💫 Industrial-strength Natural Language Processing (NLP) in Python
This report presents the forensic synthetic code analysis of explosion/spaCy, a Python project with 33,742 GitHub stars. SynthScan v2.0 examined 227,796 lines of code across 1407 source files, recording 1766 pattern matches distributed across 16 syntactic categories. The overall adjusted score of 10.6 places this repository in the Low AI signal 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).
This chart maps the temporal evolution of the adjusted synthetic code score across successive scan runs. An upward trajectory indicates ongoing incorporation of AI-generated code or expanding LLM-assisted scaffolding; a stable or declining trajectory may reflect active human refactoring, code removal, or the adoption of stricter authorship policies. The dashed secondary line (right axis) independently tracks total raw pattern hit count, which can diverge from the normalised score when codebase size changes significantly between scans.
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 1766 distinct pattern matches across 16 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 | website/setup/jinja_to_js.py | 696 | def _process_filter_capitalize(self, node, **kwargs): | STRING |
| LOW | website/setup/jinja_to_js.py | 977 | def _process_test_divisibleby(self, node, **kwargs): | STRING |
| LOW | website/meta/universe.json | 5499 | "def create_presque_normalizer(nlp, name='presque_normalizer'):", | CODE |
| LOW | extra/DEVELOPER_DOCS/Code Conventions.md | 492 | def test_doc_creation_with_pos(): | CODE |
| LOW | extra/DEVELOPER_DOCS/Code Conventions.md | 526 | def test_en_tokenizer_splits_em_dash_infix(en_tokenizer): | CODE |
| LOW | extra/DEVELOPER_DOCS/Code Conventions.md | 555 | def test_phrase_matcher_validation(en_vocab): | CODE |
| LOW | spacy/util.py | 1387 | def make_first_longest_spans_filter(): | CODE |
| LOW | spacy/language.py | 2163 | def _resolve_component_status( | CODE |
| LOW | spacy/scorer.py | 262 | def score_token_attr_per_feat( | CODE |
| LOW | spacy/pipeline/spancat.py | 144 | def build_ngram_range_suggester(min_size: int, max_size: int) -> Suggester: | CODE |
| LOW | spacy/pipeline/spancat.py | 152 | def build_preset_spans_suggester(spans_key: str) -> Suggester: | CODE |
| LOW | spacy/pipeline/spancat.py | 558 | def _make_span_group_multilabel( | CODE |
| LOW | spacy/pipeline/spancat.py | 599 | def _make_span_group_singlelabel( | CODE |
| LOW | spacy/pipeline/attributeruler.py | 47 | def make_attribute_ruler_scorer(): | CODE |
| LOW | spacy/pipeline/span_ruler.py | 36 | def prioritize_new_ents_filter( | CODE |
| LOW | spacy/pipeline/span_ruler.py | 62 | def make_prioritize_new_ents_filter(): | CODE |
| LOW | spacy/pipeline/span_ruler.py | 66 | def prioritize_existing_ents_filter( | CODE |
| LOW | spacy/pipeline/span_ruler.py | 92 | def make_preserve_existing_ents_filter(): | CODE |
| LOW | spacy/pipeline/span_ruler.py | 96 | def overlapping_labeled_spans_score( | CODE |
| LOW | spacy/pipeline/span_ruler.py | 111 | def make_overlapping_labeled_spans_scorer(spans_key: str = DEFAULT_SPANS_KEY): | CODE |
| LOW | spacy/pipeline/factories.py | 727 | def make_edit_tree_lemmatizer( | CODE |
| LOW | spacy/pipeline/entity_linker.py | 47 | def make_entity_linker_scorer(): | STRING |
| LOW | spacy/pipeline/entity_linker.py | 237 | def batch_has_learnable_example(self, examples): | CODE |
| LOW | spacy/pipeline/textcat_multilabel.py | 82 | def make_textcat_multilabel_scorer(): | STRING |
| LOW | spacy/pipeline/span_finder.py | 217 | def _get_aligned_truth_scores(self, examples, ops) -> Tuple[Floats2d, Floats2d]: | STRING |
| LOW | spacy/training/batchers.py | 22 | def configure_minibatch_by_padded_size( | CODE |
| LOW | spacy/training/batchers.py | 56 | def configure_minibatch_by_words( | CODE |
| LOW | spacy/training/augment.py | 13 | def create_combined_augmenter( | CODE |
| LOW | spacy/training/augment.py | 85 | def create_orth_variants_augmenter( | CODE |
| LOW | spacy/training/augment.py | 102 | def create_lower_casing_augmenter( | CODE |
| LOW | spacy/training/augment.py | 337 | def construct_modified_raw_text(token_dict): | CODE |
| LOW | spacy/training/iob_utils.py | 63 | def _doc_to_biluo_tags_with_partial(doc: Doc) -> List[str]: | CODE |
| LOW | spacy/training/callbacks.py | 10 | def create_copy_from_base_model( | CODE |
| LOW | spacy/training/loop.py | 290 | def create_evaluation_callback( | CODE |
| LOW | spacy/training/loop.py | 356 | def create_before_to_disk_callback( | CODE |
| LOW | spacy/training/corpus.py | 199 | def make_examples_gold_preproc( | CODE |
| LOW | spacy/tests/test_displacy.py | 120 | def test_displacy_parse_spans(en_vocab): | CODE |
| LOW | spacy/tests/test_displacy.py | 149 | def test_displacy_parse_spans_with_kb_id_options(en_vocab): | CODE |
| LOW | spacy/tests/test_displacy.py | 184 | def test_displacy_parse_spans_different_spans_key(en_vocab): | CODE |
| LOW | spacy/tests/test_displacy.py | 206 | def test_displacy_parse_empty_spans_key(en_vocab): | CODE |
| LOW | spacy/tests/test_displacy.py | 236 | def test_displacy_parse_ents_with_kb_id_options(en_vocab): | CODE |
| LOW | spacy/tests/test_displacy.py | 294 | def test_displacy_invalid_arcs(): | CODE |
| LOW | spacy/tests/test_displacy.py | 313 | def test_displacy_raises_for_wrong_type(en_vocab): | CODE |
| LOW | spacy/tests/test_displacy.py | 337 | def test_displacy_render_wrapper(en_vocab): | CODE |
| LOW | spacy/tests/test_displacy.py | 353 | def test_displacy_render_manual_dep(): | CODE |
| LOW | spacy/tests/test_displacy.py | 375 | def test_displacy_render_manual_ent(): | CODE |
| LOW | spacy/tests/test_displacy.py | 396 | def test_displacy_render_manual_span(): | CODE |
| LOW | spacy/tests/test_displacy.py | 425 | def test_displacy_options_case(): | CODE |
| LOW | spacy/tests/test_displacy.py | 440 | def test_displacy_manual_sorted_entities(): | CODE |
| LOW | spacy/tests/test_displacy.py | 474 | def test_displacy_span_stacking(): | CODE |
| LOW | spacy/tests/test_misc.py | 79 | def test_util_ensure_path_succeeds(text): | CODE |
| LOW | spacy/tests/test_misc.py | 93 | def test_util_get_package_path(package): | CODE |
| LOW | spacy/tests/test_misc.py | 176 | def test_load_model_blank_shortcut(): | CODE |
| LOW | spacy/tests/test_misc.py | 207 | def test_is_compatible_version(version, constraint, compatible): | CODE |
| LOW | spacy/tests/test_misc.py | 225 | def test_is_unconstrained_version(constraint, expected): | CODE |
| LOW | spacy/tests/test_misc.py | 284 | def test_dot_to_dict_overrides(dot_notation, expected): | CODE |
| LOW | spacy/tests/test_misc.py | 351 | def test_util_minibatch_oversize(doc_sizes, expected_batches): | CODE |
| LOW | spacy/tests/util.py | 42 | def apply_transition_sequence(parser, doc, sequence): | CODE |
| LOW | spacy/tests/test_factory_imports.py | 65 | def test_factory_import_compatibility(factory_name, original_module, compat_module): | CODE |
| LOW | spacy/tests/README.md | 111 | def test_doc_token_api_strings(en_vocab): | CODE |
| 1090 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | spacy/pipeline/tok2vec.py | 0 | learn from a batch of documents and gold-standard information, updating the pipe's model. delegates to predict and get_l | STRING |
| HIGH | spacy/pipeline/spancat.py | 0 | learn from a batch of documents and gold-standard information, updating the pipe's model. delegates to predict and get_l | STRING |
| HIGH | spacy/pipeline/entity_linker.py | 0 | learn from a batch of documents and gold-standard information, updating the pipe's model. delegates to predict and get_l | STRING |
| HIGH | spacy/pipeline/legacy/entity_linker.py | 0 | learn from a batch of documents and gold-standard information, updating the pipe's model. delegates to predict and get_l | STRING |
| HIGH | spacy/pipeline/span_finder.py | 0 | learn from a batch of documents and gold-standard information, updating the pipe's model. delegates to predict and get_l | STRING |
| HIGH | spacy/pipeline/textcat.py | 0 | learn from a batch of documents and gold-standard information, updating the pipe's model. delegates to predict and get_l | STRING |
| HIGH | spacy/pipeline/lemmatizer.py | 0 | serialize the pipe to disk. path (str / path): path to a directory. exclude (iterable[str]): string names of serializati | STRING |
| HIGH | spacy/pipeline/entity_linker.py | 0 | serialize the pipe to disk. path (str / path): path to a directory. exclude (iterable[str]): string names of serializati | STRING |
| HIGH | spacy/pipeline/legacy/entity_linker.py | 0 | serialize the pipe to disk. path (str / path): path to a directory. exclude (iterable[str]): string names of serializati | STRING |
| HIGH | spacy/pipeline/lemmatizer.py | 0 | serialize the pipe to a bytestring. exclude (iterable[str]): string names of serialization fields to exclude. returns (b | STRING |
| HIGH | spacy/pipeline/entity_linker.py | 0 | serialize the pipe to a bytestring. exclude (iterable[str]): string names of serialization fields to exclude. returns (b | STRING |
| HIGH | spacy/pipeline/legacy/entity_linker.py | 0 | serialize the pipe to a bytestring. exclude (iterable[str]): string names of serialization fields to exclude. returns (b | STRING |
| HIGH | spacy/pipeline/spancat.py | 0 | apply the pipeline's model to a batch of docs, without modifying them. docs (iterable[doc]): the documents to predict. r | STRING |
| HIGH | spacy/pipeline/span_finder.py | 0 | apply the pipeline's model to a batch of docs, without modifying them. docs (iterable[doc]): the documents to predict. r | STRING |
| HIGH | spacy/pipeline/textcat.py | 0 | apply the pipeline's model to a batch of docs, without modifying them. docs (iterable[doc]): the documents to predict. r | STRING |
| HIGH | spacy/pipeline/spancat.py | 0 | find the loss and gradient of loss for the batch of documents and their predicted scores. examples (iterable[examples]): | STRING |
| HIGH | spacy/pipeline/span_finder.py | 0 | find the loss and gradient of loss for the batch of documents and their predicted scores. examples (iterable[examples]): | STRING |
| HIGH | spacy/pipeline/textcat.py | 0 | find the loss and gradient of loss for the batch of documents and their predicted scores. examples (iterable[examples]): | STRING |
| HIGH | spacy/tests/lang/sv/test_noun_chunks.py | 0 | test that noun_chunks raises value error for 'fa' language if doc is not parsed. | STRING |
| HIGH | spacy/tests/lang/ms/test_noun_chunks.py | 0 | test that noun_chunks raises value error for 'fa' language if doc is not parsed. | STRING |
| HIGH | spacy/tests/lang/el/test_noun_chunks.py | 0 | test that noun_chunks raises value error for 'fa' language if doc is not parsed. | STRING |
| HIGH | spacy/tests/lang/it/test_noun_chunks.py | 0 | test that noun_chunks raises value error for 'fa' language if doc is not parsed. | STRING |
| HIGH | spacy/tests/lang/pt/test_noun_chunks.py | 0 | test that noun_chunks raises value error for 'fa' language if doc is not parsed. | STRING |
| HIGH | spacy/tests/lang/ht/test_noun_chunks.py | 0 | test that noun_chunks raises value error for 'fa' language if doc is not parsed. | STRING |
| HIGH | spacy/tests/lang/nl/test_noun_chunks.py | 0 | test that noun_chunks raises value error for 'fa' language if doc is not parsed. | STRING |
| HIGH | spacy/tests/lang/nb/test_noun_chunks.py | 0 | test that noun_chunks raises value error for 'fa' language if doc is not parsed. | STRING |
| HIGH | spacy/tests/lang/de/test_noun_chunks.py | 0 | test that noun_chunks raises value error for 'fa' language if doc is not parsed. | STRING |
| HIGH | spacy/tests/lang/id/test_noun_chunks.py | 0 | test that noun_chunks raises value error for 'fa' language if doc is not parsed. | STRING |
| HIGH | spacy/tests/lang/fr/test_noun_chunks.py | 0 | test that noun_chunks raises value error for 'fa' language if doc is not parsed. | STRING |
| HIGH | spacy/tests/lang/es/test_noun_chunks.py | 0 | test that noun_chunks raises value error for 'fa' language if doc is not parsed. | STRING |
| HIGH | spacy/tests/lang/en/test_noun_chunks.py | 0 | test that noun_chunks raises value error for 'fa' language if doc is not parsed. | STRING |
| HIGH | spacy/tests/lang/fa/test_noun_chunks.py | 0 | test that noun_chunks raises value error for 'fa' language if doc is not parsed. | STRING |
| HIGH | spacy/tests/lang/da/test_noun_chunks.py | 0 | test that noun_chunks raises value error for 'tr' language if doc is not parsed. to check this test, we're constructing | STRING |
| HIGH | spacy/tests/lang/fi/test_noun_chunks.py | 0 | test that noun_chunks raises value error for 'tr' language if doc is not parsed. to check this test, we're constructing | STRING |
| HIGH | spacy/tests/lang/la/test_noun_chunks.py | 0 | test that noun_chunks raises value error for 'tr' language if doc is not parsed. to check this test, we're constructing | STRING |
| HIGH | spacy/tests/lang/tr/test_noun_chunks.py | 0 | test that noun_chunks raises value error for 'tr' language if doc is not parsed. to check this test, we're constructing | STRING |
| HIGH | spacy/lang/sl/examples.py | 0 | example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlp | STRING |
| HIGH | spacy/lang/sk/examples.py | 0 | example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlp | STRING |
| HIGH | spacy/lang/ur/examples.py | 0 | example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlp | STRING |
| HIGH | spacy/lang/da/examples.py | 0 | example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlp | STRING |
| HIGH | spacy/lang/kmr/examples.py | 0 | example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlp | STRING |
| HIGH | spacy/lang/pl/examples.py | 0 | example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlp | STRING |
| HIGH | spacy/lang/vi/examples.py | 0 | example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlp | STRING |
| HIGH | spacy/lang/sq/examples.py | 0 | example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlp | STRING |
| HIGH | spacy/lang/sv/examples.py | 0 | example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlp | STRING |
| HIGH | spacy/lang/he/examples.py | 0 | example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlp | STRING |
| HIGH | spacy/lang/ms/examples.py | 0 | example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlp | STRING |
| HIGH | spacy/lang/hy/examples.py | 0 | example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlp | STRING |
| HIGH | spacy/lang/am/examples.py | 0 | example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlp | STRING |
| HIGH | spacy/lang/nn/examples.py | 0 | example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlp | STRING |
| HIGH | spacy/lang/ky/examples.py | 0 | example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlp | STRING |
| HIGH | spacy/lang/gu/examples.py | 0 | example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlp | STRING |
| HIGH | spacy/lang/grc/examples.py | 0 | example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlp | STRING |
| HIGH | spacy/lang/ja/examples.py | 0 | example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlp | STRING |
| HIGH | spacy/lang/el/examples.py | 0 | example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlp | STRING |
| HIGH | spacy/lang/lb/examples.py | 0 | example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlp | STRING |
| HIGH | spacy/lang/it/examples.py | 0 | example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlp | STRING |
| HIGH | spacy/lang/ca/examples.py | 0 | example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlp | STRING |
| HIGH | spacy/lang/cs/examples.py | 0 | example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlp | STRING |
| HIGH | spacy/lang/ru/examples.py | 0 | example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlp | STRING |
| 58 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | spacy/compat.py | 42 | CODE | |
| LOW | spacy/compat.py | 28 | CODE | |
| LOW | spacy/compat.py | 28 | CODE | |
| LOW | spacy/compat.py | 28 | CODE | |
| LOW | spacy/compat.py | 30 | CODE | |
| LOW | spacy/compat.py | 30 | CODE | |
| LOW | spacy/compat.py | 30 | CODE | |
| LOW | spacy/compat.py | 36 | CODE | |
| LOW | spacy/compat.py | 38 | CODE | |
| LOW | spacy/util.py | 68 | CODE | |
| LOW | spacy/util.py | 68 | CODE | |
| LOW | spacy/util.py | 68 | CODE | |
| LOW | spacy/util.py | 77 | CODE | |
| LOW | spacy/util.py | 77 | CODE | |
| LOW | spacy/util.py | 78 | CODE | |
| LOW | spacy/util.py | 78 | CODE | |
| LOW | spacy/util.py | 79 | CODE | |
| LOW | spacy/util.py | 402 | CODE | |
| LOW | spacy/util.py | 1156 | CODE | |
| LOW | spacy/__init__.py | 11 | CODE | |
| LOW | spacy/__init__.py | 11 | CODE | |
| LOW | spacy/__init__.py | 11 | CODE | |
| LOW | spacy/__init__.py | 13 | CODE | |
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| LOW | spacy/__init__.py | 33 | CODE | |
| LOW | spacy/__init__.py | 33 | CODE | |
| LOW | spacy/schemas.py | 41 | CODE | |
| LOW | spacy/schemas.py | 42 | CODE | |
| LOW | spacy/schemas.py | 43 | CODE | |
| LOW | spacy/pipe_analysis.py | 11 | CODE | |
| LOW | spacy/ty.py | 17 | CODE | |
| LOW | spacy/ty.py | 18 | CODE | |
| LOW | spacy/scorer.py | 24 | CODE | |
| LOW | spacy/pipeline/__init__.py | 1 | CODE | |
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| LOW | spacy/pipeline/__init__.py | 20 | CODE | |
| LOW | spacy/pipeline/legacy/__init__.py | 1 | CODE | |
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| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | website/setup/jinja_to_js.py | 458 | CODE | |
| LOW | website/setup/jinja_to_js.py | 491 | CODE | |
| LOW | website/setup/jinja_to_js.py | 651 | CODE | |
| LOW | website/setup/jinja_to_js.py | 675 | CODE | |
| LOW | website/setup/jinja_to_js.py | 886 | CODE | |
| LOW | website/setup/jinja_to_js.py | 1022 | CODE | |
| LOW | website/setup/jinja_to_js.py | 1112 | CODE | |
| LOW | spacy/util.py | 675 | CODE | |
| LOW | spacy/util.py | 940 | CODE | |
| LOW | spacy/util.py | 1810 | CODE | |
| LOW | spacy/language.py | 838 | CODE | |
| LOW | spacy/language.py | 1636 | CODE | |
| LOW | spacy/language.py | 1763 | CODE | |
| LOW | spacy/language.py | 1996 | CODE | |
| LOW | spacy/pipe_analysis.py | 17 | CODE | |
| LOW | spacy/pipe_analysis.py | 81 | CODE | |
| LOW | spacy/scorer.py | 760 | CODE | |
| LOW | spacy/scorer.py | 211 | CODE | |
| LOW | spacy/scorer.py | 262 | CODE | |
| LOW | spacy/scorer.py | 346 | CODE | |
| LOW | spacy/scorer.py | 447 | CODE | |
| LOW | spacy/scorer.py | 583 | CODE | |
| LOW | spacy/scorer.py | 652 | CODE | |
| LOW | spacy/displacy/render.py | 153 | CODE | |
| LOW | spacy/pipeline/functions.py | 82 | CODE | |
| LOW | spacy/pipeline/functions.py | 138 | CODE | |
| LOW | spacy/pipeline/tok2vec.py | 278 | CODE | |
| LOW | spacy/pipeline/lemmatizer.py | 172 | CODE | |
| LOW | spacy/pipeline/edit_tree_lemmatizer.py | 156 | CODE | |
| LOW | spacy/pipeline/edit_tree_lemmatizer.py | 176 | CODE | |
| LOW | spacy/pipeline/edit_tree_lemmatizer.py | 197 | CODE | |
| LOW | spacy/pipeline/entityruler.py | 246 | CODE | |
| LOW | spacy/pipeline/spancat.py | 449 | CODE | |
| LOW | spacy/pipeline/spancat.py | 558 | CODE | |
| LOW | spacy/pipeline/attributeruler.py | 190 | CODE | |
| LOW | spacy/pipeline/span_ruler.py | 322 | CODE | |
| LOW | spacy/pipeline/entity_linker.py | 338 | CODE | |
| LOW | spacy/pipeline/entity_linker.py | 460 | CODE | |
| LOW | spacy/pipeline/span_finder.py | 135 | CODE | |
| LOW | spacy/pipeline/span_finder.py | 217 | CODE | |
| LOW | spacy/pipeline/textcat.py | 262 | CODE | |
| LOW | spacy/pipeline/legacy/entity_linker.py | 139 | CODE | |
| LOW | spacy/pipeline/legacy/entity_linker.py | 225 | CODE | |
| LOW | spacy/pipeline/legacy/entity_linker.py | 311 | CODE | |
| LOW | spacy/training/pretrain.py | 26 | CODE | |
| LOW | spacy/training/initialize.py | 35 | CODE | |
| LOW | spacy/training/initialize.py | 210 | CODE | |
| LOW | spacy/training/batchers.py | 134 | CODE | |
| LOW | spacy/training/augment.py | 164 | CODE | |
| LOW | spacy/training/augment.py | 219 | CODE | |
| LOW | spacy/training/iob_utils.py | 71 | CODE | |
| LOW | spacy/training/iob_utils.py | 194 | CODE | |
| LOW | spacy/training/loop.py | 35 | CODE | |
| LOW | spacy/training/loop.py | 153 | CODE | |
| LOW | spacy/training/loop.py | 373 | CODE | |
| LOW | spacy/training/corpus.py | 84 | CODE | |
| LOW | spacy/training/corpus.py | 184 | CODE | |
| LOW | spacy/training/corpus.py | 212 | CODE | |
| LOW | spacy/training/corpus.py | 261 | CODE | |
| LOW | spacy/training/corpus.py | 311 | CODE | |
| 56 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | spacy/util.py | 439 | def set_lang_class(name: str, cls: Type["Language"]) -> None: | CODE |
| LOW | spacy/util.py | 1597 | def set_dot_to_object(config: Config, section: str, value: Any) -> None: | CODE |
| LOW | spacy/lookups.py | 210 | def set_table(self, name: str, table: Table) -> None: | CODE |
| LOW | spacy/language.py | 436 | def set_factory_meta(cls, name: str, value: "FactoryMeta") -> None: | CODE |
| LOW | spacy/displacy/__init__.py | 257 | def set_render_wrapper(func: Callable[[str], str]) -> None: | CODE |
| LOW | spacy/pipeline/functions.py | 102 | def _set_config(self, config: Dict[str, Any] = {}) -> None: | CODE |
| LOW | spacy/pipeline/tok2vec.py | 123 | def set_annotations(self, docs: Sequence[Doc], tokvecses) -> None: | CODE |
| LOW | spacy/pipeline/spancat.py | 380 | def set_annotations(self, docs: Iterable[Doc], indices_scores) -> None: | CODE |
| LOW | spacy/pipeline/__init__.py | 22 | __all__ = [ | CODE |
| LOW | spacy/pipeline/entity_linker.py | 460 | def set_annotations(self, docs: Iterable[Doc], kb_ids: List[str]) -> None: | CODE |
| LOW | spacy/pipeline/span_finder.py | 135 | def set_annotations(self, docs: Iterable[Doc], scores: Floats2d) -> None: | STRING |
| LOW | spacy/pipeline/textcat.py | 170 | def set_annotations(self, docs: Iterable[Doc], scores) -> None: | STRING |
| LOW | spacy/pipeline/legacy/__init__.py | 3 | __all__ = ["EntityLinker_v1"] | CODE |
| LOW | spacy/pipeline/legacy/entity_linker.py | 311 | def set_annotations(self, docs: Iterable[Doc], kb_ids: List[str]) -> None: | CODE |
| LOW | spacy/kb/__init__.py | 5 | __all__ = [ | CODE |
| LOW | spacy/training/__init__.py | 20 | __all__ = [ | CODE |
| LOW | spacy/cli/init_pipeline.py | 95 | def update_lexemes(nlp: Language, jsonl_loc: Path) -> None: | CODE |
| LOW | spacy/matcher/__init__.py | 6 | __all__ = ["DependencyMatcher", "Matcher", "PhraseMatcher", "levenshtein"] | CODE |
| LOW | spacy/lang/sl/__init__.py | 22 | __all__ = ["Slovenian"] | CODE |
| LOW | spacy/lang/sk/__init__.py | 16 | __all__ = ["Slovak"] | CODE |
| LOW | spacy/lang/ur/__init__.py | 19 | __all__ = ["Urdu"] | CODE |
| LOW | spacy/lang/kmr/__init__.py | 16 | __all__ = ["Kurmanji"] | CODE |
| LOW | spacy/lang/pl/__init__.py | 55 | __all__ = ["Polish"] | CODE |
| LOW | spacy/lang/vi/__init__.py | 132 | def _set_config(self, config: Dict[str, Any] = {}) -> None: | CODE |
| LOW | spacy/lang/vi/__init__.py | 167 | __all__ = ["Vietnamese"] | CODE |
| LOW | spacy/lang/sq/__init__.py | 14 | __all__ = ["Albanian"] | CODE |
| LOW | spacy/lang/sv/__init__.py | 52 | __all__ = ["Swedish"] | CODE |
| LOW | spacy/lang/ga/__init__.py | 33 | __all__ = ["Irish"] | CODE |
| LOW | spacy/lang/he/__init__.py | 17 | __all__ = ["Hebrew"] | CODE |
| LOW | spacy/lang/ms/__init__.py | 24 | __all__ = ["Malay"] | CODE |
| LOW | spacy/lang/hy/__init__.py | 16 | __all__ = ["Armenian"] | CODE |
| LOW | spacy/lang/am/__init__.py | 26 | __all__ = ["Amharic"] | CODE |
| LOW | spacy/lang/nn/__init__.py | 20 | __all__ = ["NorwegianNynorsk"] | CODE |
| LOW | spacy/lang/da/__init__.py | 23 | __all__ = ["Danish"] | CODE |
| LOW | spacy/lang/mr/__init__.py | 14 | __all__ = ["Marathi"] | CODE |
| LOW | spacy/lang/ky/__init__.py | 20 | __all__ = ["Kyrgyz"] | CODE |
| LOW | spacy/lang/gu/__init__.py | 14 | __all__ = ["Gujarati"] | CODE |
| LOW | spacy/lang/grc/__init__.py | 22 | __all__ = ["AncientGreek"] | CODE |
| LOW | spacy/lang/ja/__init__.py | 158 | def _set_config(self, config: Dict[str, Any] = {}) -> None: | STRING |
| LOW | spacy/lang/ja/__init__.py | 341 | __all__ = ["Japanese"] | CODE |
| LOW | spacy/lang/el/__init__.py | 53 | __all__ = ["Greek"] | CODE |
| LOW | spacy/lang/lv/__init__.py | 14 | __all__ = ["Latvian"] | CODE |
| LOW | spacy/lang/lb/__init__.py | 20 | __all__ = ["Luxembourgish"] | CODE |
| LOW | spacy/lang/it/__init__.py | 50 | __all__ = ["Italian"] | CODE |
| LOW | spacy/lang/ca/__init__.py | 53 | __all__ = ["Catalan"] | CODE |
| LOW | spacy/lang/is/__init__.py | 14 | __all__ = ["Icelandic"] | CODE |
| LOW | spacy/lang/cs/__init__.py | 16 | __all__ = ["Czech"] | CODE |
| LOW | spacy/lang/te/__init__.py | 16 | __all__ = ["Telugu"] | CODE |
| LOW | spacy/lang/ru/__init__.py | 53 | __all__ = ["Russian"] | CODE |
| LOW | spacy/lang/tl/__init__.py | 18 | __all__ = ["Tagalog"] | CODE |
| LOW | spacy/lang/ro/__init__.py | 26 | __all__ = ["Romanian"] | CODE |
| LOW | spacy/lang/hsb/__init__.py | 18 | __all__ = ["UpperSorbian"] | CODE |
| LOW | spacy/lang/yo/__init__.py | 16 | __all__ = ["Yoruba"] | CODE |
| LOW | spacy/lang/sa/__init__.py | 16 | __all__ = ["Sanskrit"] | CODE |
| LOW | spacy/lang/pt/__init__.py | 23 | __all__ = ["Portuguese"] | CODE |
| LOW | spacy/lang/zh/__init__.py | 146 | def _set_config(self, config: Dict[str, Any] = {}) -> None: | STRING |
| LOW | spacy/lang/zh/__init__.py | 336 | __all__ = ["Chinese"] | STRING |
| LOW | spacy/lang/uk/__init__.py | 53 | __all__ = ["Ukrainian"] | CODE |
| LOW | spacy/lang/sr/__init__.py | 21 | __all__ = ["Serbian"] | CODE |
| LOW | spacy/lang/si/__init__.py | 16 | __all__ = ["Sinhala"] | CODE |
| 42 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM⚡ | website/meta/universe.json | 100 | "# Define the language for the sentence as well as for the spaCy and benepar models", | CODE |
| MEDIUM⚡ | website/meta/universe.json | 104 | "# Create the pipeline (note, the required models will be downloaded and installed automatically)", | CODE |
| MEDIUM⚡ | website/meta/universe.json | 108 | "# Create the tree from where we are going to extract the desired noun phrases", | CODE |
| MEDIUM | website/meta/universe.json | 1387 | "# Create a new chat bot named Charlie", | CODE |
| MEDIUM | website/meta/universe.json | 3606 | "# Create a new DocBin", | CODE |
| MEDIUM | spacy/language.py | 220 | # Create the default tokenizer from the default config | COMMENT |
| MEDIUM | spacy/displacy/render.py | 326 | # Create a random ID prefix to make sure parses don't receive the | COMMENT |
| MEDIUM | spacy/pipeline/legacy/entity_linker.py | 1 | # This file is present to provide a prior version of the EntityLinker component | COMMENT |
| MEDIUM | spacy/tests/test_displacy.py | 457 | # Create a doc containing an annotated word and an unannotated HTML tag | COMMENT |
| MEDIUM | spacy/tests/pipeline/test_entity_linker.py | 151 | # Create the Entity Linker component and add it to the pipeline | COMMENT |
| MEDIUM | spacy/tests/pipeline/test_entity_linker.py | 746 | # Create the Entity Linker component and add it to the pipeline | COMMENT |
| MEDIUM | spacy/tests/pipeline/test_entity_linker.py | 852 | # Create the NER and EL components and add them to the pipeline | COMMENT |
| MEDIUM | spacy/tests/pipeline/test_entity_linker.py | 933 | # Create the Entity Linker component with the KB from file, and check the final vocab | COMMENT |
| MEDIUM | spacy/tests/pipeline/test_entity_linker.py | 1156 | # Create a ruler to mark entities | COMMENT |
| MEDIUM | spacy/tests/pipeline/test_entity_linker.py | 1282 | # Create the Entity Linker component and add it to the pipeline | COMMENT |
| MEDIUM | spacy/cli/debug_data.py | 149 | # Create the gold corpus to be able to better analyze data | COMMENT |
| MEDIUM | spacy/cli/debug_data.py | 903 | # Creating a data structure that holds the start and | COMMENT |
| MEDIUM | spacy/lang/lex_attrs.py | 185 | # This function is partially applied so lang code can be passed in | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH⚡ | website/pages/index.tsx | 52 | print("Noun phrases:", [chunk.text for chunk in doc.noun_chunks]) | CODE |
| HIGH⚡ | website/pages/index.tsx | 53 | print("Verbs:", [token.lemma_ for token in doc if token.pos_ == "VERB"]) | CODE |
| HIGH⚡ | website/pages/index.tsx | 57 | print(entity.text, entity.label_) | CODE |
| HIGH | website/src/widgets/quickstart-models.js | 105 | print([ | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | setup.py | 136 | except Exception: | CODE |
| LOW | setup.py | 144 | except Exception: | CODE |
| LOW | spacy/util.py | 890 | except Exception: | CODE |
| LOW | spacy/util.py | 1777 | except Exception as e: | CODE |
| LOW | spacy/language.py | 1057 | except Exception as e: | CODE |
| LOW | spacy/language.py | 2417 | except Exception: | CODE |
| LOW | spacy/pipeline/lemmatizer.py | 113 | except Exception as e: | CODE |
| LOW | spacy/pipeline/entityruler.py | 125 | except Exception as e: | CODE |
| LOW | spacy/pipeline/attributeruler.py | 134 | except Exception as e: | CODE |
| LOW | spacy/pipeline/span_ruler.py | 224 | except Exception as e: | CODE |
| LOW | spacy/training/loop.py | 126 | except Exception as e: | CODE |
| LOW | spacy/training/loop.py | 385 | except Exception as e: | CODE |
| LOW | spacy/tests/test_models.py | 163 | except Exception: | CODE |
| LOW | spacy/tests/test_models.py | 173 | except Exception: | CODE |
| LOW⚡ | spacy/tests/serialize/test_resource_warning.py | 117 | except Exception as e: | CODE |
| LOW⚡ | spacy/tests/serialize/test_resource_warning.py | 131 | except Exception as e: | CODE |
| LOW⚡ | spacy/tests/serialize/test_resource_warning.py | 137 | except Exception as e: | CODE |
| LOW | spacy/cli/_util.py | 195 | except Exception as e: | CODE |
| LOW | spacy/cli/info.py | 159 | except Exception: | CODE |
| LOW | spacy/cli/info.py | 197 | except Exception: | CODE |
| LOW | spacy/cli/debug_model.py | 146 | except Exception: | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | setup.py | 129 | CODE | |
| LOW | spacy/util.py | 1380 | CODE | |
| LOW | spacy/language.py | 768 | CODE | |
| LOW | spacy/language.py | 1763 | CODE | |
| LOW | spacy/displacy/__init__.py | 76 | CODE | |
| LOW | spacy/pipeline/entityruler.py | 42 | CODE | |
| LOW | spacy/pipeline/spancat.py | 203 | CODE | |
| LOW | spacy/pipeline/span_ruler.py | 123 | CODE | |
| LOW | spacy/tests/test_language.py | 285 | CODE | |
| LOW | spacy/cli/package.py | 22 | CODE | |
| LOW | spacy/cli/package.py | 109 | CODE | |
| LOW | spacy/cli/benchmark_speed.py | 23 | CODE | |
| LOW | spacy/cli/init_pipeline.py | 24 | CODE | |
| LOW | spacy/cli/convert.py | 48 | CODE | |
| LOW | spacy/cli/convert.py | 129 | CODE | |
| LOW | spacy/cli/find_threshold.py | 27 | CODE | |
| LOW | spacy/cli/evaluate.py | 19 | CODE | |
| LOW | spacy/cli/evaluate.py | 87 | CODE | |
| LOW | spacy/cli/debug_model.py | 36 | CODE | |
| LOW | spacy/cli/debug_model.py | 250 | CODE | |
| LOW | spacy/cli/apply.py | 69 | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | spacy/tests/parser/test_state.py | 28 | state.push() | CODE |
| HIGH | spacy/tests/parser/test_state.py | 32 | state.push() | CODE |
| HIGH | spacy/tests/parser/test_state.py | 45 | state.push() | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | website/meta/universe.json | 744 | "# [{'end': 8, 'start': 0, 'text': 'John Doe', 'type': 'PERSON'}, {'end': 25, 'start': 13, 'text': 'Go D | CODE |
| LOW | spacy/glossary.py | 314 | "ph": "placeholder", | CODE |
| LOW⚡ | spacy/tests/tokenizer/test_whitespace.py | 4 | @pytest.mark.parametrize("text", ["lorem ipsum"]) | CODE |
| LOW⚡ | spacy/tests/tokenizer/test_whitespace.py | 17 | @pytest.mark.parametrize("text", ["lorem ipsum "]) | CODE |
| LOW⚡ | spacy/tests/tokenizer/test_tokenizer.py | 317 | text = "Lorem ipsum: 1984." | CODE |
| LOW⚡ | spacy/tests/tokenizer/test_tokenizer.py | 350 | text = """Lorem ipsum dolor sit amet, consectetur adipiscing elit | CODE |
| LOW⚡ | spacy/tests/tokenizer/test_tokenizer.py | 350 | text = """Lorem ipsum dolor sit amet, consectetur adipiscing elit | CODE |
| LOW⚡ | spacy/tests/tokenizer/test_tokenizer.py | 374 | text1 = "Lorem dolor sit amet, consectetur adipiscing elit." | CODE |
| LOW⚡ | spacy/tests/tokenizer/test_tokenizer.py | 375 | text2 = "Lorem ipsum dolor sit amet, consectetur adipiscing elit." | CODE |
| LOW⚡ | spacy/tests/tokenizer/test_tokenizer.py | 375 | text2 = "Lorem ipsum dolor sit amet, consectetur adipiscing elit." | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | website/meta/universe.json | 9 | "description": "**[Temporal Expressions Normalization spaCy (TeNs)](https://github.com/iliedorobat/timespan- | CODE |
| MEDIUM | website/meta/universe.json | 5396 | "# floret n-gram embeddings robust to typos", | CODE |
| LOW | spacy/schemas.py | 102 | # binding=True. Here we just use an empty model that allows everything. | COMMENT |
| LOW | spacy/scorer.py | 724 | # None is indistinct, so we can't just add it to the set | COMMENT |
| LOW | spacy/training/loggers.py | 120 | # If we don't have a new checkpoint, just return. | COMMENT |
| LOW | spacy/tests/test_factory_registrations.py | 59 | # For Cython functions, just use a placeholder | COMMENT |
| LOW | spacy/lang/ja/__init__.py | 77 | # if there's no lemma info (it's an unk) just use the surface | STRING |
| LOW | spacy/lang/ht/lemmatizer.py | 39 | # fallback rule: just return lowercased form | COMMENT |
| LOW | spacy/ml/_precomputable_affine.py | 44 | # However, we avoid building that array for efficiency -- and just pass | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | spacy/util.py | 418 | # Check if language is registered / entry point is available | COMMENT |
| LOW | spacy/language.py | 2065 | # Check if the path actually exists in the config | COMMENT |
| LOW | spacy/lang/it/syntax_iterators.py | 57 | elif right_child.dep in np_modifs: # Check if we can expand to right | CODE |
| LOW | spacy/lang/pt/syntax_iterators.py | 56 | elif right_child.dep in np_modifs: # Check if we can expand to right | CODE |
| LOW | spacy/lang/fr/syntax_iterators.py | 58 | elif right_child.dep in np_modifs: # Check if we can expand to right | CODE |
| LOW | spacy/lang/es/syntax_iterators.py | 47 | elif right_child.dep in np_modifs: # Check if we can expand to right | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | spacy/default_config.cfg | 41 | # Whether to train on sequences with 'gold standard' sentence boundaries | COMMENT |
| LOW | spacy/lang/nl/stop_words.py | 1 | # The original stop words list (added in f46ffe3) was taken from | COMMENT |
| LOW | spacy/ml/_precomputable_affine.py | 21 | W = model.get_param("W") | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | website/meta/universe.json | 444 | "# zero shot definition of entities", | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | website/meta/universe.json | 1768 | "# For instance you can add the BertTone model for classification of sentiment polarity to the pipeline: | CODE |