Repository Analysis

explosion/spaCy

💫 Industrial-strength Natural Language Processing (NLP) in Python

10.6 Low AI signal View on GitHub

Analysis Overview

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).

10.6
Adjusted Score
10.6
Raw Score
100%
Time Factor
2026-05-19
Last Push
33.7K
Stars
Python
Language
227.8K
Lines of Code
1.4K
Files
1.8K
Pattern Hits
2026-07-14
Scan Date
0.09
HC Hit Rate

What These Metrics Mean

Adjusted Score
Primary synthetic code indicator. Raw score normalised per 1,000 lines of code and multiplied by the temporal discount factor. This is the definitive comparative metric — use it to rank repositories by AI authorship density.
Raw Score
The unmodified sum of all severity-weighted, context-multiplied pattern match scores before temporal discounting. Reflects the absolute signal strength independent of when the repository was last active.
Time Factor
The temporal discount multiplier (0–100%) applied to the raw score. Repositories last updated before ChatGPT's launch (Nov 2022) receive a 5% factor. Full signal is only assigned to repositories active in the post-adoption era (Jan 2024+).
Pattern Hits
Total count of individual pattern matches across all files and categories. A high hit count with a low score may indicate a very large codebase with isolated AI snippets; a low count with a high score indicates dense, concentrated AI signatures.
HC Hit Rate
High+Critical pattern hits per file, averaged across the repository. This orthogonal signal catches repositories where a few files are densely packed with high-severity AI tells — a strong indicator even when the normalised score appears moderate due to codebase size.
Lines of Code / Files
Total lines and files analysed. The scanner examines 94 file extensions. These denominators are used to normalise the score, enabling fair comparison between repositories of vastly different sizes.

Score History

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.

Severity Breakdown

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.

CRITICAL 0HIGH 125MEDIUM 22LOW 1619

Directory Score Breakdown

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.

Pattern Findings

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.

Hyper-Verbose Identifiers1150 hits · 1252 pts
SeverityFileLineSnippetContext
LOWwebsite/setup/jinja_to_js.py696 def _process_filter_capitalize(self, node, **kwargs):STRING
LOWwebsite/setup/jinja_to_js.py977 def _process_test_divisibleby(self, node, **kwargs):STRING
LOWwebsite/meta/universe.json5499 "def create_presque_normalizer(nlp, name='presque_normalizer'):",CODE
LOWextra/DEVELOPER_DOCS/Code Conventions.md492def test_doc_creation_with_pos():CODE
LOWextra/DEVELOPER_DOCS/Code Conventions.md526def test_en_tokenizer_splits_em_dash_infix(en_tokenizer):CODE
LOWextra/DEVELOPER_DOCS/Code Conventions.md555def test_phrase_matcher_validation(en_vocab):CODE
LOWspacy/util.py1387def make_first_longest_spans_filter():CODE
LOWspacy/language.py2163 def _resolve_component_status(CODE
LOWspacy/scorer.py262 def score_token_attr_per_feat(CODE
LOWspacy/pipeline/spancat.py144def build_ngram_range_suggester(min_size: int, max_size: int) -> Suggester:CODE
LOWspacy/pipeline/spancat.py152def build_preset_spans_suggester(spans_key: str) -> Suggester:CODE
LOWspacy/pipeline/spancat.py558 def _make_span_group_multilabel(CODE
LOWspacy/pipeline/spancat.py599 def _make_span_group_singlelabel(CODE
LOWspacy/pipeline/attributeruler.py47def make_attribute_ruler_scorer():CODE
LOWspacy/pipeline/span_ruler.py36def prioritize_new_ents_filter(CODE
LOWspacy/pipeline/span_ruler.py62def make_prioritize_new_ents_filter():CODE
LOWspacy/pipeline/span_ruler.py66def prioritize_existing_ents_filter(CODE
LOWspacy/pipeline/span_ruler.py92def make_preserve_existing_ents_filter():CODE
LOWspacy/pipeline/span_ruler.py96def overlapping_labeled_spans_score(CODE
LOWspacy/pipeline/span_ruler.py111def make_overlapping_labeled_spans_scorer(spans_key: str = DEFAULT_SPANS_KEY):CODE
LOWspacy/pipeline/factories.py727def make_edit_tree_lemmatizer(CODE
LOWspacy/pipeline/entity_linker.py47def make_entity_linker_scorer():STRING
LOWspacy/pipeline/entity_linker.py237 def batch_has_learnable_example(self, examples):CODE
LOWspacy/pipeline/textcat_multilabel.py82def make_textcat_multilabel_scorer():STRING
LOWspacy/pipeline/span_finder.py217 def _get_aligned_truth_scores(self, examples, ops) -> Tuple[Floats2d, Floats2d]:STRING
LOWspacy/training/batchers.py22def configure_minibatch_by_padded_size(CODE
LOWspacy/training/batchers.py56def configure_minibatch_by_words(CODE
LOWspacy/training/augment.py13def create_combined_augmenter(CODE
LOWspacy/training/augment.py85def create_orth_variants_augmenter(CODE
LOWspacy/training/augment.py102def create_lower_casing_augmenter(CODE
LOWspacy/training/augment.py337def construct_modified_raw_text(token_dict):CODE
LOWspacy/training/iob_utils.py63def _doc_to_biluo_tags_with_partial(doc: Doc) -> List[str]:CODE
LOWspacy/training/callbacks.py10def create_copy_from_base_model(CODE
LOWspacy/training/loop.py290def create_evaluation_callback(CODE
LOWspacy/training/loop.py356def create_before_to_disk_callback(CODE
LOWspacy/training/corpus.py199 def make_examples_gold_preproc(CODE
LOWspacy/tests/test_displacy.py120def test_displacy_parse_spans(en_vocab):CODE
LOWspacy/tests/test_displacy.py149def test_displacy_parse_spans_with_kb_id_options(en_vocab):CODE
LOWspacy/tests/test_displacy.py184def test_displacy_parse_spans_different_spans_key(en_vocab):CODE
LOWspacy/tests/test_displacy.py206def test_displacy_parse_empty_spans_key(en_vocab):CODE
LOWspacy/tests/test_displacy.py236def test_displacy_parse_ents_with_kb_id_options(en_vocab):CODE
LOWspacy/tests/test_displacy.py294def test_displacy_invalid_arcs():CODE
LOWspacy/tests/test_displacy.py313def test_displacy_raises_for_wrong_type(en_vocab):CODE
LOWspacy/tests/test_displacy.py337def test_displacy_render_wrapper(en_vocab):CODE
LOWspacy/tests/test_displacy.py353def test_displacy_render_manual_dep():CODE
LOWspacy/tests/test_displacy.py375def test_displacy_render_manual_ent():CODE
LOWspacy/tests/test_displacy.py396def test_displacy_render_manual_span():CODE
LOWspacy/tests/test_displacy.py425def test_displacy_options_case():CODE
LOWspacy/tests/test_displacy.py440def test_displacy_manual_sorted_entities():CODE
LOWspacy/tests/test_displacy.py474def test_displacy_span_stacking():CODE
LOWspacy/tests/test_misc.py79def test_util_ensure_path_succeeds(text):CODE
LOWspacy/tests/test_misc.py93def test_util_get_package_path(package):CODE
LOWspacy/tests/test_misc.py176def test_load_model_blank_shortcut():CODE
LOWspacy/tests/test_misc.py207def test_is_compatible_version(version, constraint, compatible):CODE
LOWspacy/tests/test_misc.py225def test_is_unconstrained_version(constraint, expected):CODE
LOWspacy/tests/test_misc.py284def test_dot_to_dict_overrides(dot_notation, expected):CODE
LOWspacy/tests/test_misc.py351def test_util_minibatch_oversize(doc_sizes, expected_batches):CODE
LOWspacy/tests/util.py42def apply_transition_sequence(parser, doc, sequence):CODE
LOWspacy/tests/test_factory_imports.py65def test_factory_import_compatibility(factory_name, original_module, compat_module):CODE
LOWspacy/tests/README.md111def test_doc_token_api_strings(en_vocab):CODE
1090 more matches not shown…
Cross-File Repetition118 hits · 590 pts
SeverityFileLineSnippetContext
HIGHspacy/pipeline/tok2vec.py0learn from a batch of documents and gold-standard information, updating the pipe's model. delegates to predict and get_lSTRING
HIGHspacy/pipeline/spancat.py0learn from a batch of documents and gold-standard information, updating the pipe's model. delegates to predict and get_lSTRING
HIGHspacy/pipeline/entity_linker.py0learn from a batch of documents and gold-standard information, updating the pipe's model. delegates to predict and get_lSTRING
HIGHspacy/pipeline/legacy/entity_linker.py0learn from a batch of documents and gold-standard information, updating the pipe's model. delegates to predict and get_lSTRING
HIGHspacy/pipeline/span_finder.py0learn from a batch of documents and gold-standard information, updating the pipe's model. delegates to predict and get_lSTRING
HIGHspacy/pipeline/textcat.py0learn from a batch of documents and gold-standard information, updating the pipe's model. delegates to predict and get_lSTRING
HIGHspacy/pipeline/lemmatizer.py0serialize the pipe to disk. path (str / path): path to a directory. exclude (iterable[str]): string names of serializatiSTRING
HIGHspacy/pipeline/entity_linker.py0serialize the pipe to disk. path (str / path): path to a directory. exclude (iterable[str]): string names of serializatiSTRING
HIGHspacy/pipeline/legacy/entity_linker.py0serialize the pipe to disk. path (str / path): path to a directory. exclude (iterable[str]): string names of serializatiSTRING
HIGHspacy/pipeline/lemmatizer.py0serialize the pipe to a bytestring. exclude (iterable[str]): string names of serialization fields to exclude. returns (bSTRING
HIGHspacy/pipeline/entity_linker.py0serialize the pipe to a bytestring. exclude (iterable[str]): string names of serialization fields to exclude. returns (bSTRING
HIGHspacy/pipeline/legacy/entity_linker.py0serialize the pipe to a bytestring. exclude (iterable[str]): string names of serialization fields to exclude. returns (bSTRING
HIGHspacy/pipeline/spancat.py0apply the pipeline's model to a batch of docs, without modifying them. docs (iterable[doc]): the documents to predict. rSTRING
HIGHspacy/pipeline/span_finder.py0apply the pipeline's model to a batch of docs, without modifying them. docs (iterable[doc]): the documents to predict. rSTRING
HIGHspacy/pipeline/textcat.py0apply the pipeline's model to a batch of docs, without modifying them. docs (iterable[doc]): the documents to predict. rSTRING
HIGHspacy/pipeline/spancat.py0find the loss and gradient of loss for the batch of documents and their predicted scores. examples (iterable[examples]):STRING
HIGHspacy/pipeline/span_finder.py0find the loss and gradient of loss for the batch of documents and their predicted scores. examples (iterable[examples]):STRING
HIGHspacy/pipeline/textcat.py0find the loss and gradient of loss for the batch of documents and their predicted scores. examples (iterable[examples]):STRING
HIGHspacy/tests/lang/sv/test_noun_chunks.py0test that noun_chunks raises value error for 'fa' language if doc is not parsed.STRING
HIGHspacy/tests/lang/ms/test_noun_chunks.py0test that noun_chunks raises value error for 'fa' language if doc is not parsed.STRING
HIGHspacy/tests/lang/el/test_noun_chunks.py0test that noun_chunks raises value error for 'fa' language if doc is not parsed.STRING
HIGHspacy/tests/lang/it/test_noun_chunks.py0test that noun_chunks raises value error for 'fa' language if doc is not parsed.STRING
HIGHspacy/tests/lang/pt/test_noun_chunks.py0test that noun_chunks raises value error for 'fa' language if doc is not parsed.STRING
HIGHspacy/tests/lang/ht/test_noun_chunks.py0test that noun_chunks raises value error for 'fa' language if doc is not parsed.STRING
HIGHspacy/tests/lang/nl/test_noun_chunks.py0test that noun_chunks raises value error for 'fa' language if doc is not parsed.STRING
HIGHspacy/tests/lang/nb/test_noun_chunks.py0test that noun_chunks raises value error for 'fa' language if doc is not parsed.STRING
HIGHspacy/tests/lang/de/test_noun_chunks.py0test that noun_chunks raises value error for 'fa' language if doc is not parsed.STRING
HIGHspacy/tests/lang/id/test_noun_chunks.py0test that noun_chunks raises value error for 'fa' language if doc is not parsed.STRING
HIGHspacy/tests/lang/fr/test_noun_chunks.py0test that noun_chunks raises value error for 'fa' language if doc is not parsed.STRING
HIGHspacy/tests/lang/es/test_noun_chunks.py0test that noun_chunks raises value error for 'fa' language if doc is not parsed.STRING
HIGHspacy/tests/lang/en/test_noun_chunks.py0test that noun_chunks raises value error for 'fa' language if doc is not parsed.STRING
HIGHspacy/tests/lang/fa/test_noun_chunks.py0test that noun_chunks raises value error for 'fa' language if doc is not parsed.STRING
HIGHspacy/tests/lang/da/test_noun_chunks.py0test that noun_chunks raises value error for 'tr' language if doc is not parsed. to check this test, we're constructing STRING
HIGHspacy/tests/lang/fi/test_noun_chunks.py0test that noun_chunks raises value error for 'tr' language if doc is not parsed. to check this test, we're constructing STRING
HIGHspacy/tests/lang/la/test_noun_chunks.py0test that noun_chunks raises value error for 'tr' language if doc is not parsed. to check this test, we're constructing STRING
HIGHspacy/tests/lang/tr/test_noun_chunks.py0test that noun_chunks raises value error for 'tr' language if doc is not parsed. to check this test, we're constructing STRING
HIGHspacy/lang/sl/examples.py0example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlpSTRING
HIGHspacy/lang/sk/examples.py0example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlpSTRING
HIGHspacy/lang/ur/examples.py0example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlpSTRING
HIGHspacy/lang/da/examples.py0example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlpSTRING
HIGHspacy/lang/kmr/examples.py0example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlpSTRING
HIGHspacy/lang/pl/examples.py0example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlpSTRING
HIGHspacy/lang/vi/examples.py0example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlpSTRING
HIGHspacy/lang/sq/examples.py0example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlpSTRING
HIGHspacy/lang/sv/examples.py0example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlpSTRING
HIGHspacy/lang/he/examples.py0example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlpSTRING
HIGHspacy/lang/ms/examples.py0example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlpSTRING
HIGHspacy/lang/hy/examples.py0example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlpSTRING
HIGHspacy/lang/am/examples.py0example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlpSTRING
HIGHspacy/lang/nn/examples.py0example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlpSTRING
HIGHspacy/lang/ky/examples.py0example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlpSTRING
HIGHspacy/lang/gu/examples.py0example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlpSTRING
HIGHspacy/lang/grc/examples.py0example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlpSTRING
HIGHspacy/lang/ja/examples.py0example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlpSTRING
HIGHspacy/lang/el/examples.py0example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlpSTRING
HIGHspacy/lang/lb/examples.py0example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlpSTRING
HIGHspacy/lang/it/examples.py0example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlpSTRING
HIGHspacy/lang/ca/examples.py0example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlpSTRING
HIGHspacy/lang/cs/examples.py0example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlpSTRING
HIGHspacy/lang/ru/examples.py0example sentences to test spacy and its language models. >>> from spacy.lang.ti.examples import sentences >>> docs = nlpSTRING
58 more matches not shown…
Unused Imports183 hits · 173 pts
SeverityFileLineSnippetContext
LOWspacy/compat.py42CODE
LOWspacy/compat.py28CODE
LOWspacy/compat.py28CODE
LOWspacy/compat.py28CODE
LOWspacy/compat.py30CODE
LOWspacy/compat.py30CODE
LOWspacy/compat.py30CODE
LOWspacy/compat.py36CODE
LOWspacy/compat.py38CODE
LOWspacy/util.py68CODE
LOWspacy/util.py68CODE
LOWspacy/util.py68CODE
LOWspacy/util.py77CODE
LOWspacy/util.py77CODE
LOWspacy/util.py78CODE
LOWspacy/util.py78CODE
LOWspacy/util.py79CODE
LOWspacy/util.py402CODE
LOWspacy/util.py1156CODE
LOWspacy/__init__.py11CODE
LOWspacy/__init__.py11CODE
LOWspacy/__init__.py11CODE
LOWspacy/__init__.py13CODE
LOWspacy/__init__.py17CODE
LOWspacy/__init__.py18CODE
LOWspacy/__init__.py20CODE
LOWspacy/__init__.py22CODE
LOWspacy/__init__.py22CODE
LOWspacy/__init__.py33CODE
LOWspacy/__init__.py33CODE
LOWspacy/schemas.py41CODE
LOWspacy/schemas.py42CODE
LOWspacy/schemas.py43CODE
LOWspacy/pipe_analysis.py11CODE
LOWspacy/ty.py17CODE
LOWspacy/ty.py18CODE
LOWspacy/scorer.py24CODE
LOWspacy/pipeline/__init__.py1CODE
LOWspacy/pipeline/__init__.py2CODE
LOWspacy/pipeline/__init__.py3CODE
LOWspacy/pipeline/__init__.py4CODE
LOWspacy/pipeline/__init__.py5CODE
LOWspacy/pipeline/__init__.py6CODE
LOWspacy/pipeline/__init__.py6CODE
LOWspacy/pipeline/__init__.py6CODE
LOWspacy/pipeline/__init__.py7CODE
LOWspacy/pipeline/__init__.py8CODE
LOWspacy/pipeline/__init__.py9CODE
LOWspacy/pipeline/__init__.py10CODE
LOWspacy/pipeline/__init__.py11CODE
LOWspacy/pipeline/__init__.py12CODE
LOWspacy/pipeline/__init__.py13CODE
LOWspacy/pipeline/__init__.py14CODE
LOWspacy/pipeline/__init__.py15CODE
LOWspacy/pipeline/__init__.py16CODE
LOWspacy/pipeline/__init__.py17CODE
LOWspacy/pipeline/__init__.py18CODE
LOWspacy/pipeline/__init__.py19CODE
LOWspacy/pipeline/__init__.py20CODE
LOWspacy/pipeline/legacy/__init__.py1CODE
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Deep Nesting116 hits · 116 pts
SeverityFileLineSnippetContext
LOWwebsite/setup/jinja_to_js.py458CODE
LOWwebsite/setup/jinja_to_js.py491CODE
LOWwebsite/setup/jinja_to_js.py651CODE
LOWwebsite/setup/jinja_to_js.py675CODE
LOWwebsite/setup/jinja_to_js.py886CODE
LOWwebsite/setup/jinja_to_js.py1022CODE
LOWwebsite/setup/jinja_to_js.py1112CODE
LOWspacy/util.py675CODE
LOWspacy/util.py940CODE
LOWspacy/util.py1810CODE
LOWspacy/language.py838CODE
LOWspacy/language.py1636CODE
LOWspacy/language.py1763CODE
LOWspacy/language.py1996CODE
LOWspacy/pipe_analysis.py17CODE
LOWspacy/pipe_analysis.py81CODE
LOWspacy/scorer.py760CODE
LOWspacy/scorer.py211CODE
LOWspacy/scorer.py262CODE
LOWspacy/scorer.py346CODE
LOWspacy/scorer.py447CODE
LOWspacy/scorer.py583CODE
LOWspacy/scorer.py652CODE
LOWspacy/displacy/render.py153CODE
LOWspacy/pipeline/functions.py82CODE
LOWspacy/pipeline/functions.py138CODE
LOWspacy/pipeline/tok2vec.py278CODE
LOWspacy/pipeline/lemmatizer.py172CODE
LOWspacy/pipeline/edit_tree_lemmatizer.py156CODE
LOWspacy/pipeline/edit_tree_lemmatizer.py176CODE
LOWspacy/pipeline/edit_tree_lemmatizer.py197CODE
LOWspacy/pipeline/entityruler.py246CODE
LOWspacy/pipeline/spancat.py449CODE
LOWspacy/pipeline/spancat.py558CODE
LOWspacy/pipeline/attributeruler.py190CODE
LOWspacy/pipeline/span_ruler.py322CODE
LOWspacy/pipeline/entity_linker.py338CODE
LOWspacy/pipeline/entity_linker.py460CODE
LOWspacy/pipeline/span_finder.py135CODE
LOWspacy/pipeline/span_finder.py217CODE
LOWspacy/pipeline/textcat.py262CODE
LOWspacy/pipeline/legacy/entity_linker.py139CODE
LOWspacy/pipeline/legacy/entity_linker.py225CODE
LOWspacy/pipeline/legacy/entity_linker.py311CODE
LOWspacy/training/pretrain.py26CODE
LOWspacy/training/initialize.py35CODE
LOWspacy/training/initialize.py210CODE
LOWspacy/training/batchers.py134CODE
LOWspacy/training/augment.py164CODE
LOWspacy/training/augment.py219CODE
LOWspacy/training/iob_utils.py71CODE
LOWspacy/training/iob_utils.py194CODE
LOWspacy/training/loop.py35CODE
LOWspacy/training/loop.py153CODE
LOWspacy/training/loop.py373CODE
LOWspacy/training/corpus.py84CODE
LOWspacy/training/corpus.py184CODE
LOWspacy/training/corpus.py212CODE
LOWspacy/training/corpus.py261CODE
LOWspacy/training/corpus.py311CODE
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Modern Structural Boilerplate102 hits · 98 pts
SeverityFileLineSnippetContext
LOWspacy/util.py439def set_lang_class(name: str, cls: Type["Language"]) -> None:CODE
LOWspacy/util.py1597def set_dot_to_object(config: Config, section: str, value: Any) -> None:CODE
LOWspacy/lookups.py210 def set_table(self, name: str, table: Table) -> None:CODE
LOWspacy/language.py436 def set_factory_meta(cls, name: str, value: "FactoryMeta") -> None:CODE
LOWspacy/displacy/__init__.py257def set_render_wrapper(func: Callable[[str], str]) -> None:CODE
LOWspacy/pipeline/functions.py102 def _set_config(self, config: Dict[str, Any] = {}) -> None:CODE
LOWspacy/pipeline/tok2vec.py123 def set_annotations(self, docs: Sequence[Doc], tokvecses) -> None:CODE
LOWspacy/pipeline/spancat.py380 def set_annotations(self, docs: Iterable[Doc], indices_scores) -> None:CODE
LOWspacy/pipeline/__init__.py22__all__ = [CODE
LOWspacy/pipeline/entity_linker.py460 def set_annotations(self, docs: Iterable[Doc], kb_ids: List[str]) -> None:CODE
LOWspacy/pipeline/span_finder.py135 def set_annotations(self, docs: Iterable[Doc], scores: Floats2d) -> None:STRING
LOWspacy/pipeline/textcat.py170 def set_annotations(self, docs: Iterable[Doc], scores) -> None:STRING
LOWspacy/pipeline/legacy/__init__.py3__all__ = ["EntityLinker_v1"]CODE
LOWspacy/pipeline/legacy/entity_linker.py311 def set_annotations(self, docs: Iterable[Doc], kb_ids: List[str]) -> None:CODE
LOWspacy/kb/__init__.py5__all__ = [CODE
LOWspacy/training/__init__.py20__all__ = [CODE
LOWspacy/cli/init_pipeline.py95def update_lexemes(nlp: Language, jsonl_loc: Path) -> None:CODE
LOWspacy/matcher/__init__.py6__all__ = ["DependencyMatcher", "Matcher", "PhraseMatcher", "levenshtein"]CODE
LOWspacy/lang/sl/__init__.py22__all__ = ["Slovenian"]CODE
LOWspacy/lang/sk/__init__.py16__all__ = ["Slovak"]CODE
LOWspacy/lang/ur/__init__.py19__all__ = ["Urdu"]CODE
LOWspacy/lang/kmr/__init__.py16__all__ = ["Kurmanji"]CODE
LOWspacy/lang/pl/__init__.py55__all__ = ["Polish"]CODE
LOWspacy/lang/vi/__init__.py132 def _set_config(self, config: Dict[str, Any] = {}) -> None:CODE
LOWspacy/lang/vi/__init__.py167__all__ = ["Vietnamese"]CODE
LOWspacy/lang/sq/__init__.py14__all__ = ["Albanian"]CODE
LOWspacy/lang/sv/__init__.py52__all__ = ["Swedish"]CODE
LOWspacy/lang/ga/__init__.py33__all__ = ["Irish"]CODE
LOWspacy/lang/he/__init__.py17__all__ = ["Hebrew"]CODE
LOWspacy/lang/ms/__init__.py24__all__ = ["Malay"]CODE
LOWspacy/lang/hy/__init__.py16__all__ = ["Armenian"]CODE
LOWspacy/lang/am/__init__.py26__all__ = ["Amharic"]CODE
LOWspacy/lang/nn/__init__.py20__all__ = ["NorwegianNynorsk"]CODE
LOWspacy/lang/da/__init__.py23__all__ = ["Danish"]CODE
LOWspacy/lang/mr/__init__.py14__all__ = ["Marathi"]CODE
LOWspacy/lang/ky/__init__.py20__all__ = ["Kyrgyz"]CODE
LOWspacy/lang/gu/__init__.py14__all__ = ["Gujarati"]CODE
LOWspacy/lang/grc/__init__.py22__all__ = ["AncientGreek"]CODE
LOWspacy/lang/ja/__init__.py158 def _set_config(self, config: Dict[str, Any] = {}) -> None:STRING
LOWspacy/lang/ja/__init__.py341__all__ = ["Japanese"]CODE
LOWspacy/lang/el/__init__.py53__all__ = ["Greek"]CODE
LOWspacy/lang/lv/__init__.py14__all__ = ["Latvian"]CODE
LOWspacy/lang/lb/__init__.py20__all__ = ["Luxembourgish"]CODE
LOWspacy/lang/it/__init__.py50__all__ = ["Italian"]CODE
LOWspacy/lang/ca/__init__.py53__all__ = ["Catalan"]CODE
LOWspacy/lang/is/__init__.py14__all__ = ["Icelandic"]CODE
LOWspacy/lang/cs/__init__.py16__all__ = ["Czech"]CODE
LOWspacy/lang/te/__init__.py16__all__ = ["Telugu"]CODE
LOWspacy/lang/ru/__init__.py53__all__ = ["Russian"]CODE
LOWspacy/lang/tl/__init__.py18__all__ = ["Tagalog"]CODE
LOWspacy/lang/ro/__init__.py26__all__ = ["Romanian"]CODE
LOWspacy/lang/hsb/__init__.py18__all__ = ["UpperSorbian"]CODE
LOWspacy/lang/yo/__init__.py16__all__ = ["Yoruba"]CODE
LOWspacy/lang/sa/__init__.py16__all__ = ["Sanskrit"]CODE
LOWspacy/lang/pt/__init__.py23__all__ = ["Portuguese"]CODE
LOWspacy/lang/zh/__init__.py146 def _set_config(self, config: Dict[str, Any] = {}) -> None:STRING
LOWspacy/lang/zh/__init__.py336__all__ = ["Chinese"]STRING
LOWspacy/lang/uk/__init__.py53__all__ = ["Ukrainian"]CODE
LOWspacy/lang/sr/__init__.py21__all__ = ["Serbian"]CODE
LOWspacy/lang/si/__init__.py16__all__ = ["Sinhala"]CODE
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Self-Referential Comments18 hits · 52 pts
SeverityFileLineSnippetContext
MEDIUMwebsite/meta/universe.json100 "# Define the language for the sentence as well as for the spaCy and benepar models",CODE
MEDIUMwebsite/meta/universe.json104 "# Create the pipeline (note, the required models will be downloaded and installed automatically)",CODE
MEDIUMwebsite/meta/universe.json108 "# Create the tree from where we are going to extract the desired noun phrases",CODE
MEDIUMwebsite/meta/universe.json1387 "# Create a new chat bot named Charlie",CODE
MEDIUMwebsite/meta/universe.json3606 "# Create a new DocBin",CODE
MEDIUMspacy/language.py220 # Create the default tokenizer from the default configCOMMENT
MEDIUMspacy/displacy/render.py326 # Create a random ID prefix to make sure parses don't receive theCOMMENT
MEDIUMspacy/pipeline/legacy/entity_linker.py1# This file is present to provide a prior version of the EntityLinker componentCOMMENT
MEDIUMspacy/tests/test_displacy.py457 # Create a doc containing an annotated word and an unannotated HTML tagCOMMENT
MEDIUMspacy/tests/pipeline/test_entity_linker.py151 # Create the Entity Linker component and add it to the pipelineCOMMENT
MEDIUMspacy/tests/pipeline/test_entity_linker.py746 # Create the Entity Linker component and add it to the pipelineCOMMENT
MEDIUMspacy/tests/pipeline/test_entity_linker.py852 # Create the NER and EL components and add them to the pipelineCOMMENT
MEDIUMspacy/tests/pipeline/test_entity_linker.py933 # Create the Entity Linker component with the KB from file, and check the final vocabCOMMENT
MEDIUMspacy/tests/pipeline/test_entity_linker.py1156 # Create a ruler to mark entitiesCOMMENT
MEDIUMspacy/tests/pipeline/test_entity_linker.py1282 # Create the Entity Linker component and add it to the pipelineCOMMENT
MEDIUMspacy/cli/debug_data.py149 # Create the gold corpus to be able to better analyze dataCOMMENT
MEDIUMspacy/cli/debug_data.py903 # Creating a data structure that holds the start andCOMMENT
MEDIUMspacy/lang/lex_attrs.py185 # This function is partially applied so lang code can be passed inCOMMENT
Cross-Language Confusion (JS/TS)4 hits · 28 pts
SeverityFileLineSnippetContext
HIGHwebsite/pages/index.tsx52print("Noun phrases:", [chunk.text for chunk in doc.noun_chunks])CODE
HIGHwebsite/pages/index.tsx53print("Verbs:", [token.lemma_ for token in doc if token.pos_ == "VERB"])CODE
HIGHwebsite/pages/index.tsx57 print(entity.text, entity.label_)CODE
HIGHwebsite/src/widgets/quickstart-models.js105 print([CODE
Excessive Try-Catch Wrapping21 hits · 22 pts
SeverityFileLineSnippetContext
LOWsetup.py136 except Exception:CODE
LOWsetup.py144 except Exception:CODE
LOWspacy/util.py890 except Exception:CODE
LOWspacy/util.py1777 except Exception as e:CODE
LOWspacy/language.py1057 except Exception as e:CODE
LOWspacy/language.py2417 except Exception:CODE
LOWspacy/pipeline/lemmatizer.py113 except Exception as e:CODE
LOWspacy/pipeline/entityruler.py125 except Exception as e:CODE
LOWspacy/pipeline/attributeruler.py134 except Exception as e:CODE
LOWspacy/pipeline/span_ruler.py224 except Exception as e:CODE
LOWspacy/training/loop.py126 except Exception as e:CODE
LOWspacy/training/loop.py385 except Exception as e:CODE
LOWspacy/tests/test_models.py163 except Exception:CODE
LOWspacy/tests/test_models.py173 except Exception:CODE
LOWspacy/tests/serialize/test_resource_warning.py117 except Exception as e:CODE
LOWspacy/tests/serialize/test_resource_warning.py131 except Exception as e:CODE
LOWspacy/tests/serialize/test_resource_warning.py137 except Exception as e:CODE
LOWspacy/cli/_util.py195 except Exception as e:CODE
LOWspacy/cli/info.py159 except Exception:CODE
LOWspacy/cli/info.py197 except Exception:CODE
LOWspacy/cli/debug_model.py146 except Exception:CODE
AI Structural Patterns21 hits · 20 pts
SeverityFileLineSnippetContext
LOWsetup.py129CODE
LOWspacy/util.py1380CODE
LOWspacy/language.py768CODE
LOWspacy/language.py1763CODE
LOWspacy/displacy/__init__.py76CODE
LOWspacy/pipeline/entityruler.py42CODE
LOWspacy/pipeline/spancat.py203CODE
LOWspacy/pipeline/span_ruler.py123CODE
LOWspacy/tests/test_language.py285CODE
LOWspacy/cli/package.py22CODE
LOWspacy/cli/package.py109CODE
LOWspacy/cli/benchmark_speed.py23CODE
LOWspacy/cli/init_pipeline.py24CODE
LOWspacy/cli/convert.py48CODE
LOWspacy/cli/convert.py129CODE
LOWspacy/cli/find_threshold.py27CODE
LOWspacy/cli/evaluate.py19CODE
LOWspacy/cli/evaluate.py87CODE
LOWspacy/cli/debug_model.py36CODE
LOWspacy/cli/debug_model.py250CODE
LOWspacy/cli/apply.py69CODE
Cross-Language Confusion3 hits · 15 pts
SeverityFileLineSnippetContext
HIGHspacy/tests/parser/test_state.py28 state.push()CODE
HIGHspacy/tests/parser/test_state.py32 state.push()CODE
HIGHspacy/tests/parser/test_state.py45 state.push()CODE
Fake / Example Data10 hits · 14 pts
SeverityFileLineSnippetContext
LOWwebsite/meta/universe.json744 "# [{'end': 8, 'start': 0, 'text': 'John Doe', 'type': 'PERSON'}, {'end': 25, 'start': 13, 'text': 'Go DCODE
LOWspacy/glossary.py314 "ph": "placeholder",CODE
LOWspacy/tests/tokenizer/test_whitespace.py4@pytest.mark.parametrize("text", ["lorem ipsum"])CODE
LOWspacy/tests/tokenizer/test_whitespace.py17@pytest.mark.parametrize("text", ["lorem ipsum "])CODE
LOWspacy/tests/tokenizer/test_tokenizer.py317 text = "Lorem ipsum: 1984."CODE
LOWspacy/tests/tokenizer/test_tokenizer.py350 text = """Lorem ipsum dolor sit amet, consectetur adipiscing elitCODE
LOWspacy/tests/tokenizer/test_tokenizer.py350 text = """Lorem ipsum dolor sit amet, consectetur adipiscing elitCODE
LOWspacy/tests/tokenizer/test_tokenizer.py374 text1 = "Lorem dolor sit amet, consectetur adipiscing elit."CODE
LOWspacy/tests/tokenizer/test_tokenizer.py375 text2 = "Lorem ipsum dolor sit amet, consectetur adipiscing elit."CODE
LOWspacy/tests/tokenizer/test_tokenizer.py375 text2 = "Lorem ipsum dolor sit amet, consectetur adipiscing elit."CODE
AI Slop Vocabulary9 hits · 14 pts
SeverityFileLineSnippetContext
MEDIUMwebsite/meta/universe.json9 "description": "**[Temporal Expressions Normalization spaCy (TeNs)](https://github.com/iliedorobat/timespan-CODE
MEDIUMwebsite/meta/universe.json5396 "# floret n-gram embeddings robust to typos",CODE
LOWspacy/schemas.py102 # binding=True. Here we just use an empty model that allows everything.COMMENT
LOWspacy/scorer.py724 # None is indistinct, so we can't just add it to the setCOMMENT
LOWspacy/training/loggers.py120 # If we don't have a new checkpoint, just return.COMMENT
LOWspacy/tests/test_factory_registrations.py59 # For Cython functions, just use a placeholderCOMMENT
LOWspacy/lang/ja/__init__.py77 # if there's no lemma info (it's an unk) just use the surfaceSTRING
LOWspacy/lang/ht/lemmatizer.py39 # fallback rule: just return lowercased formCOMMENT
LOWspacy/ml/_precomputable_affine.py44 # However, we avoid building that array for efficiency -- and just passCOMMENT
Redundant / Tautological Comments6 hits · 7 pts
SeverityFileLineSnippetContext
LOWspacy/util.py418 # Check if language is registered / entry point is availableCOMMENT
LOWspacy/language.py2065 # Check if the path actually exists in the configCOMMENT
LOWspacy/lang/it/syntax_iterators.py57 elif right_child.dep in np_modifs: # Check if we can expand to rightCODE
LOWspacy/lang/pt/syntax_iterators.py56 elif right_child.dep in np_modifs: # Check if we can expand to rightCODE
LOWspacy/lang/fr/syntax_iterators.py58 elif right_child.dep in np_modifs: # Check if we can expand to rightCODE
LOWspacy/lang/es/syntax_iterators.py47 elif right_child.dep in np_modifs: # Check if we can expand to rightCODE
Over-Commented Block3 hits · 3 pts
SeverityFileLineSnippetContext
LOWspacy/default_config.cfg41# Whether to train on sequences with 'gold standard' sentence boundariesCOMMENT
LOWspacy/lang/nl/stop_words.py1# The original stop words list (added in f46ffe3) was taken fromCOMMENT
LOWspacy/ml/_precomputable_affine.py21 W = model.get_param("W")COMMENT
Modern AI Meta-Vocabulary1 hit · 2 pts
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MEDIUMwebsite/meta/universe.json444 "# zero shot definition of entities",CODE
Slop Phrases1 hit · 2 pts
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MEDIUMwebsite/meta/universe.json1768 "# For instance you can add the BertTone model for classification of sentiment polarity to the pipeline:CODE