Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more.
This report presents the forensic synthetic code analysis of sloria/TextBlob, a Python project with 9,540 GitHub stars. SynthScan v2.0 examined 41,263 lines of code across 58 source files, recording 134 pattern matches distributed across 9 syntactic categories. The overall adjusted score of 3.4 places this repository in the Likely human-written band.
The scanner applied 160+ deterministic lexical heuristics, multi-line block detectors, abstract syntax tree depth profilers, and a cross-file Jaccard similarity matrix to construct a statistically normalised synthetic code estimate. All matches are individually weighted by severity coefficient and contextual multiplier before summation, and the resulting headline score is temporally discounted to account for the repository's development history relative to the commercial emergence of large language model coding tooling (November 2022 onward).
Longitudinal tracking requires multiple scan runs. Once this repository is re-scanned after new commits land, this chart will visualise how the synthetic code signal evolves over time — enabling you to detect whether AI authorship is growing, stabilising, or being actively corrected by human engineers.
Classifies detected patterns by their diagnostic confidence and structural impact. CRITICAL patterns (coefficient 10) represent definitive synthetic signatures — hallucinated imports, explicit LLM attribution metadata — virtually never produced by human authors. HIGH (5) indicates strong structural tells such as cross-file repetition or cross-linguistic idioms. MEDIUM (2) covers recognisable conversational padding and AI-specific vocabulary. LOW (1) captures subtle indicators like tautological comments and generic boilerplate that require density to carry independent signal.
This horizontal bar chart decomposes the repository's raw synthetic code score by top-level directory, allowing you to pinpoint precisely which modules or components carry the highest AI authorship density. Directories with disproportionately high scores relative to their size warrant targeted manual review: concentrated AI signatures often trace back to mass-generated configuration layers, auto-ported test suites, LLM-scaffolded boilerplate classes, or entire subsystems authored under heavy copilot assistance. Use this view to prioritise your human code-review effort.
The scanner identified 134 distinct pattern matches across 9 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a statistically significant AI authorship indicator. Expand any category row to inspect the individual file paths, line numbers, code snippets, and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.
Reading the findings table: The Severity column indicates the diagnostic confidence level (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — comment-context matches receive a ×1.5 weight because LLMs systematically over-annotate. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier as dense clusters constitute far stronger evidence of synthetic authorship than isolated hits.
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | tests/test_decorators.py | 15 | def test_decorator_raises_missing_corpus_exception(): | CODE |
| LOW | tests/test_tokenizers.py | 69 | def test_tokenize_with_multiple_punctuation(self): | CODE |
| LOW⚡ | tests/test_inflect.py | 13 | def s_singular_pluralize_test(self): | CODE |
| LOW⚡ | tests/test_inflect.py | 16 | def s_singular_singularize_test(self): | CODE |
| LOW⚡ | tests/test_inflect.py | 19 | def diagnoses_singularize_test(self): | CODE |
| LOW | tests/test_inflect.py | 37 | def test_pluralize_already_plural_jeans(self): | CODE |
| LOW | tests/test_inflect.py | 52 | def test_all_singular_irregular(self): | CODE |
| LOW | tests/test_np_extractor.py | 38 | def test_filter_insignificant(self): | STRING |
| LOW | tests/test_np_extractor.py | 53 | def test_cannot_instantiate_incomplete_extractor(): | CODE |
| LOW | tests/test_formats.py | 34 | def test_delimiter_defaults_to_comma(self): | CODE |
| LOW | tests/test_formats.py | 61 | def test_read_from_file_object(self): | CODE |
| LOW | tests/test_formats.py | 76 | def test_read_from_file_object(self): | CODE |
| LOW | tests/test_taggers.py | 65 | def test_cannot_instantiate_incomplete_tagger(): | CODE |
| LOW⚡ | tests/test_classifiers.py | 118 | def test_show_informative_features(self): | CODE |
| LOW⚡ | tests/test_classifiers.py | 121 | def test_informative_features(self): | CODE |
| LOW⚡ | tests/test_classifiers.py | 126 | def test_custom_feature_extractor(self): | CODE |
| LOW⚡ | tests/test_classifiers.py | 179 | def test_data_with_no_available_format(self): | CODE |
| LOW⚡ | tests/test_classifiers.py | 186 | def test_accuracy_on_a_csv_file(self): | CODE |
| LOW⚡ | tests/test_classifiers.py | 191 | def test_accuracy_on_json_file(self): | CODE |
| LOW⚡ | tests/test_classifiers.py | 343 | def test_basic_extractor_with_list(): | CODE |
| LOW⚡ | tests/test_classifiers.py | 351 | def test_contains_extractor_with_string(): | CODE |
| LOW⚡ | tests/test_classifiers.py | 360 | def test_contains_extractor_with_list(): | CODE |
| LOW | tests/test_classifiers.py | 59 | def test_raises_value_error_without_nltk_class(self): | CODE |
| LOW | tests/test_classifiers.py | 85 | def test_classify_a_list_of_words(self): | CODE |
| LOW | tests/test_classifiers.py | 89 | def test_train_from_lists_of_words(self): | CODE |
| LOW | tests/test_classifiers.py | 138 | def test_init_with_csv_file_without_format_specifier(self): | CODE |
| LOW | tests/test_classifiers.py | 152 | def test_init_with_json_file_without_format_specifier(self): | CODE |
| LOW | tests/test_classifiers.py | 159 | def test_init_with_custom_format(self): | CODE |
| LOW | tests/test_classifiers.py | 203 | def test_init_with_bad_format_specifier(self): | CODE |
| LOW | tests/test_classifiers.py | 233 | def test_custom_feature_extractor(self): | CODE |
| LOW | tests/test_classifiers.py | 378 | def test_get_words_from_dataset(): | CODE |
| LOW⚡ | tests/test_blob.py | 363 | def test_blob_with_no_sentences(self): | CODE |
| LOW⚡ | tests/test_blob.py | 455 | def test_pos_tags_includes_one_letter_articles(self): | CODE |
| LOW⚡ | tests/test_blob.py | 460 | def test_np_extractor_defaults_to_fast_tagger(self): | CODE |
| LOW⚡ | tests/test_blob.py | 465 | def test_np_extractor_is_shared_among_instances(self): | CODE |
| LOW⚡ | tests/test_blob.py | 471 | def test_can_use_different_np_extractors(self): | CODE |
| LOW⚡ | tests/test_blob.py | 478 | def test_can_use_different_sentanalyzer(self): | CODE |
| LOW⚡ | tests/test_blob.py | 487 | def test_can_get_subjectivity_and_polarity_with_different_analyzer(self): | CODE |
| LOW⚡ | tests/test_blob.py | 493 | def test_pos_tagger_defaults_to_pattern(self): | CODE |
| LOW⚡ | tests/test_blob.py | 497 | def test_pos_tagger_is_shared_among_instances(self): | CODE |
| LOW⚡ | tests/test_blob.py | 502 | def test_can_use_different_pos_tagger(self): | CODE |
| LOW⚡ | tests/test_blob.py | 508 | def test_can_pass_np_extractor_to_constructor(self): | CODE |
| LOW⚡ | tests/test_blob.py | 565 | def test_using_indices_for_slicing(self): | CODE |
| LOW⚡ | tests/test_blob.py | 571 | def test_indices_with_only_one_sentences(self): | CODE |
| LOW⚡ | tests/test_blob.py | 576 | def test_indices_with_multiple_puncutations(self): | CODE |
| LOW⚡ | tests/test_blob.py | 739 | def test_tokenizer_defaults_to_word_tokenizer(self): | CODE |
| LOW⚡ | tests/test_blob.py | 745 | def test_can_use_an_different_tokenizer(self): | CODE |
| LOW⚡ | tests/test_blob.py | 750 | def test_words_uses_custom_tokenizer(self): | CODE |
| LOW | tests/test_blob.py | 221 | def test_words_are_word_objects(self): | CODE |
| LOW | tests/test_blob.py | 340 | def test_senences_with_space_before_punctuation(self): | CODE |
| LOW | tests/test_blob.py | 345 | def test_sentiment_of_foreign_text(self): | CODE |
| LOW | tests/test_blob.py | 419 | def test_words_includes_apostrophes_in_contractions(self): | CODE |
| LOW | tests/test_blob.py | 666 | def test_sentences_after_concatenation(self): | CODE |
| LOW | tests/test_blob.py | 693 | def test_sentiment_of_emoticons(self): | CODE |
| LOW | tests/test_blob.py | 727 | def test_words_are_word_objects(self): | CODE |
| LOW | tests/test_blob.py | 765 | def test_tags_uses_custom_tokenizer(self): | CODE |
| LOW | tests/test_blob.py | 779 | def test_tags_with_custom_tokenizer_and_tagger(self): | CODE |
| LOW | tests/test_blob.py | 832 | def test_passing_bad_init_params(self): | CODE |
| LOW | tests/test_blob.py | 854 | def test_classify_without_classifier(self): | CODE |
| LOW | tests/test_blob.py | 859 | def test_word_string_type_after_pos_tags_is_str(self): | CODE |
| 7 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | src/textblob/np_extractors.py | 11 | CODE | |
| LOW | src/textblob/np_extractors.py | 12 | CODE | |
| LOW | src/textblob/np_extractors.py | 12 | CODE | |
| LOW | src/textblob/__init__.py | 1 | CODE | |
| LOW | src/textblob/__init__.py | 1 | CODE | |
| LOW | src/textblob/__init__.py | 1 | CODE | |
| LOW | src/textblob/__init__.py | 1 | CODE | |
| LOW | src/textblob/__init__.py | 1 | CODE | |
| LOW | src/textblob/inflect.py | 11 | CODE | |
| LOW | src/textblob/inflect.py | 11 | CODE | |
| LOW | src/textblob/parsers.py | 10 | CODE | |
| LOW | src/textblob/parsers.py | 11 | CODE | |
| LOW | src/textblob/taggers.py | 11 | CODE | |
| LOW | src/textblob/taggers.py | 12 | CODE | |
| LOW | src/textblob/taggers.py | 12 | CODE | |
| LOW | src/textblob/utils.py | 1 | CODE | |
| LOW | src/textblob/formats.py | 24 | CODE | |
| LOW | src/textblob/sentiments.py | 11 | CODE | |
| LOW | src/textblob/sentiments.py | 12 | CODE | |
| LOW | src/textblob/sentiments.py | 12 | CODE | |
| LOW | src/textblob/sentiments.py | 12 | CODE | |
| LOW | src/textblob/sentiments.py | 12 | CODE | |
| LOW | src/textblob/base.py | 8 | CODE | |
| LOW | src/textblob/decorators.py | 3 | CODE | |
| LOW | src/textblob/en/inflect.py | 8 | CODE | |
| LOW | src/textblob/en/inflect.py | 14 | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW⚡ | tests/test_classifiers.py | 105 | res1 = self.classifier.prob_classify("lorem ipsum") | CODE |
| LOW⚡ | tests/test_classifiers.py | 107 | self.classifier.update([("lorem ipsum", "positive")]) | CODE |
| LOW⚡ | tests/test_classifiers.py | 109 | res2 = self.classifier.prob_classify("lorem ipsum") | CODE |
| LOW | tests/test_classifiers.py | 229 | self.classifier.update([("lorem ipsum", "positive")]) | CODE |
| LOW⚡ | tests/test_blob.py | 373 | blob = tb.TextBlob("lorem ipsum") | CODE |
| LOW⚡ | tests/test_blob.py | 374 | assert len(blob) == len("lorem ipsum") | CODE |
| LOW⚡ | tests/test_blob.py | 377 | blob1 = tb.TextBlob("lorem ipsum") | CODE |
| LOW⚡ | tests/test_blob.py | 378 | assert repr(blob1) == 'TextBlob("{}")'.format("lorem ipsum") | CODE |
| LOW⚡ | tests/test_blob.py | 381 | blob1 = tb.TextBlob("lorem ipsum") | CODE |
| LOW⚡ | tests/test_blob.py | 382 | blob2 = tb.TextBlob("lorem ipsum") | CODE |
| LOW⚡ | tests/test_blob.py | 383 | blob3 = tb.TextBlob("dolor sit amet") | CODE |
| LOW⚡ | tests/test_blob.py | 514 | blob = tb.TextBlob("lorem ipsum") | CODE |
| LOW⚡ | tests/test_blob.py | 519 | blob = tb.TextBlob("lorem ipsum") | CODE |
| LOW⚡ | tests/test_blob.py | 521 | assert blob.upper() == tb.TextBlob("LOREM IPSUM") | CODE |
| LOW⚡ | tests/test_blob.py | 528 | blob = tb.TextBlob("Lorem Ipsum") | CODE |
| LOW⚡ | tests/test_blob.py | 530 | assert blob.lower() == tb.TextBlob("lorem ipsum") | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | src/textblob/_text.py | 350 | CODE | |
| LOW | src/textblob/_text.py | 459 | CODE | |
| LOW | src/textblob/_text.py | 1178 | CODE | |
| LOW | src/textblob/_text.py | 1316 | CODE | |
| LOW | src/textblob/_text.py | 1360 | CODE | |
| LOW | src/textblob/_text.py | 783 | CODE | |
| LOW | src/textblob/_text.py | 970 | CODE | |
| LOW | src/textblob/_text.py | 1048 | CODE | |
| LOW | src/textblob/en/__init__.py | 51 | CODE | |
| LOW | src/textblob/en/inflect.py | 537 | CODE | |
| LOW | src/textblob/en/inflect.py | 852 | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | src/textblob/np_extractors.py | 14 | __all__ = [ | CODE |
| LOW | src/textblob/__init__.py | 3 | __all__ = [ | CODE |
| LOW | src/textblob/inflect.py | 13 | __all__ = [ | CODE |
| LOW | src/textblob/parsers.py | 13 | __all__ = [ | CODE |
| LOW | src/textblob/taggers.py | 14 | __all__ = [ | CODE |
| LOW | src/textblob/sentiments.py | 19 | __all__ = [ | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | src/textblob/_text.py | 181 | # The default part-of-speech tagset used in Pattern is Penn Treebank II. | COMMENT |
| LOW | src/textblob/_text.py | 821 | COMMENT | |
| LOW | src/textblob/_text.py | 1381 | ch[-1] = "I-PNP" | COMMENT |
| LOW | src/textblob/_text.py | 1401 | # ------------------------------------------------------------------ | COMMENT |
| LOW | src/textblob/en/inflect.py | 601 | #### SINGULARIZE ################################################################################### | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | src/textblob/_text.py | 1401 | # ------------------------------------------------------------------ | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | src/textblob/_text.py | 1178 | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | src/textblob/classifiers.py | 98 | except Exception as error: | CODE |