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Diffstat (limited to 'src/prompt_toolkit/completion/fuzzy_completer.py')
| -rw-r--r-- | src/prompt_toolkit/completion/fuzzy_completer.py | 213 |
1 files changed, 213 insertions, 0 deletions
diff --git a/src/prompt_toolkit/completion/fuzzy_completer.py b/src/prompt_toolkit/completion/fuzzy_completer.py new file mode 100644 index 0000000..25ea892 --- /dev/null +++ b/src/prompt_toolkit/completion/fuzzy_completer.py @@ -0,0 +1,213 @@ +from __future__ import annotations + +import re +from typing import Callable, Iterable, NamedTuple + +from prompt_toolkit.document import Document +from prompt_toolkit.filters import FilterOrBool, to_filter +from prompt_toolkit.formatted_text import AnyFormattedText, StyleAndTextTuples + +from .base import CompleteEvent, Completer, Completion +from .word_completer import WordCompleter + +__all__ = [ + "FuzzyCompleter", + "FuzzyWordCompleter", +] + + +class FuzzyCompleter(Completer): + """ + Fuzzy completion. + This wraps any other completer and turns it into a fuzzy completer. + + If the list of words is: ["leopard" , "gorilla", "dinosaur", "cat", "bee"] + Then trying to complete "oar" would yield "leopard" and "dinosaur", but not + the others, because they match the regular expression 'o.*a.*r'. + Similar, in another application "djm" could expand to "django_migrations". + + The results are sorted by relevance, which is defined as the start position + and the length of the match. + + Notice that this is not really a tool to work around spelling mistakes, + like what would be possible with difflib. The purpose is rather to have a + quicker or more intuitive way to filter the given completions, especially + when many completions have a common prefix. + + Fuzzy algorithm is based on this post: + https://blog.amjith.com/fuzzyfinder-in-10-lines-of-python + + :param completer: A :class:`~.Completer` instance. + :param WORD: When True, use WORD characters. + :param pattern: Regex pattern which selects the characters before the + cursor that are considered for the fuzzy matching. + :param enable_fuzzy: (bool or `Filter`) Enabled the fuzzy behavior. For + easily turning fuzzyness on or off according to a certain condition. + """ + + def __init__( + self, + completer: Completer, + WORD: bool = False, + pattern: str | None = None, + enable_fuzzy: FilterOrBool = True, + ) -> None: + assert pattern is None or pattern.startswith("^") + + self.completer = completer + self.pattern = pattern + self.WORD = WORD + self.pattern = pattern + self.enable_fuzzy = to_filter(enable_fuzzy) + + def get_completions( + self, document: Document, complete_event: CompleteEvent + ) -> Iterable[Completion]: + if self.enable_fuzzy(): + return self._get_fuzzy_completions(document, complete_event) + else: + return self.completer.get_completions(document, complete_event) + + def _get_pattern(self) -> str: + if self.pattern: + return self.pattern + if self.WORD: + return r"[^\s]+" + return "^[a-zA-Z0-9_]*" + + def _get_fuzzy_completions( + self, document: Document, complete_event: CompleteEvent + ) -> Iterable[Completion]: + word_before_cursor = document.get_word_before_cursor( + pattern=re.compile(self._get_pattern()) + ) + + # Get completions + document2 = Document( + text=document.text[: document.cursor_position - len(word_before_cursor)], + cursor_position=document.cursor_position - len(word_before_cursor), + ) + + inner_completions = list( + self.completer.get_completions(document2, complete_event) + ) + + fuzzy_matches: list[_FuzzyMatch] = [] + + if word_before_cursor == "": + # If word before the cursor is an empty string, consider all + # completions, without filtering everything with an empty regex + # pattern. + fuzzy_matches = [_FuzzyMatch(0, 0, compl) for compl in inner_completions] + else: + pat = ".*?".join(map(re.escape, word_before_cursor)) + pat = f"(?=({pat}))" # lookahead regex to manage overlapping matches + regex = re.compile(pat, re.IGNORECASE) + for compl in inner_completions: + matches = list(regex.finditer(compl.text)) + if matches: + # Prefer the match, closest to the left, then shortest. + best = min(matches, key=lambda m: (m.start(), len(m.group(1)))) + fuzzy_matches.append( + _FuzzyMatch(len(best.group(1)), best.start(), compl) + ) + + def sort_key(fuzzy_match: _FuzzyMatch) -> tuple[int, int]: + "Sort by start position, then by the length of the match." + return fuzzy_match.start_pos, fuzzy_match.match_length + + fuzzy_matches = sorted(fuzzy_matches, key=sort_key) + + for match in fuzzy_matches: + # Include these completions, but set the correct `display` + # attribute and `start_position`. + yield Completion( + text=match.completion.text, + start_position=match.completion.start_position + - len(word_before_cursor), + # We access to private `_display_meta` attribute, because that one is lazy. + display_meta=match.completion._display_meta, + display=self._get_display(match, word_before_cursor), + style=match.completion.style, + ) + + def _get_display( + self, fuzzy_match: _FuzzyMatch, word_before_cursor: str + ) -> AnyFormattedText: + """ + Generate formatted text for the display label. + """ + + def get_display() -> AnyFormattedText: + m = fuzzy_match + word = m.completion.text + + if m.match_length == 0: + # No highlighting when we have zero length matches (no input text). + # In this case, use the original display text (which can include + # additional styling or characters). + return m.completion.display + + result: StyleAndTextTuples = [] + + # Text before match. + result.append(("class:fuzzymatch.outside", word[: m.start_pos])) + + # The match itself. + characters = list(word_before_cursor) + + for c in word[m.start_pos : m.start_pos + m.match_length]: + classname = "class:fuzzymatch.inside" + if characters and c.lower() == characters[0].lower(): + classname += ".character" + del characters[0] + + result.append((classname, c)) + + # Text after match. + result.append( + ("class:fuzzymatch.outside", word[m.start_pos + m.match_length :]) + ) + + return result + + return get_display() + + +class FuzzyWordCompleter(Completer): + """ + Fuzzy completion on a list of words. + + (This is basically a `WordCompleter` wrapped in a `FuzzyCompleter`.) + + :param words: List of words or callable that returns a list of words. + :param meta_dict: Optional dict mapping words to their meta-information. + :param WORD: When True, use WORD characters. + """ + + def __init__( + self, + words: list[str] | Callable[[], list[str]], + meta_dict: dict[str, str] | None = None, + WORD: bool = False, + ) -> None: + self.words = words + self.meta_dict = meta_dict or {} + self.WORD = WORD + + self.word_completer = WordCompleter( + words=self.words, WORD=self.WORD, meta_dict=self.meta_dict + ) + + self.fuzzy_completer = FuzzyCompleter(self.word_completer, WORD=self.WORD) + + def get_completions( + self, document: Document, complete_event: CompleteEvent + ) -> Iterable[Completion]: + return self.fuzzy_completer.get_completions(document, complete_event) + + +class _FuzzyMatch(NamedTuple): + match_length: int + start_pos: int + completion: Completion |