File size: 5,558 Bytes
dfe1d91 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 | import difflib
import re
def get_word_positions(text):
positions = []
for m in re.finditer(r'\S+', text):
positions.append((m.group(), m.start(), m.end()))
return positions
class OffsetMapper:
def __init__(self, original, modified):
self.original = original
self.modified = modified
self.mapping = []
self._build_mapping()
def _build_mapping(self):
s = difflib.SequenceMatcher(None, self.original, self.modified)
for tag, i1, i2, j1, j2 in s.get_opcodes():
self.mapping.append((j1, j2, i1, i2))
def map_offset(self, mod_offset):
for j1, j2, i1, i2 in self.mapping:
if j1 <= mod_offset <= j2:
if j2 == j1:
return i1
ratio = (mod_offset - j1) / (j2 - j1)
return int(i1 + ratio * (i2 - i1))
return len(self.original)
def get_word_diffs(original, corrected):
orig_words = get_word_positions(original)
corr_words = get_word_positions(corrected)
s = difflib.SequenceMatcher(None, [w[0] for w in orig_words], [w[0] for w in corr_words])
suggestions = []
for tag, i1, i2, j1, j2 in s.get_opcodes():
if tag == 'replace':
if i1 < len(orig_words) and i2 - 1 < len(orig_words):
start_char = orig_words[i1][1]
end_char = orig_words[i2-1][2]
suggestions.append({
'start': start_char,
'end': end_char,
'original': original[start_char:end_char],
'correction': " ".join([w[0] for w in corr_words[j1:j2]]),
'type': 'generic'
})
elif tag == 'delete':
if i1 < len(orig_words) and i2 - 1 < len(orig_words):
start_char = orig_words[i1][1]
end_char = orig_words[i2-1][2]
suggestions.append({
'start': start_char,
'end': end_char,
'original': original[start_char:end_char],
'correction': '',
'type': 'generic'
})
elif tag == 'insert':
pos = orig_words[i1][1] if i1 < len(orig_words) else len(original)
suggestions.append({
'start': pos,
'end': pos,
'original': '',
'correction': " ".join([w[0] for w in corr_words[j1:j2]]),
'type': 'generic'
})
return suggestions
def test():
original_text = "قال محمد: علي أننا حققنا نجاحا كبيرا في المشروع رغم الصعوباالصعوبات...."
spelling_text = "قال محمد علي أننا حققنا نجاحا كبيرا في المشروع رغم الصعوباالصعوبات...."
grammar_text = "قال محمد علي أننا حققنا نجاحا كبيرا في المشروع رغم الصعوبات..."
punct_text = "قال محمد علي: أننا حققنا نجاحا كبيرا في المشروع رغم الصعوبات...."
suggestions = []
mappers = []
# SPELLING
suggestions.append({
'start': 4,
'end': 9,
'original': "محمد:",
'correction': "محمد",
'type': 'spelling'
})
mappers.append(OffsetMapper(original_text, spelling_text))
def map_range_to_original(start, end):
curr_start, curr_end = start, end
for mapper in reversed(mappers):
curr_start = mapper.map_offset(curr_start)
curr_end = mapper.map_offset(curr_end)
return curr_start, curr_end
# GRAMMAR
diffs = get_word_diffs(spelling_text, grammar_text)
for d in diffs:
orig_start, orig_end = map_range_to_original(d['start'], d['end'])
suggestions.append({
'start': orig_start,
'end': orig_end,
'original': original_text[orig_start:orig_end],
'correction': d['correction'],
'type': 'grammar'
})
mappers.append(OffsetMapper(spelling_text, grammar_text))
# PUNCTUATION
diffs = get_word_diffs(grammar_text, punct_text)
for d in diffs:
orig_start, orig_end = map_range_to_original(d['start'], d['end'])
suggestions.append({
'start': orig_start,
'end': orig_end,
'original': original_text[orig_start:orig_end],
'correction': d['correction'],
'type': 'punctuation'
})
print("SUGGESTIONS BEFORE RESOLUTION:")
for s in suggestions:
print(s)
PRIORITY = {'grammar': 3, 'punctuation': 2, 'spelling': 1, 'autocomplete': 0}
suggestions.sort(key=lambda s: PRIORITY.get(s['type'], 0), reverse=True)
claimed_ranges = []
resolved = []
for s in suggestions:
s_start, s_end = s['start'], s['end']
overlaps = False
for (c_start, c_end, c_type) in claimed_ranges:
if s_start < c_end and s_end > c_start:
overlaps = True
print(f"Overlap detected! {s['type']} [{s_start}:{s_end}] overlaps with {c_type} [{c_start}:{c_end}]")
break
if not overlaps:
resolved.append(s)
claimed_ranges.append((s_start, s_end, s['type']))
else:
print(f"[OVERLAP] Dropped {s['type']} [{s_start}:{s_end}] '{s.get('original','')}'")
if __name__ == "__main__":
test()
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