#!/usr/bin/env python # encoding: utf-8 """ process.py Copyright (c) 2011 Adam Cohen 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. """ import itertools from . import fuzz from . import utils def extract(query, choices, processor=None, scorer=None, limit=5): """Find best matches in a list or dictionary of choices, return a list of tuples containing the match and it's score. If a dictionery is used, also returns the key for each match. Arguments: query -- an object representing the thing we want to find choices -- a list or dictionary of objects we are attempting to extract values from. The dictionary should consist of {key: str} pairs. scorer -- f(OBJ, QUERY) --> INT. We will return the objects with the highest score by default, we use score.WRatio() and both OBJ and QUERY should be strings processor -- f(OBJ_A) --> OBJ_B, where the output is an input to scorer for example, "processor = lambda x: x[0]" would return the first element in a collection x (of, say, strings) this would then be used in the scoring collection by default, we use utils.full_process() """ if choices is None: return [] try: if len(choices) == 0: return [] except TypeError: pass # default, turn whatever the choice is into a workable string if processor is None: processor = lambda x: utils.full_process(x) # default: wratio if scorer is None: scorer = fuzz.WRatio sl = list() if isinstance(choices, dict): for key, choice in choices.items(): processed = processor(choice) score = scorer(query, processed) tuple = (choice, score, key) sl.append(tuple) else: for choice in choices: processed = processor(choice) score = scorer(query, processed) tuple = (choice, score) sl.append(tuple) sl.sort(key=lambda i: i[1], reverse=True) return sl[:limit] def extractBests(query, choices, processor=None, scorer=None, score_cutoff=0, limit=5): """Find best matches above a score in a list of choices, return a list of tuples containing the match and it's score. Convenience method which returns the choices with best scores, see extract() for full arguments list Optional parameter: score_cutoff. If the choice has a score of less than or equal to score_cutoff it will not be included on result list """ best_list = extract(query, choices, processor, scorer, limit) if len(best_list) > 0: return list(itertools.takewhile(lambda x: x[1] >= score_cutoff, best_list)) else: return [] def extractOne(query, choices, processor=None, scorer=None, score_cutoff=0): """Find the best match above a score in a list of choices, return a tuple containing the match and it's score if it's above the treshold or None. Convenience method which returns the single best choice, see extract() for full arguments list Optional parameter: score_cutoff. If the best choice has a score of less than or equal to score_cutoff we will return none (intuition: not a good enough match) """ best_list = extract(query, choices, processor, scorer, limit=1) if len(best_list) > 0: best = best_list[0] if best[1] >= score_cutoff: return best else: return None else: return None