class RecommendationFinder:
def __init__(self, normalizer=None):
self.normalizer = normalizer or (lambda x: x)
def find_and_format(self, name, candidates, message, max_matches=10,
check_missing_argument_separator=False):
recommendations = self.find(name, candidates, max_matches)
if recommendations:
return self.format(message, recommendations)
if check_missing_argument_separator and name:
recommendation = self._check_missing_argument_separator(name, candidates)
if recommendation:
return f'{message} {recommendation}'
return message
def find(self, name, candidates, max_matches=10):
"""Return a list of close matches to `name` from `candidates`."""
if not name or not candidates:
return []
norm_name = self.normalizer(name)
norm_candidates = self._get_normalized_candidates(candidates)
cutoff = self._calculate_cutoff(norm_name)
norm_matches = difflib.get_close_matches(
norm_name, norm_candidates, n=max_matches, cutoff=cutoff
)
return self._get_original_candidates(norm_matches, norm_candidates)
def format(self, message, recommendations):
"""Add recommendations to the given message.
The recommendation string looks like::
<message> Did you mean:
<recommendations[0]>
<recommendations[1]>
<recommendations[2]>
"""
if recommendations:
message += " Did you mean:"
for rec in recommendations:
message += "\n %s" % rec
return message
def _get_normalized_candidates(self, candidates):
norm_candidates = {}
for cand in sorted(candidates):
norm = self.normalizer(cand)
norm_candidates.setdefault(norm, []).append(cand)
return norm_candidates
def _get_original_candidates(self, norm_matches, norm_candidates):
candidates = []
for match in norm_matches:
candidates.extend(norm_candidates[match])
return candidates
def _calculate_cutoff(self, string, min_cutoff=0.5, max_cutoff=0.85, step=0.03):
"""Calculate a cutoff depending on string length.
Default values determined by manual tuning until the results "look right".
"""
cutoff = min_cutoff + len(string) * step
return min(cutoff, max_cutoff)
def _check_missing_argument_separator(self, name, candidates):
name = self.normalizer(name)
candidates = self._get_normalized_candidates(candidates)
matches = [c for c in candidates if name.startswith(c)]
if not matches:
return None
candidates = self._get_original_candidates(matches, candidates)
return (f"Did you try using keyword {seq2str(candidates, lastsep=' or ')} "
f"and forgot to use enough whitespace between keyword and arguments?")