def adapt_translation(source, matches = []):
""" Translate new messages by adapting an old translation """
# Start with a null result
result = None, None
# Start by considering the operation not safe
# True: translated
# False: fuzzy
# None: untranslated
safe = None
# Iterate over the matches
for match_source, match_translation in matches:
# Consider the operation is safe for the moment
safe = True
# The accepted operations
operations = {}
# Split the texts by using the Splitter
source_list = patterns.split(source)
# print 'Source list', source_list
# Split the matching source text by using the Splitter
match_source_list = patterns.split(match_source)
# print
# print 'Match source list', match_source_list
# The sequence matcher
seq = SequenceMatcher(None, match_source_list, source_list)
# Build the result
for tag, i1, i2, j1, j2 in seq.get_opcodes():
from_seq = match_source_list[i1:i2]
to_seq = source_list[j1:j2]
# print 'OPCODE:', tag, i1, i2, j1, j2, from_seq, to_seq
if tag == 'replace':
# Accept replacement of several genera
if (check_sequence(from_seq, genera = ['placeholder', 'branding', 'syntax']) and \
check_sequence(to_seq, genera = ['placeholder', 'branding', 'syntax'])) or \
(check_sequence(from_seq, genera = ['number']) and \
check_sequence(to_seq, genera = ['number'])) or \
(check_sequence(from_seq, genera = ['fixed']) and \
check_sequence(to_seq, genera = ['fixed'])) or \
(check_sequence(from_seq, genera = ['punctuation']) and \
check_sequence(to_seq, genera = ['punctuation'])):
# Check if the operation is safe
if not check_sequence_operations(operations, from_seq, to_seq):
safe = None
break
else:
safe = None
break
elif tag == 'delete':
# Accept deletion of several genera
if check_sequence(from_seq, genera = ['placeholder',
'branding',
'syntax',
'number',
'punctuation',
'control']):
# Check if the operation is safe
if not check_sequence_operations(operations, from_seq, []):
safe = None
break
else:
safe = None
break
elif tag == 'equal':
# Check the letter case of text/words in equal sequences
for from_word, to_word in zip (from_seq, to_seq):
if from_word.genus == 'text':
if from_word.key(ignorecase = False) != to_word.key(ignorecase = False):
safe = False
break
elif tag == 'insert':
# Accept insertion of several genera only
if check_sequence(to_seq, genera = ['placeholder',
'branding',
'syntax',
'number',
'punctuation',
'control']):
if i1 == 0:
# Insert at begining
from_item = patterns.SplitNode(text = '', genus = '~', species = '^')
elif i1 == len(match_source_list):
# Insert at end
from_item = patterns.SplitNode(text = '', genus = '~', species = '$')
else:
# No other insertion allowed
safe = None
break
# Check if the operation is safe
if not check_sequence_operations(operations, [from_item,], to_seq):
safe = None
break
else:
# Unaccepted genera
safe = None
break
else:
# Unkonwn operation
safe = None
break
# print 'SAFE:', safe
# Check if we are safe
if safe is None:
# We are not, try another match
continue
# We can now operate on translation
# print 'OPERATIONS:', operations
# Split the matching translation text by using the Splitter
match_translation_list = patterns.split(match_translation)
# Start with a result translation list based on the matching list
translation_list = match_translation_list[:]
# Get the operations list
ops = operations.items()
# Start with an empty list of failed operations
failed = []
# Do not extrapolate from the start
extrapolate = False
# Continue to process each operation as long as there are any
# operations left
while ops:
# print 'OPS', ops
# Iterate over operations
for op, count in ops:
# print 'OP:', op, count
# Get the from and to
from_item, to_item = op
# Convert back the tuples into lists
from_seq = list(from_item)
to_seq = list(to_item)
# Check if 'from' is emty, which means insertion and this is
# allowd only at the end (append)
if len(from_seq) == 1 and from_seq[0].genus == '~':
if from_seq[0].species == '$':
translation_list.extend(to_seq)
elif from_seq[0].species == '^':
to_seq.extend(translation_list)
translation_list = to_seq[:]
else:
# Get the number of the occurences of this operation in
# translation we are building
from_item_count = sublist_count(from_seq, translation_list, ignore = ['space'])
# Check if the occurrences remain the same
if from_item_count != count:
# Check if we should push the operation a little, if the
# count means 'all' anyway
if extrapolate and sublist_count(from_seq, match_source_list, ignore = ['space']) == count:
# We can operate on all of them, but the result will be
# fuzzy at best
safe = False
else:
# The number of occurrences is not the same, we can not
# extrapolate or we can extrapolate but the count does
# not mean 'all', so fail this operation
failed.append((op, count))
continue
# Adapt the translation if safe
if safe is not None:
# Get the sub-list positions
positions = sublist_positions(from_seq, translation_list, ignore = ['space'])
# Replace original sequences with constructed
# sequences, in reversed order
for start, end in reversed(positions):
translation_list[start:end] = to_seq
# Check if there are any failed operations
if failed:
# print 'FAILED', failed
# There are failed operations, check if all of them have failed
if ops == failed:
# Check if we have tried extrapolating too
if not extrapolate:
# Let's try to extrapolate
extrapolate = True
else:
# All the operations have failed, even in
# extrapolation, we are not safe at all
ops = []
# If safe was True (first iteration), switch to None,
# if safe was False (later iteration) or None, keep it
if safe:
safe = None
else:
# Only some operations have failed, try them again
ops = failed[:]
failed = []
safe = False
else:
# There are no failed operations, we can go on with current
# safety level
ops = []
# Check the result of the previous match
if (result[0] is None and safe is not None) or (not result[0] and safe):
# If there is no previous match or we are safe now and the previous
# match was not, create a new result
result = (safe, patterns.join(translation_list))
if safe:
# We can break if we are safe, no more matches are needed
break
# Return the result
return result
