2, 1]) + """ + + builder = _PListBuilder() + head = self + while head: + if head.first == elem: + return builder.append_plist(head.rest) + + builder.append_elem(head.first) + head = head.rest + + raise ValueError('{0} not found in PList'.format(elem)) + + +class PList(_PListBase): + """ + Classical Lisp style singly linked list. Adding elements to the head using cons is O(1). + Element access is O(k) where k is the position of the element in the list. Taking the + length of the list is O(n). + + Fully supports the Sequence and Hashable protocols including indexing and slicing but + if you need fast random access go for the PVector instead. + + Do not instantiate directly, instead use the factory functions :py:func:`l` or :py:func:`plist` to + create an instance. + + Some examples: + + >>> x = plist([1, 2]) + >>> y = x.cons(3) + >>> x + plist([1, 2]) + >>> y + plist([3, 1, 2]) + >>> y.first + 3 + >>> y.rest == x + True + >>> y[:2] + plist([3, 1]) + """ + __slots__ = ('first', 'rest') + + def __new__(cls, first, rest): + instance = super(PList, cls).__new__(cls) + instance.first = first + instance.rest = rest + return instance + + def __bool__(self): + return True + __nonzero__ = __bool__ + + +Sequence.register(PList) +Hashable.register(PList) + + +class _EmptyPList(_PListBase): + __slots__ = () + + def __bool__(self): + return False + __nonzero__ = __bool__ + + @property + def first(self): + raise AttributeError("Empty PList has no first") + + @property + def rest(self): + return self + + +Sequence.register(_EmptyPList) +Hashable.register(_EmptyPList) + +_EMPTY_PLIST = _EmptyPList() + + +def plist(iterable=(), reverse=False): + """ + Creates a new persistent list containing all elements of iterable. + Optional parameter reverse specifies if the elements should be inserted in + reverse order or not. + + >>> plist([1, 2, 3]) + plist([1, 2, 3]) + >>> plist([1, 2, 3], reverse=True) + plist([3, 2, 1]) + """ + if not reverse: + iterable = list(iterable) + iterable.reverse() + + return reduce(lambda pl, elem: pl.cons(elem), iterable, _EMPTY_PLIST) + + +def l(*elements): + """ + Creates a new persistent list containing all arguments. + + >>> l(1, 2, 3) + plist([1, 2, 3]) + """ + return plist(elements) diff --git a/third_party/python/pyrsistent/pyrsistent/_pmap.py b/third_party/python/pyrsistent/pyrsistent/_pmap.py new file mode 100644 index 0000000000..e8a0ec53f8 --- /dev/null +++ b/third_party/python/pyrsistent/pyrsistent/_pmap.py @@ -0,0 +1,460 @@ +from ._compat import Mapping, Hashable +from itertools import chain +import six +from pyrsistent._pvector import pvector +from pyrsistent._transformations import transform + + +class PMap(object): + """ + Persistent map/dict. Tries to follow the same naming conventions as the built in dict where feasible. + + Do not instantiate directly, instead use the factory functions :py:func:`m` or :py:func:`pmap` to + create an instance. + + Was originally written as a very close copy of the Clojure equivalent but was later rewritten to closer + re-assemble the python dict. This means that a sparse vector (a PVector) of buckets is used. The keys are + hashed and the elements inserted at position hash % len(bucket_vector). Whenever the map size exceeds 2/3 of + the containing vectors size the map is reallocated to a vector of double the size. This is done to avoid + excessive hash collisions. + + This structure corresponds most closely to the built in dict type and is intended as a replacement. Where the + semantics are the same (more or less) the same function names have been used but for some cases it is not possible, + for example assignments and deletion of values. + + PMap implements the Mapping protocol and is Hashable. It also supports dot-notation for + element access. + + Random access and insert is log32(n) where n is the size of the map. + + The following are examples of some common operations on persistent maps + + >>> m1 = m(a=1, b=3) + >>> m2 = m1.set('c', 3) + >>> m3 = m2.remove('a') + >>> m1 + pmap({'b': 3, 'a': 1}) + >>> m2 + pmap({'c': 3, 'b': 3, 'a': 1}) + >>> m3 + pmap({'c': 3, 'b': 3}) + >>> m3['c'] + 3 + >>> m3.c + 3 + """ + __slots__ = ('_size', '_buckets', '__weakref__', '_cached_hash') + + def __new__(cls, size, buckets): + self = super(PMap, cls).__new__(cls) + self._size = size + self._buckets = buckets + return self + + @staticmethod + def _get_bucket(buckets, key): + index = hash(key) % len(buckets) + bucket = buckets[index] + return index, bucket + + @staticmethod + def _getitem(buckets, key): + _, bucket = PMap._get_bucket(buckets, key) + if bucket: + for k, v in bucket: + if k == key: + return v + + raise KeyError(key) + + def __getitem__(self, key): + return PMap._getitem(self._buckets, key) + + @staticmethod + def _contains(buckets, key): + _, bucket = PMap._get_bucket(buckets, key) + if bucket: + for k, _ in bucket: + if k == key: + return True + + return False + + return False + + def __contains__(self, key): + return self._contains(self._buckets, key) + + get = Mapping.get + + def __iter__(self): + return self.iterkeys() + + def __getattr__(self, key): + try: + return self[key] + except KeyError: + raise AttributeError( + "{0} has no attribute '{1}'".format(type(self).__name__, key) + ) + + def iterkeys(self): + for k, _ in self.iteritems(): + yield k + + # These are more efficient implementations compared to the original + # methods that are based on the keys iterator and then calls the + # accessor functions to access the value for the corresponding key + def itervalues(self): + for _, v in self.iteritems(): + yield v + + def iteritems(self): + for bucket in self._buckets: + if bucket: + for k, v in bucket: + yield k, v + + def values(self): + return pvector(self.itervalues()) + + def keys(self): + return pvector(self.iterkeys()) + + def items(self): + return pvector(self.iteritems()) + + def __len__(self): + return self._size + + def __repr__(self): + return 'pmap({0})'.format(str(dict(self))) + + def __eq__(self, other): + if self is other: + return True + if not isinstance(other, Mapping): + return NotImplemented + if len(self) != len(other): + return False + if isinstance(other, PMap): + if (hasattr(self, '_cached_hash') and hasattr(other, '_cached_hash') + and self._cached_hash != other._cached_hash): + return False + if self._buckets == other._buckets: + return True + return dict(self.iteritems()) == dict(other.iteritems()) + elif isinstance(other, dict): + return dict(self.iteritems()) == other + return dict(self.iteritems()) == dict(six.iteritems(other)) + + __ne__ = Mapping.__ne__ + + def __lt__(self, other): + raise TypeError('PMaps are not orderable') + + __le__ = __lt__ + __gt__ = __lt__ + __ge__ = __lt__ + + def __str__(self): + return self.__repr__() + + def __hash__(self): + if not hasattr(self, '_cached_hash'): + self._cached_hash = hash(frozenset(self.iteritems())) + return self._cached_hash + + def set(self, key, val): + """ + Return a new PMap with key and val inserted. + + >>> m1 = m(a=1, b=2) + >>> m2 = m1.set('a', 3) + >>> m3 = m1.set('c' ,4) + >>> m1 + pmap({'b': 2, 'a': 1}) + >>> m2 + pmap({'b': 2, 'a': 3}) + >>> m3 + pmap({'c': 4, 'b': 2, 'a': 1}) + """ + return self.evolver().set(key, val).persistent() + + def remove(self, key): + """ + Return a new PMap without the element specified by key. Raises KeyError if the element + is not present. + + >>> m1 = m(a=1, b=2) + >>> m1.remove('a') + pmap({'b': 2}) + """ + return self.evolver().remove(key).persistent() + + def discard(self, key): + """ + Return a new PMap without the element specified by key. Returns reference to itself + if element is not present. + + >>> m1 = m(a=1, b=2) + >>> m1.discard('a') + pmap({'b': 2}) + >>> m1 is m1.discard('c') + True + """ + try: + return self.remove(key) + except KeyError: + return self + + def update(self, *maps): + """ + Return a new PMap with the items in Mappings inserted. If the same key is present in multiple + maps the rightmost (last) value is inserted. + + >>> m1 = m(a=1, b=2) + >>> m1.update(m(a=2, c=3), {'a': 17, 'd': 35}) + pmap({'c': 3, 'b': 2, 'a': 17, 'd': 35}) + """ + return self.update_with(lambda l, r: r, *maps) + + def update_with(self, update_fn, *maps): + """ + Return a new PMap with the items in Mappings maps inserted. If the same key is present in multiple + maps the values will be merged using merge_fn going from left to right. + + >>> from operator import add + >>> m1 = m(a=1, b=2) + >>> m1.update_with(add, m(a=2)) + pmap({'b': 2, 'a': 3}) + + The reverse behaviour of the regular merge. Keep the leftmost element instead of the rightmost. + + >>> m1 = m(a=1) + >>> m1.update_with(lambda l, r: l, m(a=2), {'a':3}) + pmap({'a': 1}) + """ + evolver = self.evolver() + for map in maps: + for key, value in map.items(): + evolver.set(key, update_fn(evolver[key], value) if key in evolver else value) + + return evolver.persistent() + + def __add__(self, other): + return self.update(other) + + def __reduce__(self): + # Pickling support + return pmap, (dict(self),) + + def transform(self, *transformations): + """ + Transform arbitrarily complex combinations of PVectors and PMaps. A transformation + consists of two parts. One match expression that specifies which elements to transform + and one transformation function that performs the actual transformation. + + >>> from pyrsistent import freeze, ny + >>> news_paper = freeze({'articles': [{'author': 'Sara', 'content': 'A short article'}, + ... {'author': 'Steve', 'content': 'A slightly longer article'}], + ... 'weather': {'temperature': '11C', 'wind': '5m/s'}}) + >>> short_news = news_paper.transform(['articles', ny, 'content'], lambda c: c[:25] + '...' if len(c) > 25 else c) + >>> very_short_news = news_paper.transform(['articles', ny, 'content'], lambda c: c[:15] + '...' if len(c) > 15 else c) + >>> very_short_news.articles[0].content + 'A short article' + >>> very_short_news.articles[1].content + 'A slightly long...' + + When nothing has been transformed the original data structure is kept + + >>> short_news is news_paper + True + >>> very_short_news is news_paper + False + >>> very_short_news.articles[0] is news_paper.articles[0] + True + """ + return transform(self, transformations) + + def copy(self): + return self + + class _Evolver(object): + __slots__ = ('_buckets_evolver', '_size', '_original_pmap') + + def __init__(self, original_pmap): + self._original_pmap = original_pmap + self._buckets_evolver = original_pmap._buckets.evolver() + self._size = original_pmap._size + + def __getitem__(self, key): + return PMap._getitem(self._buckets_evolver, key) + + def __setitem__(self, key, val): + self.set(key, val) + + def set(self, key, val): + if len(self._buckets_evolver) < 0.67 * self._size: + self._reallocate(2 * len(self._buckets_evolver)) + + kv = (key, val) + index, bucket = PMap._get_bucket(self._buckets_evolver, key) + if bucket: + for k, v in bucket: + if k == key: + if v is not val: + new_bucket = [(k2, v2) if k2 != k else (k2, val) for k2, v2 in bucket] + self._buckets_evolver[index] = new_bucket + + return self + + new_bucket = [kv] + new_bucket.extend(bucket) + self._buckets_evolver[index] = new_bucket + self._size += 1 + else: + self._buckets_evolver[index] = [kv] + self._size += 1 + + return self + + def _reallocate(self, new_size): + new_list = new_size * [None] + buckets = self._buckets_evolver.persistent() + for k, v in chain.from_iterable(x for x in buckets if x): + index = hash(k) % new_size + if new_list[index]: + new_list[index].append((k, v)) + else: + new_list[index] = [(k, v)] + + # A reallocation should always result in a dirty buckets evolver to avoid + # possible loss of elements when doing the reallocation. + self._buckets_evolver = pvector().evolver() + self._buckets_evolver.extend(new_list) + + def is_dirty(self): + return self._buckets_evolver.is_dirty() + + def persistent(self): + if self.is_dirty(): + self._original_pmap = PMap(self._size, self._buckets_evolver.persistent()) + + return self._original_pmap + + def __len__(self): + return self._size + + def __contains__(self, key): + return PMap._contains(self._buckets_evolver, key) + + def __delitem__(self, key): + self.remove(key) + + def remove(self, key): + index, bucket = PMap._get_bucket(self._buckets_evolver, key) + + if bucket: + new_bucket = [(k, v) for (k, v) in bucket if k != key] + if len(bucket) > len(new_bucket): + self._buckets_evolver[index] = new_bucket if new_bucket else None + self._size -= 1 + return self + + raise KeyError('{0}'.format(key)) + + def evolver(self): + """ + Create a new evolver for this pmap. For a discussion on evolvers in general see the + documentation for the pvector evolver. + + Create the evolver and perform various mutating updates to it: + + >>> m1 = m(a=1, b=2) + >>> e = m1.evolver() + >>> e['c'] = 3 + >>> len(e) + 3 + >>> del e['a'] + + The underlying pmap remains the same: + + >>> m1 + pmap({'b': 2, 'a': 1}) + + The changes are kept in the evolver. An updated pmap can be created using the + persistent() function on the evolver. + + >>> m2 = e.persistent() + >>> m2 + pmap({'c': 3, 'b': 2}) + + The new pmap will share data with the original pmap in the same way that would have + been done if only using operations on the pmap. + """ + return self._Evolver(self) + +Mapping.register(PMap) +Hashable.register(PMap) + + +def _turbo_mapping(initial, pre_size): + if pre_size: + size = pre_size + else: + try: + size = 2 * len(initial) or 8 + except Exception: + # Guess we can't figure out the length. Give up on length hinting, + # we can always reallocate later. + size = 8 + + buckets = size * [None] + + if not isinstance(initial, Mapping): + # Make a dictionary of the initial data if it isn't already, + # that will save us some job further down since we can assume no + # key collisions + initial = dict(initial) + + for k, v in six.iteritems(initial): + h = hash(k) + index = h % size + bucket = buckets[index] + + if bucket: + bucket.append((k, v)) + else: + buckets[index] = [(k, v)] + + return PMap(len(initial), pvector().extend(buckets)) + + +_EMPTY_PMAP = _turbo_mapping({}, 0) + + +def pmap(initial={}, pre_size=0): + """ + Create new persistent map, inserts all elements in initial into the newly created map. + The optional argument pre_size may be used to specify an initial size of the underlying bucket vector. This + may have a positive performance impact in the cases where you know beforehand that a large number of elements + will be inserted into the map eventually since it will reduce the number of reallocations required. + + >>> pmap({'a': 13, 'b': 14}) + pmap({'b': 14, 'a': 13}) + """ + if not initial: + return _EMPTY_PMAP + + return _turbo_mapping(initial, pre_size) + + +def m(**kwargs): + """ + Creates a new persitent map. Inserts all key value arguments into the newly created map. + + >>> m(a=13, b=14) + pmap({'b': 14, 'a': 13}) + """ + return pmap(kwargs) diff --git a/third_party/python/pyrsistent/pyrsistent/_precord.py b/third_party/python/pyrsistent/pyrsistent/_precord.py new file mode 100644 index 0000000000..ec8d32c3da --- /dev/null +++ b/third_party/python/pyrsistent/pyrsistent/_precord.py @@ -0,0 +1,169 @@ +import six +from pyrsistent._checked_types import CheckedType, _restore_pickle, InvariantException, store_invariants +from pyrsistent._field_common import ( + set_fields, check_type, is_field_ignore_extra_complaint, PFIELD_NO_INITIAL, serialize, check_global_invariants +) +from pyrsistent._pmap import PMap, pmap + + +class _PRecordMeta(type): + def __new__(mcs, name, bases, dct): + set_fields(dct, bases, name='_precord_fields') + store_invariants(dct, bases, '_precord_invariants', '__invariant__') + + dct['_precord_mandatory_fields'] = \ + set(name for name, field in dct['_precord_fields'].items() if field.mandatory) + + dct['_precord_initial_values'] = \ + dict((k, field.initial) for k, field in dct['_precord_fields'].items() if field.initial is not PFIELD_NO_INITIAL) + + + dct['__slots__'] = () + + return super(_PRecordMeta, mcs).__new__(mcs, name, bases, dct) + + +@six.add_metaclass(_PRecordMeta) +class PRecord(PMap, CheckedType): + """ + A PRecord is a PMap with a fixed set of specified fields. Records are declared as python classes inheriting + from PRecord. Because it is a PMap it has full support for all Mapping methods such as iteration and element + access using subscript notation. + + More documentation and examples of PRecord usage is available at https://github.com/tobgu/pyrsistent + """ + def __new__(cls, **kwargs): + # Hack total! If these two special attributes exist that means we can create + # ourselves. Otherwise we need to go through the Evolver to create the structures + # for us. + if '_precord_size' in kwargs and '_precord_buckets' in kwargs: + return super(PRecord, cls).__new__(cls, kwargs['_precord_size'], kwargs['_precord_buckets']) + + factory_fields = kwargs.pop('_factory_fields', None) + ignore_extra = kwargs.pop('_ignore_extra', False) + + initial_values = kwargs + if cls._precord_initial_values: + initial_values = dict((k, v() if callable(v) else v) + for k, v in cls._precord_initial_values.items()) + initial_values.update(kwargs) + + e = _PRecordEvolver(cls, pmap(), _factory_fields=factory_fields, _ignore_extra=ignore_extra) + for k, v in initial_values.items(): + e[k] = v + + return e.persistent() + + def set(self, *args, **kwargs): + """ + Set a field in the record. This set function differs slightly from that in the PMap + class. First of all it accepts key-value pairs. Second it accepts multiple key-value + pairs to perform one, atomic, update of multiple fields. + """ + + # The PRecord set() can accept kwargs since all fields that have been declared are + # valid python identifiers. Also allow multiple fields to be set in one operation. + if args: + return super(PRecord, self).set(args[0], args[1]) + + return self.update(kwargs) + + def evolver(self): + """ + Returns an evolver of this object. + """ + return _PRecordEvolver(self.__class__, self) + + def __repr__(self): + return "{0}({1})".format(self.__class__.__name__, + ', '.join('{0}={1}'.format(k, repr(v)) for k, v in self.items())) + + @classmethod + def create(cls, kwargs, _factory_fields=None, ignore_extra=False): + """ + Factory method. Will create a new PRecord of the current type and assign the values + specified in kwargs. + + :param ignore_extra: A boolean which when set to True will ignore any keys which appear in kwargs that are not + in the set of fields on the PRecord. + """ + if isinstance(kwargs, cls): + return kwargs + + if ignore_extra: + kwargs = {k: kwargs[k] for k in cls._precord_fields if k in kwargs} + + return cls(_factory_fields=_factory_fields, _ignore_extra=ignore_extra, **kwargs) + + def __reduce__(self): + # Pickling support + return _restore_pickle, (self.__class__, dict(self),) + + def serialize(self, format=None): + """ + Serialize the current PRecord using custom serializer functions for fields where + such have been supplied. + """ + return dict((k, serialize(self._precord_fields[k].serializer, format, v)) for k, v in self.items()) + + +class _PRecordEvolver(PMap._Evolver): + __slots__ = ('_destination_cls', '_invariant_error_codes', '_missing_fields', '_factory_fields', '_ignore_extra') + + def __init__(self, cls, original_pmap, _factory_fields=None, _ignore_extra=False): + super(_PRecordEvolver, self).__init__(original_pmap) + self._destination_cls = cls + self._invariant_error_codes = [] + self._missing_fields = [] + self._factory_fields = _factory_fields + self._ignore_extra = _ignore_extra + + def __setitem__(self, key, original_value): + self.set(key, original_value) + + def set(self, key, original_value): + field = self._destination_cls._precord_fields.get(key) + if field: + if self._factory_fields is None or field in self._factory_fields: + try: + if is_field_ignore_extra_complaint(PRecord, field, self._ignore_extra): + value = field.factory(original_value, ignore_extra=self._ignore_extra) + else: + value = field.factory(original_value) + except InvariantException as e: + self._invariant_error_codes += e.invariant_errors + self._missing_fields += e.missing_fields + return self + else: + value = original_value + + check_type(self._destination_cls, field, key, value) + + is_ok, error_code = field.invariant(value) + if not is_ok: + self._invariant_error_codes.append(error_code) + + return super(_PRecordEvolver, self).set(key, value) + else: + raise AttributeError("'{0}' is not among the specified fields for {1}".format(key, self._destination_cls.__name__)) + + def persistent(self): + cls = self._destination_cls + is_dirty = self.is_dirty() + pm = super(_PRecordEvolver, self).persistent() + if is_dirty or not isinstance(pm, cls): + result = cls(_precord_buckets=pm._buckets, _precord_size=pm._size) + else: + result = pm + + if cls._precord_mandatory_fields: + self._missing_fields += tuple('{0}.{1}'.format(cls.__name__, f) for f + in (cls._precord_mandatory_fields - set(result.keys()))) + + if self._invariant_error_codes or self._missing_fields: + raise InvariantException(tuple(self._invariant_error_codes), tuple(self._missing_fields), + 'Field invariant failed') + + check_global_invariants(result, cls._precord_invariants) + + return result diff --git a/third_party/python/pyrsistent/pyrsistent/_pset.py b/third_party/python/pyrsistent/pyrsistent/_pset.py new file mode 100644 index 0000000000..a972ec533b --- /dev/null +++ b/third_party/python/pyrsistent/pyrsistent/_pset.py @@ -0,0 +1,229 @@ +from ._compat import Set, Hashable +import sys +from pyrsistent._pmap import pmap + +PY2 = sys.version_info[0] < 3 + + +class PSet(object): + """ + Persistent set implementation. Built on top of the persistent map. The set supports all operations + in the Set protocol and is Hashable. + + Do not instantiate directly, instead use the factory functions :py:func:`s` or :py:func:`pset` + to create an instance. + + Random access and insert is log32(n) where n is the size of the set. + + Some examples: + + >>> s = pset([1, 2, 3, 1]) + >>> s2 = s.add(4) + >>> s3 = s2.remove(2) + >>> s + pset([1, 2, 3]) + >>> s2 + pset([1, 2, 3, 4]) + >>> s3 + pset([1, 3, 4]) + """ + __slots__ = ('_map', '__weakref__') + + def __new__(cls, m): + self = super(PSet, cls).__new__(cls) + self._map = m + return self + + def __contains__(self, element): + return element in self._map + + def __iter__(self): + return iter(self._map) + + def __len__(self): + return len(self._map) + + def __repr__(self): + if PY2 or not self: + return 'p' + str(set(self)) + + return 'pset([{0}])'.format(str(set(self))[1:-1]) + + def __str__(self): + return self.__repr__() + + def __hash__(self): + return hash(self._map) + + def __reduce__(self): + # Pickling support + return pset, (list(self),) + + @classmethod + def _from_iterable(cls, it, pre_size=8): + return PSet(pmap(dict((k, True) for k in it), pre_size=pre_size)) + + def add(self, element): + """ + Return a new PSet with element added + + >>> s1 = s(1, 2) + >>> s1.add(3) + pset([1, 2, 3]) + """ + return self.evolver().add(element).persistent() + + def update(self, iterable): + """ + Return a new PSet with elements in iterable added + + >>> s1 = s(1, 2) + >>> s1.update([3, 4, 4]) + pset([1, 2, 3, 4]) + """ + e = self.evolver() + for element in iterable: + e.add(element) + + return e.persistent() + + def remove(self, element): + """ + Return a new PSet with element removed. Raises KeyError if element is not present. + + >>> s1 = s(1, 2) + >>> s1.remove(2) + pset([1]) + """ + if element in self._map: + return self.evolver().remove(element).persistent() + + raise KeyError("Element '%s' not present in PSet" % element) + + def discard(self, element): + """ + Return a new PSet with element removed. Returns itself if element is not present. + """ + if element in self._map: + return self.evolver().remove(element).persistent() + + return self + + class _Evolver(object): + __slots__ = ('_original_pset', '_pmap_evolver') + + def __init__(self, original_pset): + self._original_pset = original_pset + self._pmap_evolver = original_pset._map.evolver() + + def add(self, element): + self._pmap_evolver[element] = True + return self + + def remove(self, element): + del self._pmap_evolver[element] + return self + + def is_dirty(self): + return self._pmap_evolver.is_dirty() + + def persistent(self): + if not self.is_dirty(): + return self._original_pset + + return PSet(self._pmap_evolver.persistent()) + + def __len__(self): + return len(self._pmap_evolver) + + def copy(self): + return self + + def evolver(self): + """ + Create a new evolver for this pset. For a discussion on evolvers in general see the + documentation for the pvector evolver. + + Create the evolver and perform various mutating updates to it: + + >>> s1 = s(1, 2, 3) + >>> e = s1.evolver() + >>> _ = e.add(4) + >>> len(e) + 4 + >>> _ = e.remove(1) + + The underlying pset remains the same: + + >>> s1 + pset([1, 2, 3]) + + The changes are kept in the evolver. An updated pmap can be created using the + persistent() function on the evolver. + + >>> s2 = e.persistent() + >>> s2 + pset([2, 3, 4]) + + The new pset will share data with the original pset in the same way that would have + been done if only using operations on the pset. + """ + return PSet._Evolver(self) + + # All the operations and comparisons you would expect on a set. + # + # This is not very beautiful. If we avoid inheriting from PSet we can use the + # __slots__ concepts (which requires a new style class) and hopefully save some memory. + __le__ = Set.__le__ + __lt__ = Set.__lt__ + __gt__ = Set.__gt__ + __ge__ = Set.__ge__ + __eq__ = Set.__eq__ + __ne__ = Set.__ne__ + + __and__ = Set.__and__ + __or__ = Set.__or__ + __sub__ = Set.__sub__ + __xor__ = Set.__xor__ + + issubset = __le__ + issuperset = __ge__ + union = __or__ + intersection = __and__ + difference = __sub__ + symmetric_difference = __xor__ + + isdisjoint = Set.isdisjoint + +Set.register(PSet) +Hashable.register(PSet) + +_EMPTY_PSET = PSet(pmap()) + + +def pset(iterable=(), pre_size=8): + """ + Creates a persistent set from iterable. Optionally takes a sizing parameter equivalent to that + used for :py:func:`pmap`. + + >>> s1 = pset([1, 2, 3, 2]) + >>> s1 + pset([1, 2, 3]) + """ + if not iterable: + return _EMPTY_PSET + + return PSet._from_iterable(iterable, pre_size=pre_size) + + +def s(*elements): + """ + Create a persistent set. + + Takes an arbitrary number of arguments to insert into the new set. + + >>> s1 = s(1, 2, 3, 2) + >>> s1 + pset([1, 2, 3]) + """ + return pset(elements) diff --git a/third_party/python/pyrsistent/pyrsistent/_pvector.py b/third_party/python/pyrsistent/pyrsistent/_pvector.py new file mode 100644 index 0000000000..82232782b7 --- /dev/null +++ b/third_party/python/pyrsistent/pyrsistent/_pvector.py @@ -0,0 +1,713 @@ +from abc import abstractmethod, ABCMeta +from ._compat import Sequence, Hashable +from numbers import Integral +import operator +import six +from pyrsistent._transformations import transform + + +def _bitcount(val): + return bin(val).count("1") + +BRANCH_FACTOR = 32 +BIT_MASK = BRANCH_FACTOR - 1 +SHIFT = _bitcount(BIT_MASK) + + +def compare_pvector(v, other, operator): + return operator(v.tolist(), other.tolist() if isinstance(other, PVector) else other) + + +def _index_or_slice(index, stop): + if stop is None: + return index + + return slice(index, stop) + + +class PythonPVector(object): + """ + Support structure for PVector that implements structural sharing for vectors using a trie. + """ + __slots__ = ('_count', '_shift', '_root', '_tail', '_tail_offset', '__weakref__') + + def __new__(cls, count, shift, root, tail): + self = super(PythonPVector, cls).__new__(cls) + self._count = count + self._shift = shift + self._root = root + self._tail = tail + + # Derived attribute stored for performance + self._tail_offset = self._count - len(self._tail) + return self + + def __len__(self): + return self._count + + def __getitem__(self, index): + if isinstance(index, slice): + # There are more conditions than the below where it would be OK to + # return ourselves, implement those... + if index.start is None and index.stop is None and index.step is None: + return self + + # This is a bit nasty realizing the whole structure as a list before + # slicing it but it is the fastest way I've found to date, and it's easy :-) + return _EMPTY_PVECTOR.extend(self.tolist()[index]) + + if index < 0: + index += self._count + + return PythonPVector._node_for(self, index)[index & BIT_MASK] + + def __add__(self, other): + return self.extend(other) + + def __repr__(self): + return 'pvector({0})'.format(str(self.tolist())) + + def __str__(self): + return self.__repr__() + + def __iter__(self): + # This is kind of lazy and will produce some memory overhead but it is the fasted method + # by far of those tried since it uses the speed of the built in python list directly. + return iter(self.tolist()) + + def __ne__(self, other): + return not self.__eq__(other) + + def __eq__(self, other): + return self is other or (hasattr(other, '__len__') and self._count == len(other)) and compare_pvector(self, other, operator.eq) + + def __gt__(self, other): + return compare_pvector(self, other, operator.gt) + + def __lt__(self, other): + return compare_pvector(self, other, operator.lt) + + def __ge__(self, other): + return compare_pvector(self, other, operator.ge) + + def __le__(self, other): + return compare_pvector(self, other, operator.le) + + def __mul__(self, times): + if times <= 0 or self is _EMPTY_PVECTOR: + return _EMPTY_PVECTOR + + if times == 1: + return self + + return _EMPTY_PVECTOR.extend(times * self.tolist()) + + __rmul__ = __mul__ + + def _fill_list(self, node, shift, the_list): + if shift: + shift -= SHIFT + for n in node: + self._fill_list(n, shift, the_list) + else: + the_list.extend(node) + + def tolist(self): + """ + The fastest way to convert the vector into a python list. + """ + the_list = [] + self._fill_list(self._root, self._shift, the_list) + the_list.extend(self._tail) + return the_list + + def _totuple(self): + """ + Returns the content as a python tuple. + """ + return tuple(self.tolist()) + + def __hash__(self): + # Taking the easy way out again... + return hash(self._totuple()) + + def transform(self, *transformations): + return transform(self, transformations) + + def __reduce__(self): + # Pickling support + return pvector, (self.tolist(),) + + def mset(self, *args): + if len(args) % 2: + raise TypeError("mset expected an even number of arguments") + + evolver = self.evolver() + for i in range(0, len(args), 2): + evolver[args[i]] = args[i+1] + + return evolver.persistent() + + class Evolver(object): + __slots__ = ('_count', '_shift', '_root', '_tail', '_tail_offset', '_dirty_nodes', + '_extra_tail', '_cached_leafs', '_orig_pvector') + + def __init__(self, v): + self._reset(v) + + def __getitem__(self, index): + if not isinstance(index, Integral): + raise TypeError("'%s' object cannot be interpreted as an index" % type(index).__name__) + + if index < 0: + index += self._count + len(self._extra_tail) + + if self._count <= index < self._count + len(self._extra_tail): + return self._extra_tail[index - self._count] + + return PythonPVector._node_for(self, index)[index & BIT_MASK] + + def _reset(self, v): + self._count = v._count + self._shift = v._shift + self._root = v._root + self._tail = v._tail + self._tail_offset = v._tail_offset + self._dirty_nodes = {} + self._cached_leafs = {} + self._extra_tail = [] + self._orig_pvector = v + + def append(self, element): + self._extra_tail.append(element) + return self + + def extend(self, iterable): + self._extra_tail.extend(iterable) + return self + + def set(self, index, val): + self[index] = val + return self + + def __setitem__(self, index, val): + if not isinstance(index, Integral): + raise TypeError("'%s' object cannot be interpreted as an index" % type(index).__name__) + + if index < 0: + index += self._count + len(self._extra_tail) + + if 0 <= index < self._count: + node = self._cached_leafs.get(index >> SHIFT) + if node: + node[index & BIT_MASK] = val + elif index >= self._tail_offset: + if id(self._tail) not in self._dirty_nodes: + self._tail = list(self._tail) + self._dirty_nodes[id(self._tail)] = True + self._cached_leafs[index >> SHIFT] = self._tail + self._tail[index & BIT_MASK] = val + else: + self._root = self._do_set(self._shift, self._root, index, val) + elif self._count <= index < self._count + len(self._extra_tail): + self._extra_tail[index - self._count] = val + elif index == self._count + len(self._extra_tail): + self._extra_tail.append(val) + else: + raise IndexError("Index out of range: %s" % (index,)) + + def _do_set(self, level, node, i, val): + if id(node) in self._dirty_nodes: + ret = node + else: + ret = list(node) + self._dirty_nodes[id(ret)] = True + + if level == 0: + ret[i & BIT_MASK] = val + self._cached_leafs[i >> SHIFT] = ret + else: + sub_index = (i >> level) & BIT_MASK # >>> + ret[sub_index] = self._do_set(level - SHIFT, node[sub_index], i, val) + + return ret + + def delete(self, index): + del self[index] + return self + + def __delitem__(self, key): + if self._orig_pvector: + # All structural sharing bets are off, base evolver on _extra_tail only + l = PythonPVector(self._count, self._shift, self._root, self._tail).tolist() + l.extend(self._extra_tail) + self._reset(_EMPTY_PVECTOR) + self._extra_tail = l + + del self._extra_tail[key] + + def persistent(self): + result = self._orig_pvector + if self.is_dirty(): + result = PythonPVector(self._count, self._shift, self._root, self._tail).extend(self._extra_tail) + self._reset(result) + + return result + + def __len__(self): + return self._count + len(self._extra_tail) + + def is_dirty(self): + return bool(self._dirty_nodes or self._extra_tail) + + def evolver(self): + return PythonPVector.Evolver(self) + + def set(self, i, val): + # This method could be implemented by a call to mset() but doing so would cause + # a ~5 X performance penalty on PyPy (considered the primary platform for this implementation + # of PVector) so we're keeping this implementation for now. + + if not isinstance(i, Integral): + raise TypeError("'%s' object cannot be interpreted as an index" % type(i).__name__) + + if i < 0: + i += self._count + + if 0 <= i < self._count: + if i >= self._tail_offset: + new_tail = list(self._tail) + new_tail[i & BIT_MASK] = val + return PythonPVector(self._count, self._shift, self._root, new_tail) + + return PythonPVector(self._count, self._shift, self._do_set(self._shift, self._root, i, val), self._tail) + + if i == self._count: + return self.append(val) + + raise IndexError("Index out of range: %s" % (i,)) + + def _do_set(self, level, node, i, val): + ret = list(node) + if level == 0: + ret[i & BIT_MASK] = val + else: + sub_index = (i >> level) & BIT_MASK # >>> + ret[sub_index] = self._do_set(level - SHIFT, node[sub_index], i, val) + + return ret + + @staticmethod + def _node_for(pvector_like, i): + if 0 <= i < pvector_like._count: + if i >= pvector_like._tail_offset: + return pvector_like._tail + + node = pvector_like._root + for level in range(pvector_like._shift, 0, -SHIFT): + node = node[(i >> level) & BIT_MASK] # >>> + + return node + + raise IndexError("Index out of range: %s" % (i,)) + + def _create_new_root(self): + new_shift = self._shift + + # Overflow root? + if (self._count >> SHIFT) > (1 << self._shift): # >>> + new_root = [self._root, self._new_path(self._shift, self._tail)] + new_shift += SHIFT + else: + new_root = self._push_tail(self._shift, self._root, self._tail) + + return new_root, new_shift + + def append(self, val): + if len(self._tail) < BRANCH_FACTOR: + new_tail = list(self._tail) + new_tail.append(val) + return PythonPVector(self._count + 1, self._shift, self._root, new_tail) + + # Full tail, push into tree + new_root, new_shift = self._create_new_root() + return PythonPVector(self._count + 1, new_shift, new_root, [val]) + + def _new_path(self, level, node): + if level == 0: + return node + + return [self._new_path(level - SHIFT, node)] + + def _mutating_insert_tail(self): + self._root, self._shift = self._create_new_root() + self._tail = [] + + def _mutating_fill_tail(self, offset, sequence): + max_delta_len = BRANCH_FACTOR - len(self._tail) + delta = sequence[offset:offset + max_delta_len] + self._tail.extend(delta) + delta_len = len(delta) + self._count += delta_len + return offset + delta_len + + def _mutating_extend(self, sequence): + offset = 0 + sequence_len = len(sequence) + while offset < sequence_len: + offset = self._mutating_fill_tail(offset, sequence) + if len(self._tail) == BRANCH_FACTOR: + self._mutating_insert_tail() + + self._tail_offset = self._count - len(self._tail) + + def extend(self, obj): + # Mutates the new vector directly for efficiency but that's only an + # implementation detail, once it is returned it should be considered immutable + l = obj.tolist() if isinstance(obj, PythonPVector) else list(obj) + if l: + new_vector = self.append(l[0]) + new_vector._mutating_extend(l[1:]) + return new_vector + + return self + + def _push_tail(self, level, parent, tail_node): + """ + if parent is leaf, insert node, + else does it map to an existing child? -> + node_to_insert = push node one more level + else alloc new path + + return node_to_insert placed in copy of parent + """ + ret = list(parent) + + if level == SHIFT: + ret.append(tail_node) + return ret + + sub_index = ((self._count - 1) >> level) & BIT_MASK # >>> + if len(parent) > sub_index: + ret[sub_index] = self._push_tail(level - SHIFT, parent[sub_index], tail_node) + return ret + + ret.append(self._new_path(level - SHIFT, tail_node)) + return ret + + def index(self, value, *args, **kwargs): + return self.tolist().index(value, *args, **kwargs) + + def count(self, value): + return self.tolist().count(value) + + def delete(self, index, stop=None): + l = self.tolist() + del l[_index_or_slice(index, stop)] + return _EMPTY_PVECTOR.extend(l) + + def remove(self, value): + l = self.tolist() + l.remove(value) + return _EMPTY_PVECTOR.extend(l) + +@six.add_metaclass(ABCMeta) +class PVector(object): + """ + Persistent vector implementation. Meant as a replacement for the cases where you would normally + use a Python list. + + Do not instantiate directly, instead use the factory functions :py:func:`v` and :py:func:`pvector` to + create an instance. + + Heavily influenced by the persistent vector available in Clojure. Initially this was more or + less just a port of the Java code for the Clojure vector. It has since been modified and to + some extent optimized for usage in Python. + + The vector is organized as a trie, any mutating method will return a new vector that contains the changes. No + updates are done to the original vector. Structural sharing between vectors are applied where possible to save + space and to avoid making complete copies. + + This structure corresponds most closely to the built in list type and is intended as a replacement. Where the + semantics are the same (more or less) the same function names have been used but for some cases it is not possible, + for example assignments. + + The PVector implements the Sequence protocol and is Hashable. + + Inserts are amortized O(1). Random access is log32(n) where n is the size of the vector. + + The following are examples of some common operations on persistent vectors: + + >>> p = v(1, 2, 3) + >>> p2 = p.append(4) + >>> p3 = p2.extend([5, 6, 7]) + >>> p + pvector([1, 2, 3]) + >>> p2 + pvector([1, 2, 3, 4]) + >>> p3 + pvector([1, 2, 3, 4, 5, 6, 7]) + >>> p3[5] + 6 + >>> p.set(1, 99) + pvector([1, 99, 3]) + >>> + """ + + @abstractmethod + def __len__(self): + """ + >>> len(v(1, 2, 3)) + 3 + """ + + @abstractmethod + def __getitem__(self, index): + """ + Get value at index. Full slicing support. + + >>> v1 = v(5, 6, 7, 8) + >>> v1[2] + 7 + >>> v1[1:3] + pvector([6, 7]) + """ + + @abstractmethod + def __add__(self, other): + """ + >>> v1 = v(1, 2) + >>> v2 = v(3, 4) + >>> v1 + v2 + pvector([1, 2, 3, 4]) + """ + + @abstractmethod + def __mul__(self, times): + """ + >>> v1 = v(1, 2) + >>> 3 * v1 + pvector([1, 2, 1, 2, 1, 2]) + """ + + @abstractmethod + def __hash__(self): + """ + >>> v1 = v(1, 2, 3) + >>> v2 = v(1, 2, 3) + >>> hash(v1) == hash(v2) + True + """ + + @abstractmethod + def evolver(self): + """ + Create a new evolver for this pvector. The evolver acts as a mutable view of the vector + with "transaction like" semantics. No part of the underlying vector i updated, it is still + fully immutable. Furthermore multiple evolvers created from the same pvector do not + interfere with each other. + + You may want to use an evolver instead of working directly with the pvector in the + following cases: + + * Multiple updates are done to the same vector and the intermediate results are of no + interest. In this case using an evolver may be a more efficient and easier to work with. + * You need to pass a vector into a legacy function or a function that you have no control + over which performs in place mutations of lists. In this case pass an evolver instance + instead and then create a new pvector from the evolver once the function returns. + + The following example illustrates a typical workflow when working with evolvers. It also + displays most of the API (which i kept small by design, you should not be tempted to + use evolvers in excess ;-)). + + Create the evolver and perform various mutating updates to it: + + >>> v1 = v(1, 2, 3, 4, 5) + >>> e = v1.evolver() + >>> e[1] = 22 + >>> _ = e.append(6) + >>> _ = e.extend([7, 8, 9]) + >>> e[8] += 1 + >>> len(e) + 9 + + The underlying pvector remains the same: + + >>> v1 + pvector([1, 2, 3, 4, 5]) + + The changes are kept in the evolver. An updated pvector can be created using the + persistent() function on the evolver. + + >>> v2 = e.persistent() + >>> v2 + pvector([1, 22, 3, 4, 5, 6, 7, 8, 10]) + + The new pvector will share data with the original pvector in the same way that would have + been done if only using operations on the pvector. + """ + + @abstractmethod + def mset(self, *args): + """ + Return a new vector with elements in specified positions replaced by values (multi set). + + Elements on even positions in the argument list are interpreted as indexes while + elements on odd positions are considered values. + + >>> v1 = v(1, 2, 3) + >>> v1.mset(0, 11, 2, 33) + pvector([11, 2, 33]) + """ + + @abstractmethod + def set(self, i, val): + """ + Return a new vector with element at position i replaced with val. The original vector remains unchanged. + + Setting a value one step beyond the end of the vector is equal to appending. Setting beyond that will + result in an IndexError. + + >>> v1 = v(1, 2, 3) + >>> v1.set(1, 4) + pvector([1, 4, 3]) + >>> v1.set(3, 4) + pvector([1, 2, 3, 4]) + >>> v1.set(-1, 4) + pvector([1, 2, 4]) + """ + + @abstractmethod + def append(self, val): + """ + Return a new vector with val appended. + + >>> v1 = v(1, 2) + >>> v1.append(3) + pvector([1, 2, 3]) + """ + + @abstractmethod + def extend(self, obj): + """ + Return a new vector with all values in obj appended to it. Obj may be another + PVector or any other Iterable. + + >>> v1 = v(1, 2, 3) + >>> v1.extend([4, 5]) + pvector([1, 2, 3, 4, 5]) + """ + + @abstractmethod + def index(self, value, *args, **kwargs): + """ + Return first index of value. Additional indexes may be supplied to limit the search to a + sub range of the vector. + + >>> v1 = v(1, 2, 3, 4, 3) + >>> v1.index(3) + 2 + >>> v1.index(3, 3, 5) + 4 + """ + + @abstractmethod + def count(self, value): + """ + Return the number of times that value appears in the vector. + + >>> v1 = v(1, 4, 3, 4) + >>> v1.count(4) + 2 + """ + + @abstractmethod + def transform(self, *transformations): + """ + Transform arbitrarily complex combinations of PVectors and PMaps. A transformation + consists of two parts. One match expression that specifies which elements to transform + and one transformation function that performs the actual transformation. + + >>> from pyrsistent import freeze, ny + >>> news_paper = freeze({'articles': [{'author': 'Sara', 'content': 'A short article'}, + ... {'author': 'Steve', 'content': 'A slightly longer article'}], + ... 'weather': {'temperature': '11C', 'wind': '5m/s'}}) + >>> short_news = news_paper.transform(['articles', ny, 'content'], lambda c: c[:25] + '...' if len(c) > 25 else c) + >>> very_short_news = news_paper.transform(['articles', ny, 'content'], lambda c: c[:15] + '...' if len(c) > 15 else c) + >>> very_short_news.articles[0].content + 'A short article' + >>> very_short_news.articles[1].content + 'A slightly long...' + + When nothing has been transformed the original data structure is kept + + >>> short_news is news_paper + True + >>> very_short_news is news_paper + False + >>> very_short_news.articles[0] is news_paper.articles[0] + True + """ + + @abstractmethod + def delete(self, index, stop=None): + """ + Delete a portion of the vector by index or range. + + >>> v1 = v(1, 2, 3, 4, 5) + >>> v1.delete(1) + pvector([1, 3, 4, 5]) + >>> v1.delete(1, 3) + pvector([1, 4, 5]) + """ + + @abstractmethod + def remove(self, value): + """ + Remove the first occurrence of a value from the vector. + + >>> v1 = v(1, 2, 3, 2, 1) + >>> v2 = v1.remove(1) + >>> v2 + pvector([2, 3, 2, 1]) + >>> v2.remove(1) + pvector([2, 3, 2]) + """ + + +_EMPTY_PVECTOR = PythonPVector(0, SHIFT, [], []) +PVector.register(PythonPVector) +Sequence.register(PVector) +Hashable.register(PVector) + +def python_pvector(iterable=()): + """ + Create a new persistent vector containing the elements in iterable. + + >>> v1 = pvector([1, 2, 3]) + >>> v1 + pvector([1, 2, 3]) + """ + return _EMPTY_PVECTOR.extend(iterable) + +try: + # Use the C extension as underlying trie implementation if it is available + import os + if os.environ.get('PYRSISTENT_NO_C_EXTENSION'): + pvector = python_pvector + else: + from pvectorc import pvector + PVector.register(type(pvector())) +except ImportError: + pvector = python_pvector + + +def v(*elements): + """ + Create a new persistent vector containing all parameters to this function. + + >>> v1 = v(1, 2, 3) + >>> v1 + pvector([1, 2, 3]) + """ + return pvector(elements) diff --git a/third_party/python/pyrsistent/pyrsistent/_toolz.py b/third_party/python/pyrsistent/pyrsistent/_toolz.py new file mode 100644 index 0000000000..6643ee860d --- /dev/null +++ b/third_party/python/pyrsistent/pyrsistent/_toolz.py @@ -0,0 +1,83 @@ +""" +Functionality copied from the toolz package to avoid having +to add toolz as a dependency. + +See https://github.com/pytoolz/toolz/. + +toolz is relased under BSD licence. Below is the licence text +from toolz as it appeared when copying the code. + +-------------------------------------------------------------- + +Copyright (c) 2013 Matthew Rocklin + +All rights reserved. + +Redistribution and use in source and binary forms, with or without +modification, are permitted provided that the following conditions are met: + + a. Redistributions of source code must retain the above copyright notice, + this list of conditions and the following disclaimer. + b. Redistributions in binary form must reproduce the above copyright + notice, this list of conditions and the following disclaimer in the + documentation and/or other materials provided with the distribution. + c. Neither the name of toolz nor the names of its contributors + may be used to endorse or promote products derived from this software + without specific prior written permission. + + +THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" +AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE +IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE +ARE DISCLAIMED. IN NO EVENT SHALL THE REGENTS OR CONTRIBUTORS BE LIABLE FOR +ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL +DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR +SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER +CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT +LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY +OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH +DAMAGE. +""" +import operator +from six.moves import reduce + + +def get_in(keys, coll, default=None, no_default=False): + """ + NB: This is a straight copy of the get_in implementation found in + the toolz library (https://github.com/pytoolz/toolz/). It works + with persistent data structures as well as the corresponding + datastructures from the stdlib. + + Returns coll[i0][i1]...[iX] where [i0, i1, ..., iX]==keys. + + If coll[i0][i1]...[iX] cannot be found, returns ``default``, unless + ``no_default`` is specified, then it raises KeyError or IndexError. + + ``get_in`` is a generalization of ``operator.getitem`` for nested data + structures such as dictionaries and lists. + >>> from pyrsistent import freeze + >>> transaction = freeze({'name': 'Alice', + ... 'purchase': {'items': ['Apple', 'Orange'], + ... 'costs': [0.50, 1.25]}, + ... 'credit card': '5555-1234-1234-1234'}) + >>> get_in(['purchase', 'items', 0], transaction) + 'Apple' + >>> get_in(['name'], transaction) + 'Alice' + >>> get_in(['purchase', 'total'], transaction) + >>> get_in(['purchase', 'items', 'apple'], transaction) + >>> get_in(['purchase', 'items', 10], transaction) + >>> get_in(['purchase', 'total'], transaction, 0) + 0 + >>> get_in(['y'], {}, no_default=True) + Traceback (most recent call last): + ... + KeyError: 'y' + """ + try: + return reduce(operator.getitem, keys, coll) + except (KeyError, IndexError, TypeError): + if no_default: + raise + return default
\ No newline at end of file diff --git a/third_party/python/pyrsistent/pyrsistent/_transformations.py b/third_party/python/pyrsistent/pyrsistent/_transformations.py new file mode 100644 index 0000000000..612098969b --- /dev/null +++ b/third_party/python/pyrsistent/pyrsistent/_transformations.py @@ -0,0 +1,143 @@ +import re +import six +try: + from inspect import Parameter, signature +except ImportError: + signature = None + try: + from inspect import getfullargspec as getargspec + except ImportError: + from inspect import getargspec + + +_EMPTY_SENTINEL = object() + + +def inc(x): + """ Add one to the current value """ + return x + 1 + + +def dec(x): + """ Subtract one from the current value """ + return x - 1 + + +def discard(evolver, key): + """ Discard the element and returns a structure without the discarded elements """ + try: + del evolver[key] + except KeyError: + pass + + +# Matchers +def rex(expr): + """ Regular expression matcher to use together with transform functions """ + r = re.compile(expr) + return lambda key: isinstance(key, six.string_types) and r.match(key) + + +def ny(_): + """ Matcher that matches any value """ + return True + + +# Support functions +def _chunks(l, n): + for i in range(0, len(l), n): + yield l[i:i + n] + + +def transform(structure, transformations): + r = structure + for path, command in _chunks(transformations, 2): + r = _do_to_path(r, path, command) + return r + + +def _do_to_path(structure, path, command): + if not path: + return command(structure) if callable(command) else command + + kvs = _get_keys_and_values(structure, path[0]) + return _update_structure(structure, kvs, path[1:], command) + + +def _items(structure): + try: + return structure.items() + except AttributeError: + # Support wider range of structures by adding a transform_items() or similar? + return list(enumerate(structure)) + + +def _get(structure, key, default): + try: + if hasattr(structure, '__getitem__'): + return structure[key] + + return getattr(structure, key) + + except (IndexError, KeyError): + return default + + +def _get_keys_and_values(structure, key_spec): + if callable(key_spec): + # Support predicates as callable objects in the path + arity = _get_arity(key_spec) + if arity == 1: + # Unary predicates are called with the "key" of the path + # - eg a key in a mapping, an index in a sequence. + return [(k, v) for k, v in _items(structure) if key_spec(k)] + elif arity == 2: + # Binary predicates are called with the key and the corresponding + # value. + return [(k, v) for k, v in _items(structure) if key_spec(k, v)] + else: + # Other arities are an error. + raise ValueError( + "callable in transform path must take 1 or 2 arguments" + ) + + # Non-callables are used as-is as a key. + return [(key_spec, _get(structure, key_spec, _EMPTY_SENTINEL))] + + +if signature is None: + def _get_arity(f): + argspec = getargspec(f) + return len(argspec.args) - len(argspec.defaults or ()) +else: + def _get_arity(f): + return sum( + 1 + for p + in signature(f).parameters.values() + if p.default is Parameter.empty + and p.kind in (Parameter.POSITIONAL_ONLY, Parameter.POSITIONAL_OR_KEYWORD) + ) + + +def _update_structure(structure, kvs, path, command): + from pyrsistent._pmap import pmap + e = structure.evolver() + if not path and command is discard: + # Do this in reverse to avoid index problems with vectors. See #92. + for k, v in reversed(kvs): + discard(e, k) + else: + for k, v in kvs: + is_empty = False + if v is _EMPTY_SENTINEL: + # Allow expansion of structure but make sure to cover the case + # when an empty pmap is added as leaf node. See #154. + is_empty = True + v = pmap() + + result = _do_to_path(v, path, command) + if result is not v or is_empty: + e[k] = result + + return e.persistent() diff --git a/third_party/python/pyrsistent/pyrsistent/py.typed b/third_party/python/pyrsistent/pyrsistent/py.typed new file mode 100644 index 0000000000..e69de29bb2 --- /dev/null +++ b/third_party/python/pyrsistent/pyrsistent/py.typed diff --git a/third_party/python/pyrsistent/pyrsistent/typing.py b/third_party/python/pyrsistent/pyrsistent/typing.py new file mode 100644 index 0000000000..6a86c831ba --- /dev/null +++ b/third_party/python/pyrsistent/pyrsistent/typing.py @@ -0,0 +1,80 @@ +"""Helpers for use with type annotation. + +Use the empty classes in this module when annotating the types of Pyrsistent +objects, instead of using the actual collection class. + +For example, + + from pyrsistent import pvector + from pyrsistent.typing import PVector + + myvector: PVector[str] = pvector(['a', 'b', 'c']) + +""" +from __future__ import absolute_import + +try: + from typing import Container + from typing import Hashable + from typing import Generic + from typing import Iterable + from typing import Mapping + from typing import Sequence + from typing import Sized + from typing import TypeVar + + __all__ = [ + 'CheckedPMap', + 'CheckedPSet', + 'CheckedPVector', + 'PBag', + 'PDeque', + 'PList', + 'PMap', + 'PSet', + 'PVector', + ] + + T = TypeVar('T') + KT = TypeVar('KT') + VT = TypeVar('VT') + + class CheckedPMap(Mapping[KT, VT], Hashable): + pass + + # PSet.add and PSet.discard have different type signatures than that of Set. + class CheckedPSet(Generic[T], Hashable): + pass + + class CheckedPVector(Sequence[T], Hashable): + pass + + class PBag(Container[T], Iterable[T], Sized, Hashable): + pass + + class PDeque(Sequence[T], Hashable): + pass + + class PList(Sequence[T], Hashable): + pass + + class PMap(Mapping[KT, VT], Hashable): + pass + + # PSet.add and PSet.discard have different type signatures than that of Set. + class PSet(Generic[T], Hashable): + pass + + class PVector(Sequence[T], Hashable): + pass + + class PVectorEvolver(Generic[T]): + pass + + class PMapEvolver(Generic[KT, VT]): + pass + + class PSetEvolver(Generic[T]): + pass +except ImportError: + pass diff --git a/third_party/python/pyrsistent/pyrsistent/typing.pyi b/third_party/python/pyrsistent/pyrsistent/typing.pyi new file mode 100644 index 0000000000..0221c48cc9 --- /dev/null +++ b/third_party/python/pyrsistent/pyrsistent/typing.pyi @@ -0,0 +1,292 @@ +# flake8: noqa: E704 +# from https://gist.github.com/WuTheFWasThat/091a17d4b5cab597dfd5d4c2d96faf09 +# Stubs for pyrsistent (Python 3.6) +# +from typing import Any +from typing import Callable +from typing import Dict +from typing import Generic +from typing import Hashable +from typing import Iterator +from typing import Iterable +from typing import List +from typing import Mapping +from typing import Optional +from typing import Sequence +from typing import AbstractSet +from typing import Sized +from typing import Set +from typing import Tuple +from typing import TypeVar +from typing import Type +from typing import Union +from typing import overload + +T = TypeVar('T') +KT = TypeVar('KT') +VT = TypeVar('VT') + + +class PMap(Mapping[KT, VT], Hashable): + def __add__(self, other: PMap[KT, VT]) -> PMap[KT, VT]: ... + def __getitem__(self, key: KT) -> VT: ... + def __getattr__(self, key: str) -> VT: ... + def __hash__(self) -> int: ... + def __iter__(self) -> Iterator[KT]: ... + def __len__(self) -> int: ... + def copy(self) -> PMap[KT, VT]: ... + def discard(self, key: KT) -> PMap[KT, VT]: ... + def evolver(self) -> PMapEvolver[KT, VT]: ... + def iteritems(self) -> Iterable[Tuple[KT, VT]]: ... + def iterkeys(self) -> Iterable[KT]: ... + def itervalues(self) -> Iterable[VT]: ... + def remove(self, key: KT) -> PMap[KT, VT]: ... + def set(self, key: KT, val: VT) -> PMap[KT, VT]: ... + def transform(self, *transformations: Any) -> PMap[KT, VT]: ... + def update(self, *args: Mapping): ... + def update_with(self, update_fn: Callable[[VT, VT], VT], *args: Mapping) -> Any: ... + + +class PMapEvolver(Generic[KT, VT]): + def __delitem__(self, key: KT) -> None: ... + def __getitem__(self, key: KT) -> VT: ... + def __len__(self) -> int: ... + def __setitem__(self, key: KT, val: VT) -> None: ... + def is_dirty(self) -> bool: ... + def persistent(self) -> PMap[KT, VT]: ... + def remove(self, key: KT) -> PMapEvolver[KT, VT]: ... + def set(self, key: KT, val: VT) -> PMapEvolver[KT, VT]: ... + + +class PVector(Sequence[T], Hashable): + def __add__(self, other: PVector[T]) -> PVector[T]: ... + @overload + def __getitem__(self, index: int) -> T: ... + @overload + def __getitem__(self, index: slice) -> PVector[T]: ... + def __hash__(self) -> int: ... + def __len__(self) -> int: ... + def __mul__(self, other: PVector[T]) -> PVector[T]: ... + def append(self, val: T) -> PVector[T]: ... + def delete(self, index: int, stop: Optional[int]) -> PVector[T]: ... + def evolver(self) -> PVectorEvolver[T]: ... + def extend(self, obj: Iterable[T]) -> PVector[T]: ... + def tolist(self) -> List[T]: ... + def mset(self, *args: Iterable[Union[T, int]]) -> PVector[T]: ... + def remove(self, value: T) -> PVector[T]: ... + # Not compatible with MutableSequence + def set(self, i: int, val: T) -> PVector[T]: ... + def transform(self, *transformations: Any) -> PVector[T]: ... + + +class PVectorEvolver(Sequence[T], Sized): + def __delitem__(self, i: Union[int, slice]) -> None: ... + @overload + def __getitem__(self, index: int) -> T: ... + # Not actually supported + @overload + def __getitem__(self, index: slice) -> PVectorEvolver[T]: ... + def __len__(self) -> int: ... + def __setitem__(self, index: int, val: T) -> None: ... + def append(self, val: T) -> PVectorEvolver[T]: ... + def delete(self, value: T) -> PVectorEvolver[T]: ... + def extend(self, obj: Iterable[T]) -> PVectorEvolver[T]: ... + def is_dirty(self) -> bool: ... + def persistent(self) -> PVector[T]: ... + def set(self, i: int, val: T) -> PVectorEvolver[T]: ... + + +class PSet(AbstractSet[T], Hashable): + def __contains__(self, element: object) -> bool: ... + def __hash__(self) -> int: ... + def __iter__(self) -> Iterator[T]: ... + def __len__(self) -> int: ... + def add(self, element: T) -> PSet[T]: ... + def copy(self) -> PSet[T]: ... + def difference(self, iterable: Iterable) -> PSet[T]: ... + def discard(self, element: T) -> PSet[T]: ... + def evolver(self) -> PSetEvolver[T]: ... + def intersection(self, iterable: Iterable) -> PSet[T]: ... + def issubset(self, iterable: Iterable) -> bool: ... + def issuperset(self, iterable: Iterable) -> bool: ... + def remove(self, element: T) -> PSet[T]: ... + def symmetric_difference(self, iterable: Iterable[T]) -> PSet[T]: ... + def union(self, iterable: Iterable[T]) -> PSet[T]: ... + def update(self, iterable: Iterable[T]) -> PSet[T]: ... + + +class PSetEvolver(Generic[T], Sized): + def __len__(self) -> int: ... + def add(self, element: T) -> PSetEvolver[T]: ... + def is_dirty(self) -> bool: ... + def persistent(self) -> PSet[T]: ... + def remove(self, element: T) -> PSetEvolver[T]: ... + + +class PBag(Generic[T], Sized, Hashable): + def __add__(self, other: PBag[T]) -> PBag[T]: ... + def __and__(self, other: PBag[T]) -> PBag[T]: ... + def __contains__(self, elem: object) -> bool: ... + def __hash__(self) -> int: ... + def __iter__(self) -> Iterator[T]: ... + def __len__(self) -> int: ... + def __or__(self, other: PBag[T]) -> PBag[T]: ... + def __sub__(self, other: PBag[T]) -> PBag[T]: ... + def add(self, elem: T) -> PBag[T]: ... + def count(self, elem: T) -> int: ... + def remove(self, elem: T) -> PBag[T]: ... + def update(self, iterable: Iterable[T]) -> PBag[T]: ... + + +class PDeque(Sequence[T], Hashable): + @overload + def __getitem__(self, index: int) -> T: ... + @overload + def __getitem__(self, index: slice) -> PDeque[T]: ... + def __hash__(self) -> int: ... + def __len__(self) -> int: ... + def __lt__(self, other: PDeque[T]) -> bool: ... + def append(self, elem: T) -> PDeque[T]: ... + def appendleft(self, elem: T) -> PDeque[T]: ... + def extend(self, iterable: Iterable[T]) -> PDeque[T]: ... + def extendleft(self, iterable: Iterable[T]) -> PDeque[T]: ... + @property + def left(self) -> T: ... + # The real return type is Integral according to what pyrsistent + # checks at runtime but mypy doesn't deal in numeric.*: + # https://github.com/python/mypy/issues/2636 + @property + def maxlen(self) -> int: ... + def pop(self, count: int = 1) -> PDeque[T]: ... + def popleft(self, count: int = 1) -> PDeque[T]: ... + def remove(self, elem: T) -> PDeque[T]: ... + def reverse(self) -> PDeque[T]: ... + @property + def right(self) -> T: ... + def rotate(self, steps: int) -> PDeque[T]: ... + + +class PList(Sequence[T], Hashable): + @overload + def __getitem__(self, index: int) -> T: ... + @overload + def __getitem__(self, index: slice) -> PList[T]: ... + def __hash__(self) -> int: ... + def __len__(self) -> int: ... + def __lt__(self, other: PList[T]) -> bool: ... + def __gt__(self, other: PList[T]) -> bool: ... + def cons(self, elem: T) -> PList[T]: ... + @property + def first(self) -> T: ... + def mcons(self, iterable: Iterable[T]) -> PList[T]: ... + def remove(self, elem: T) -> PList[T]: ... + @property + def rest(self) -> PList[T]: ... + def reverse(self) -> PList[T]: ... + def split(self, index: int) -> Tuple[PList[T], PList[T]]: ... + +T_PClass = TypeVar('T_PClass', bound='PClass') + +class PClass(Hashable): + def __new__(cls, **kwargs: Any): ... + def set(self: T_PClass, *args: Any, **kwargs: Any) -> T_PClass: ... + @classmethod + def create( + cls: Type[T_PClass], + kwargs: Any, + _factory_fields: Optional[Any] = ..., + ignore_extra: bool = ..., + ) -> T_PClass: ... + def serialize(self, format: Optional[Any] = ...): ... + def transform(self, *transformations: Any): ... + def __eq__(self, other: object): ... + def __ne__(self, other: object): ... + def __hash__(self): ... + def __reduce__(self): ... + def evolver(self) -> PClassEvolver: ... + def remove(self: T_PClass, name: Any) -> T_PClass: ... + +class PClassEvolver: + def __init__(self, original: Any, initial_dict: Any) -> None: ... + def __getitem__(self, item: Any): ... + def set(self, key: Any, value: Any): ... + def __setitem__(self, key: Any, value: Any) -> None: ... + def remove(self, item: Any): ... + def __delitem__(self, item: Any) -> None: ... + def persistent(self) -> PClass: ... + def __getattr__(self, item: Any): ... + + + +class CheckedPMap(PMap[KT, VT]): + __key_type__: Type[KT] + __value_type__: Type[VT] + def __new__(cls, source: Mapping[KT, VT] = ..., size: int = ...) -> CheckedPMap: ... + @classmethod + def create(cls, source_data: Mapping[KT, VT], _factory_fields: Any = ...) -> CheckedPMap[KT, VT]: ... + def serialize(self, format: Optional[Any] = ...) -> Dict[KT, VT]: ... + + +class CheckedPVector(PVector[T]): + __type__: Type[T] + def __new__(self, initial: Iterable[T] = ...) -> CheckedPVector: ... + @classmethod + def create(cls, source_data: Iterable[T], _factory_fields: Any = ...) -> CheckedPVector[T]: ... + def serialize(self, format: Optional[Any] = ...) -> List[T]: ... + + +class CheckedPSet(PSet[T]): + __type__: Type[T] + def __new__(cls, initial: Iterable[T] = ...) -> CheckedPSet: ... + @classmethod + def create(cls, source_data: Iterable[T], _factory_fields: Any = ...) -> CheckedPSet[T]: ... + def serialize(self, format: Optional[Any] = ...) -> Set[T]: ... + + +class InvariantException(Exception): + invariant_errors: Tuple[Any, ...] = ... # possibly nested tuple + missing_fields: Tuple[str, ...] = ... + def __init__( + self, + error_codes: Any = ..., + missing_fields: Any = ..., + *args: Any, + **kwargs: Any + ) -> None: ... + + +class CheckedTypeError(TypeError): + source_class: Type[Any] + expected_types: Tuple[Any, ...] + actual_type: Type[Any] + actual_value: Any + def __init__( + self, + source_class: Any, + expected_types: Any, + actual_type: Any, + actual_value: Any, + *args: Any, + **kwargs: Any + ) -> None: ... + + +class CheckedKeyTypeError(CheckedTypeError): ... +class CheckedValueTypeError(CheckedTypeError): ... +class CheckedType: ... + + +class PTypeError(TypeError): + source_class: Type[Any] = ... + field: str = ... + expected_types: Tuple[Any, ...] = ... + actual_type: Type[Any] = ... + def __init__( + self, + source_class: Any, + field: Any, + expected_types: Any, + actual_type: Any, + *args: Any, + **kwargs: Any + ) -> None: ... diff --git a/third_party/python/pyrsistent/setup.cfg b/third_party/python/pyrsistent/setup.cfg new file mode 100644 index 0000000000..e4eba0b6c3 --- /dev/null +++ b/third_party/python/pyrsistent/setup.cfg @@ -0,0 +1,7 @@ +[aliases] +test = pytest + +[egg_info] +tag_build = +tag_date = 0 + diff --git a/third_party/python/pyrsistent/setup.py b/third_party/python/pyrsistent/setup.py new file mode 100644 index 0000000000..931800ff15 --- /dev/null +++ b/third_party/python/pyrsistent/setup.py @@ -0,0 +1,81 @@ +import os +from setuptools import setup, Extension +import sys +import platform +import warnings +import codecs +from distutils.command.build_ext import build_ext +from distutils.errors import CCompilerError +from distutils.errors import DistutilsPlatformError, DistutilsExecError +from _pyrsistent_version import __version__ + +readme_path = os.path.join(os.path.dirname(__file__), 'README.rst') +with codecs.open(readme_path, encoding='utf8') as f: + readme = f.read() + +extensions = [] +if platform.python_implementation() == 'CPython': + extensions = [Extension('pvectorc', sources=['pvectorcmodule.c'])] + +needs_pytest = {'pytest', 'test', 'ptr'}.intersection(sys.argv) +pytest_runner = ['pytest-runner'] if needs_pytest else [] + + +class custom_build_ext(build_ext): + """Allow C extension building to fail.""" + + warning_message = """ +******************************************************************************** +WARNING: Could not build the %s. + Pyrsistent will still work but performance may be degraded. + %s +******************************************************************************** +""" + + def run(self): + try: + build_ext.run(self) + except Exception: + e = sys.exc_info()[1] + sys.stderr.write('%s\n' % str(e)) + sys.stderr.write(self.warning_message % ("extension modules", "There was an issue with your platform configuration - see above.")) + + def build_extension(self, ext): + name = ext.name + try: + build_ext.build_extension(self, ext) + except Exception: + e = sys.exc_info()[1] + sys.stderr.write('%s\n' % str(e)) + sys.stderr.write(self.warning_message % ("%s extension module" % name, "The output above this warning shows how the compilation failed.")) + +setup( + name='pyrsistent', + version=__version__, + description='Persistent/Functional/Immutable data structures', + long_description=readme, + author='Tobias Gustafsson', + author_email='tobias.l.gustafsson@gmail.com', + url='http://github.com/tobgu/pyrsistent/', + license='MIT', + license_files=['LICENCE.mit'], + py_modules=['_pyrsistent_version'], + classifiers=[ + 'Intended Audience :: Developers', + 'License :: OSI Approved :: MIT License', + 'Operating System :: OS Independent', + 'Programming Language :: Python :: 3.5', + 'Programming Language :: Python :: 3.6', + 'Programming Language :: Python :: 3.7', + 'Programming Language :: Python :: Implementation :: PyPy', + ], + test_suite='tests', + tests_require=['pytest<5', 'hypothesis<5'], + scripts=[], + setup_requires=pytest_runner, + ext_modules=extensions, + cmdclass={'build_ext': custom_build_ext}, + install_requires=['six'], + packages=['pyrsistent'], + package_data={'pyrsistent': ['py.typed', '__init__.pyi', 'typing.pyi']}, +) |