def lev(request):
original_word = request.GET.get('original_word', '')
new_word = request.GET.get('new_word', '')
if len(original_word) == 0 or len(new_word) == 0:
data = {
'status': 'error',
'message': "You must supply both 'original_word' & 'new_word' as GET params.",
'description': """It's Levenshtein-As-A-Service. You know, for the lulz.
Please direct all VC monies to Daniel Lindsley.""",
}
else:
data = {
'status': 'success',
'distance': pylev.levenschtein(original_word, new_word),
}
return Response(json.dumps(data), content_type='application/json')
def traverseDir(self, root):
for dirName, subdirList, fileList in os.walk(root):
mov = next(
(x for x in fileList if any(os.path.splitext(x)[1] == mov_type for mov_type in mov_types)), None
) # 2 and more?
self.mov.Text = mov
if mov is None:
continue
if any(filter(lambda file: file == "folder.jpg", fileList)):
continue
# ifilter(lambda t: all(f(t) for f in [folder_filter, mov_filter]), fileList)
_fileList = filter(lambda file: os.path.splitext(file)[1] == ".jpg", fileList)
if _fileList == []:
continue
fileDict = {k: pylev.levenschtein(k, mov) for k in _fileList}
_fileList = sorted(fileDict, key=fileDict.__getitem__)
self.lv.Items.Clear()
self.loc.Text = dirName
map(lambda x: self.lv.Items.Add(x), _fileList)
finished = yield "%s/%s" % (dirName, _fileList[0])
def traverseDir(self, root):
for dirName, subdirList, fileList in os.walk(root):
mov = next((x for x in fileList if any(
os.path.splitext(x)[1] == mov_type for mov_type in mov_types)),
None) # 2 and more?
self.mov.Text = mov
if mov is None:
continue
if any(filter(lambda file: file == 'folder.jpg', fileList)):
continue
#ifilter(lambda t: all(f(t) for f in [folder_filter, mov_filter]), fileList)
_fileList = filter(
lambda file: os.path.splitext(file)[1] == '.jpg', fileList)
if _fileList == []:
continue
fileDict = {k: pylev.levenschtein(k, mov) for k in _fileList}
_fileList = sorted(fileDict, key=fileDict.__getitem__)
self.lv.Items.Clear()
self.loc.Text = dirName
map(lambda x: self.lv.Items.Add(x), _fileList)
finished = yield '%s/%s' % (dirName, _fileList[0])
i = 0
lev_max = 1
levenstein_distance = []
for idx, row in data_train.iterrows():
provider_current = row['provider_lower']
count_current = row['count']
data_train_current = data_train[data_train['provider_lower'] !=
row['provider_lower']]['provider_lower']
closest_word = difflib.get_close_matches(provider_current,
data_train_current,
n=1,
cutoff=0.6)
if len(closest_word) > 0:
match = closest_word[0]
distance = levenschtein(provider_current, match)
if distance <= lev_max:
count_closest = data_train[data_train['provider_lower'] ==
match]['count'].item()
if count_closest > count_current:
#print "replace " + provider_current + " by " + match + " ( " + str(count_current) + " , " + str(count_closest) + ")"
idx = data_train[data_train['provider_lower'] ==
provider_current].index
data_train.loc[idx, 'replacing'] = match
i = i + 1
if count_closest == count_current:
i = i + 1
idx = data_train[data_train['provider_lower'] ==
provider_current].index
data_train.loc[idx, 'replacing'] = match
idx = data_train[data_train['provider_lower'] == match].index