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authorDaniel Baumann <daniel.baumann@progress-linux.org>2024-05-04 17:35:20 +0000
committerDaniel Baumann <daniel.baumann@progress-linux.org>2024-05-04 17:35:20 +0000
commite106bf94eff07d9a59771d9ccc4406421e18ab64 (patch)
treeedb6545500e39df9c67aa918a6125bffc8ec1aee /src/prompt_toolkit/completion/nested.py
parentInitial commit. (diff)
downloadprompt-toolkit-0a3e0a12a3f6453f8e5b1cffb2f7e1e619420f44.tar.xz
prompt-toolkit-0a3e0a12a3f6453f8e5b1cffb2f7e1e619420f44.zip
Adding upstream version 3.0.36.upstream/3.0.36upstream
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
Diffstat (limited to 'src/prompt_toolkit/completion/nested.py')
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+"""
+Nestedcompleter for completion of hierarchical data structures.
+"""
+from typing import Any, Dict, Iterable, Mapping, Optional, Set, Union
+
+from prompt_toolkit.completion import CompleteEvent, Completer, Completion
+from prompt_toolkit.completion.word_completer import WordCompleter
+from prompt_toolkit.document import Document
+
+__all__ = ["NestedCompleter"]
+
+# NestedDict = Mapping[str, Union['NestedDict', Set[str], None, Completer]]
+NestedDict = Mapping[str, Union[Any, Set[str], None, Completer]]
+
+
+class NestedCompleter(Completer):
+ """
+ Completer which wraps around several other completers, and calls any the
+ one that corresponds with the first word of the input.
+
+ By combining multiple `NestedCompleter` instances, we can achieve multiple
+ hierarchical levels of autocompletion. This is useful when `WordCompleter`
+ is not sufficient.
+
+ If you need multiple levels, check out the `from_nested_dict` classmethod.
+ """
+
+ def __init__(
+ self, options: Dict[str, Optional[Completer]], ignore_case: bool = True
+ ) -> None:
+
+ self.options = options
+ self.ignore_case = ignore_case
+
+ def __repr__(self) -> str:
+ return f"NestedCompleter({self.options!r}, ignore_case={self.ignore_case!r})"
+
+ @classmethod
+ def from_nested_dict(cls, data: NestedDict) -> "NestedCompleter":
+ """
+ Create a `NestedCompleter`, starting from a nested dictionary data
+ structure, like this:
+
+ .. code::
+
+ data = {
+ 'show': {
+ 'version': None,
+ 'interfaces': None,
+ 'clock': None,
+ 'ip': {'interface': {'brief'}}
+ },
+ 'exit': None
+ 'enable': None
+ }
+
+ The value should be `None` if there is no further completion at some
+ point. If all values in the dictionary are None, it is also possible to
+ use a set instead.
+
+ Values in this data structure can be a completers as well.
+ """
+ options: Dict[str, Optional[Completer]] = {}
+ for key, value in data.items():
+ if isinstance(value, Completer):
+ options[key] = value
+ elif isinstance(value, dict):
+ options[key] = cls.from_nested_dict(value)
+ elif isinstance(value, set):
+ options[key] = cls.from_nested_dict({item: None for item in value})
+ else:
+ assert value is None
+ options[key] = None
+
+ return cls(options)
+
+ def get_completions(
+ self, document: Document, complete_event: CompleteEvent
+ ) -> Iterable[Completion]:
+ # Split document.
+ text = document.text_before_cursor.lstrip()
+ stripped_len = len(document.text_before_cursor) - len(text)
+
+ # If there is a space, check for the first term, and use a
+ # subcompleter.
+ if " " in text:
+ first_term = text.split()[0]
+ completer = self.options.get(first_term)
+
+ # If we have a sub completer, use this for the completions.
+ if completer is not None:
+ remaining_text = text[len(first_term) :].lstrip()
+ move_cursor = len(text) - len(remaining_text) + stripped_len
+
+ new_document = Document(
+ remaining_text,
+ cursor_position=document.cursor_position - move_cursor,
+ )
+
+ yield from completer.get_completions(new_document, complete_event)
+
+ # No space in the input: behave exactly like `WordCompleter`.
+ else:
+ completer = WordCompleter(
+ list(self.options.keys()), ignore_case=self.ignore_case
+ )
+ yield from completer.get_completions(document, complete_event)