py-why/dowhy

26.9

Adjusted Score

26.9

Raw Score

100%

Time Factor

2026-07-14

Last Push

8.2K

Stars

Python

Language

56.1K

Lines of Code

300

Files

1.2K

Pattern Hits

2026-07-14

Scan Date

0.14

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 1HIGH 42MEDIUM 41LOW 1121

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 1205 distinct pattern matches across 19 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 Identifiers760 hits · 823 pts

Severity	File	Line	Snippet	Context
LOW	test_parallel_refuters.py	33	"def _simulate_confounders_effect_once(" in aucc_content	CODE
LOW	tests/test_datasets.py	6	def test_when_generating_sales_dataset_then_returns_reasonable_samples():	CODE
LOW	tests/test_datasets.py	19	def test_linear_dataset_with_binary_treatment():	CODE
LOW	tests/test_datasets.py	33	def test_linear_dataset_with_categorical_treatment():	CODE
LOW	tests/test_causal_model.py	381	def test_cate_estimates_regression(self, beta, num_effect_modifiers, num_samples):	STRING
LOW	tests/test_causal_model.py	406	def test_estimate_conditional_effects_public_api(self):	STRING
LOW	tests/test_causal_model.py	567	def test_unobserved_graph_variables_log_warning(self, caplog):	STRING
LOW	tests/test_causal_model.py	627	def test_compability_with_gcm(self):	STRING
LOW	tests/test_causal_model.py	651	def test_incorrect_graph_format(self):	STRING
LOW	tests/test_causal_model.py	661	def test_warn_when_treatment_not_in_data(self):	STRING
LOW	tests/test_causal_model.py	672	def test_warn_when_outcome_not_in_data(self):	CODE
LOW	tests/test_causal_model.py	683	def test_no_warn_when_treatment_and_outcome_in_data(self):	CODE
LOW	tests/test_causal_model.py	700	def test_causal_estimator_cache(self):	CODE
LOW	tests/test_causal_model.py	743	def test_refute_estimate_raises_when_method_name_is_none(self):	CODE
LOW	tests/test_causal_model.py	765	def test_do_raises_when_method_name_is_none(self):	CODE
LOW	tests/test_causal_model.py	783	def test_estimate_effect_raises_when_method_name_is_none(self):	CODE
LOW	tests/test_causal_model.py	801	def test_fit_estimator_false_reuses_cached_estimator(self):	CODE
LOW	tests/test_causal_model.py	857	def test_causal_model_do_regression(self):	CODE
LOW	tests/test_causal_model.py	900	def test_repr_matches_str_for_key_result_objects(self):	CODE
LOW	tests/test_data_transformer.py	10	def test_dimensionality_reducer_placeholder_methods():	CODE
LOW	tests/test_causal_estimator.py	13	def test_causal_estimator_placeholder_methods():	CODE
LOW	tests/test_causal_estimator.py	30	# def test_average_treatment_effect(self):	COMMENT
LOW	tests/test_causal_estimator.py	36	# def test_average_treatment_effect_on_treated(self):	COMMENT
LOW	tests/test_causal_estimator.py	48	def test_estimate_effect_warns_on_nan_in_treatment_or_outcome():	CODE
LOW	tests/test_causal_estimator.py	88	def test_estimate_effect_no_warning_when_no_nan():	CODE
LOW	tests/test_causal_estimator.py	117	def test_estimate_effect_raises_valueerror_for_missing_estimand():	CODE
LOW	tests/test_confounder_distribution_interpreter.py	36	def test_confounder_distribution_interpreter_with_categorical_confounder(mock_show):	CODE
LOW	tests/test_confounder_distribution_interpreter.py	49	def test_confounder_distribution_interpreter_with_integer_confounder(mock_show):	CODE
LOW⚡	tests/test_causal_refuter.py	14	def test_causal_refuter_placeholder_method():	CODE
LOW⚡	tests/test_causal_refuter.py	21	def test_causal_refuter_bootstrap_test():	CODE
LOW⚡	tests/test_causal_refuter.py	29	def test_normal_distribution_test_zero_std_returns_one():	CODE
LOW⚡	tests/test_causal_refuter.py	47	def test_choose_variables_true_returns_all():	CODE
LOW⚡	tests/test_causal_refuter.py	53	def test_choose_variables_false_returns_none():	CODE
LOW⚡	tests/test_causal_refuter.py	59	def test_choose_variables_int_returns_correct_count():	CODE
LOW⚡	tests/test_causal_refuter.py	66	def test_choose_variables_int_zero_returns_empty():	CODE
LOW⚡	tests/test_causal_refuter.py	72	def test_choose_variables_int_too_large_raises():	CODE
LOW⚡	tests/test_causal_refuter.py	78	def test_choose_variables_list_select_returns_subset():	CODE
LOW⚡	tests/test_causal_refuter.py	84	def test_choose_variables_list_deselect_returns_complement():	CODE
LOW⚡	tests/test_causal_refuter.py	90	def test_choose_variables_list_deselect_all_returns_empty():	CODE
LOW⚡	tests/test_causal_refuter.py	96	def test_choose_variables_list_mixed_select_deselect_raises():	CODE
LOW⚡	tests/test_causal_refuter.py	102	def test_choose_variables_list_invalid_variable_raises():	CODE
LOW⚡	tests/test_causal_refuter.py	108	def test_choose_variables_empty_pool_true_returns_empty():	CODE
LOW⚡	tests/test_causal_refuter.py	114	def test_choose_variables_empty_pool_false_returns_none():	CODE
LOW	tests/test_causal_graph.py	58	def test_check_valid_backdoor_set(self):	CODE
LOW	tests/test_causal_graph.py	120	def test_build_graph_from_str(self):	CODE
LOW⚡	tests/test_causal_graph.py	131	def test_identify_mediation_single_mediator():	CODE
LOW⚡	tests/test_causal_graph.py	138	def test_identify_mediation_parallel_mediators():	CODE
LOW⚡	tests/test_causal_graph.py	148	def test_identify_mediation_no_mediator():	CODE
LOW⚡	tests/test_causal_graph.py	155	def test_nie_with_parallel_mediators():	CODE
LOW	tests/test_propensity_balance_interpreter.py	58	def test_interpreter_with_standard_covariate_names(self):	CODE
LOW	tests/test_propensity_balance_interpreter.py	66	def test_interpreter_with_arbitrary_covariate_names(self):	CODE
LOW⚡	tests/test_propensity_balance_interpreter.py	78	def test_interpreter_returns_dataframe(self):	CODE
LOW⚡	tests/test_propensity_balance_interpreter.py	87	def test_interpreter_with_snake_case_method_name(self):	CODE
LOW⚡	tests/test_propensity_balance_interpreter.py	93	def test_interpreter_with_multiple_method_names_returns_list(self):	CODE
LOW	…/causal_estimators/test_linear_regression_estimator.py	151	def test_average_treatment_effect(	CODE
LOW	…/causal_estimators/test_linear_regression_estimator.py	182	def test_general_adjustment_estimation_on_example_graphs(self, example_graph: TestGraphObject):	CODE
LOW	…/causal_estimators/test_linear_regression_estimator.py	195	def test_none_identifier_method_does_not_raise(self):	CODE
LOW	…/causal_estimators/test_linear_regression_estimator.py	217	def test_test_significance_returns_scalar_float_for_single_treatment(self):	CODE
LOW	…/causal_estimators/test_linear_regression_estimator.py	249	def test_test_significance_returns_array_for_multiple_treatments(self):	CODE
LOW	…/causal_estimators/test_linear_regression_estimator.py	279	def test_invalid_identifier_method_raises(self, invalid_method):	CODE
700 more matches not shown…

Cross-File Repetition38 hits · 190 pts

Severity	File	Snippet	Context
HIGH	dowhy/causal_estimators/econml.py	:param identified_estimand: probability expression representing the target identified estimand to estimate. :param test_	STRING
HIGH	…sal_estimators/propensity_score_weighting_estimator.py	:param identified_estimand: probability expression representing the target identified estimand to estimate. :param test_	STRING
HIGH	…hy/causal_estimators/two_stage_regression_estimator.py	:param identified_estimand: probability expression representing the target identified estimand to estimate. :param test_	STRING
HIGH	…ausal_estimators/regression_discontinuity_estimator.py	:param identified_estimand: probability expression representing the target identified estimand to estimate. :param test_	STRING
HIGH	…usal_estimators/propensity_score_matching_estimator.py	:param identified_estimand: probability expression representing the target identified estimand to estimate. :param test_	STRING
HIGH	dowhy/causal_estimators/propensity_score_estimator.py	:param identified_estimand: probability expression representing the target identified estimand to estimate. :param test_	STRING
HIGH	dowhy/causal_estimators/linear_regression_estimator.py	:param identified_estimand: probability expression representing the target identified estimand to estimate. :param test_	STRING
HIGH	dowhy/causal_estimators/regression_estimator.py	:param identified_estimand: probability expression representing the target identified estimand to estimate. :param test_	STRING
HIGH	dowhy/causal_estimators/causalml.py	:param identified_estimand: probability expression representing the target identified estimand to estimate. :param test_	STRING
HIGH	…y/causal_estimators/instrumental_variable_estimator.py	:param identified_estimand: probability expression representing the target identified estimand to estimate. :param test_	STRING
HIGH	dowhy/causal_estimators/distance_matching_estimator.py	:param identified_estimand: probability expression representing the target identified estimand to estimate. :param test_	STRING
HIGH	…stimators/propensity_score_stratification_estimator.py	:param identified_estimand: probability expression representing the target identified estimand to estimate. :param test_	STRING
HIGH	dowhy/causal_estimators/doubly_robust_estimator.py	:param identified_estimand: probability expression representing the target identified estimand to estimate. :param test_	STRING
HIGH	dowhy/causal_estimators/econml.py	fits the estimator with data for effect estimation :param data: data frame containing the data :param treatment: name of	STRING
HIGH	dowhy/causal_estimators/tabpfn_estimator.py	fits the estimator with data for effect estimation :param data: data frame containing the data :param treatment: name of	STRING
HIGH	…sal_estimators/propensity_score_weighting_estimator.py	fits the estimator with data for effect estimation :param data: data frame containing the data :param treatment: name of	STRING
HIGH	…ausal_estimators/regression_discontinuity_estimator.py	fits the estimator with data for effect estimation :param data: data frame containing the data :param treatment: name of	STRING
HIGH	…usal_estimators/propensity_score_matching_estimator.py	fits the estimator with data for effect estimation :param data: data frame containing the data :param treatment: name of	STRING
HIGH	dowhy/causal_estimators/linear_regression_estimator.py	fits the estimator with data for effect estimation :param data: data frame containing the data :param treatment: name of	STRING
HIGH	dowhy/causal_estimators/causalml.py	fits the estimator with data for effect estimation :param data: data frame containing the data :param treatment: name of	STRING
HIGH	…y/causal_estimators/instrumental_variable_estimator.py	fits the estimator with data for effect estimation :param data: data frame containing the data :param treatment: name of	STRING
HIGH	…ausal_estimators/generalized_linear_model_estimator.py	fits the estimator with data for effect estimation :param data: data frame containing the data :param treatment: name of	STRING
HIGH	…stimators/propensity_score_stratification_estimator.py	fits the estimator with data for effect estimation :param data: data frame containing the data :param treatment: name of	STRING
HIGH	dowhy/causal_estimators/regression_estimator.py	fits the estimator with data for effect estimation :param data: data frame containing the data :param treatment: name of	STRING
HIGH	dowhy/causal_estimators/econml.py	data: dataframe containing the data on which treatment effect is to be estimated. treatment_value: value of the treatmen	STRING
HIGH	dowhy/causal_estimators/causalml.py	data: dataframe containing the data on which treatment effect is to be estimated. treatment_value: value of the treatmen	STRING
HIGH	…y/causal_estimators/instrumental_variable_estimator.py	data: dataframe containing the data on which treatment effect is to be estimated. treatment_value: value of the treatmen	STRING
HIGH	dowhy/causal_refuters/overrule/ruleset.py	overlapbooleanrule. this module implements the boolean ruleset estimator from overrule [1]. code is adapted (with some s	STRING
HIGH	dowhy/causal_refuters/overrule/utils.py	overlapbooleanrule. this module implements the boolean ruleset estimator from overrule [1]. code is adapted (with some s	STRING
HIGH	…/causal_refuters/overrule/BCS/load_process_data_BCS.py	overlapbooleanrule. this module implements the boolean ruleset estimator from overrule [1]. code is adapted (with some s	STRING
HIGH	dowhy/causal_refuters/overrule/BCS/beam_search.py	overlapbooleanrule. this module implements the boolean ruleset estimator from overrule [1]. code is adapted (with some s	STRING
HIGH	…y/causal_refuters/overrule/BCS/overlap_boolean_rule.py	overlapbooleanrule. this module implements the boolean ruleset estimator from overrule [1]. code is adapted (with some s	STRING
HIGH	dowhy/graph_learners/ges.py	discover causal graph and return the graph in dot format.	STRING
HIGH	dowhy/graph_learners/cdt.py	discover causal graph and return the graph in dot format.	STRING
HIGH	dowhy/graph_learners/lingam.py	discover causal graph and return the graph in dot format.	STRING
HIGH	dowhy/utils/dgps/quadratic_dgp.py	implements a data generating process that returns data having linear relationship between the treatment, outcome and con	STRING
HIGH	dowhy/utils/dgps/cubic_dgp.py	implements a data generating process that returns data having linear relationship between the treatment, outcome and con	STRING
HIGH	dowhy/utils/dgps/linear_dgp.py	implements a data generating process that returns data having linear relationship between the treatment, outcome and con	STRING

Unused Imports160 hits · 140 pts

Severity	File	Line	Context
LOW	test_parallel_refuters.py	8	CODE
LOW	tests/test_confounder_distribution_interpreter.py	17	CODE
LOW	tests/test_causal_graph.py	4	CODE
LOW	tests/test_causal_graph.py	5	CODE
LOW	tests/test_causal_graph.py	11	CODE
LOW	tests/causal_estimators/mock_external_estimator.py	1	CODE
LOW	tests/timeseries/test_temporal_shift.py	2	CODE
LOW	tests/timeseries/test_temporal_shift.py	2	CODE
LOW	tests/gcm/test_anomaly.py	24	CODE
LOW	tests/gcm/test_feature_relevance.py	8	CODE
LOW	tests/gcm/test_model_evaluation.py	7	CODE
LOW	tests/gcm/test_intrinsic_influence.py	20	CODE
LOW	tests/gcm/ml/test_autogluon.py	5	CODE
LOW	tests/utils/test_plotting.py	8	CODE
LOW	tests/utils/test_encoding.py	1	CODE
LOW	tests/utils/test_encoding.py	2	CODE
LOW	…sal_identifiers/test_complete_adjustment_identifier.py	3	CODE
LOW	tests/causal_identifiers/test_backdoor_identifier.py	1	CODE
LOW	tests/causal_identifiers/test_frontdoor_identifier.py	3	CODE
LOW	tests/causal_identifiers/test_frontdoor_identifier.py	6	CODE
LOW	tests/causal_identifiers/test_frontdoor_identifier.py	6	CODE
LOW	tests/causal_identifiers/test_frontdoor_identifier.py	8	CODE
LOW	…discovery-book/test_causal_inference_discovery_book.py	11	CODE
LOW	…discovery-book/test_causal_inference_discovery_book.py	11	CODE
LOW	dowhy/__init__.py	3	CODE
LOW	dowhy/__init__.py	3	CODE
LOW	dowhy/__init__.py	3	CODE
LOW	dowhy/__init__.py	3	CODE
LOW	dowhy/__init__.py	4	CODE
LOW	dowhy/causal_identifier/id_identifier.py	1	CODE
LOW	dowhy/causal_identifier/__init__.py	1	CODE
LOW	dowhy/causal_identifier/__init__.py	1	CODE
LOW	dowhy/causal_identifier/__init__.py	1	CODE
LOW	dowhy/causal_identifier/__init__.py	1	CODE
LOW	dowhy/causal_identifier/__init__.py	1	CODE
LOW	dowhy/causal_identifier/__init__.py	1	CODE
LOW	dowhy/causal_identifier/__init__.py	1	CODE
LOW	dowhy/causal_identifier/__init__.py	1	CODE
LOW	dowhy/causal_identifier/__init__.py	11	CODE
LOW	dowhy/causal_identifier/__init__.py	11	CODE
LOW	dowhy/causal_identifier/__init__.py	12	CODE
LOW	dowhy/causal_identifier/__init__.py	13	CODE
LOW	dowhy/causal_estimators/tabpfn_estimator.py	1	CODE
LOW	…usal_estimators/propensity_score_matching_estimator.py	3	CODE
LOW	dowhy/timeseries/temporal_shift.py	2	CODE
LOW	dowhy/timeseries/temporal_shift.py	2	CODE
LOW	dowhy/timeseries/temporal_shift.py	2	CODE
LOW	dowhy/causal_refuters/data_subset_refuter.py	10	CODE
LOW	dowhy/causal_refuters/placebo_treatment_refuter.py	12	CODE
LOW	dowhy/causal_refuters/evalue_sensitivity_analyzer.py	10	CODE
LOW	dowhy/causal_refuters/bootstrap_refuter.py	12	CODE
LOW	dowhy/causal_refuters/__init__.py	5	CODE
LOW	dowhy/causal_refuters/__init__.py	5	CODE
LOW	dowhy/causal_refuters/__init__.py	5	CODE
LOW	dowhy/causal_refuters/__init__.py	10	CODE
LOW	dowhy/causal_refuters/__init__.py	10	CODE
LOW	dowhy/causal_refuters/__init__.py	11	CODE
LOW	dowhy/causal_refuters/__init__.py	11	CODE
LOW	dowhy/causal_refuters/__init__.py	12	CODE
LOW	dowhy/causal_refuters/__init__.py	12	CODE
100 more matches not shown…

Self-Referential Comments33 hits · 78 pts

Severity	File	Line	Snippet	Context
MEDIUM	…usal_estimators/test_two_stage_regression_estimator.py	86	# Create the graph describing the causal structure	COMMENT
MEDIUM	…usal_estimators/test_two_stage_regression_estimator.py	142	# Create a model	STRING
MEDIUM	tests/causal_estimators/test_causalml_estimator.py	36	# Create a model that captures the same	COMMENT
MEDIUM	tests/causal_estimators/test_causalml_estimator.py	61	# Create a model that captures the same	COMMENT
MEDIUM	tests/causal_estimators/test_causalml_estimator.py	86	# Create a model that captures the same	COMMENT
MEDIUM	tests/causal_estimators/test_causalml_estimator.py	113	# Create a model that captures the same	COMMENT
MEDIUM	tests/causal_estimators/test_causalml_estimator.py	138	# Create a model that captures the same	COMMENT
MEDIUM	tests/causal_estimators/base.py	307	# Create a copy of the data and swap the rows.	COMMENT
MEDIUM	…/causal_estimators/test_distance_matching_estimator.py	153	# Create a categorical common cause	COMMENT
MEDIUM	…ts/causal_refuters/test_add_unobserved_common_cause.py	266	# Creating a model with no unobserved confounders	COMMENT
MEDIUM	tests/gcm/test_anomaly.py	334	{"X0": X0[:1], "X1": X1[:1] + np.std(X1.data) * 3, "X2": X2[:1], "X3": X3[:1]} # Creating an anomaly here	CODE
MEDIUM	tests/gcm/test_anomaly_attribution.py	31	# Defining an anomaly scorer that handles multidimensional inputs.	COMMENT
MEDIUM	tests/gcm/test_anomaly_attribution.py	84	# Defining an anomaly scorer that handles multidimensional inputs.	COMMENT
MEDIUM	…discovery-book/test_causal_inference_discovery_book.py	72	# Define the true effect	COMMENT
MEDIUM	…discovery-book/test_causal_inference_discovery_book.py	145	# Create the graph describing the causal structure	COMMENT
MEDIUM	docs/generate_docs.sh	54	# Create the top-level index.html	COMMENT
MEDIUM	dowhy/datasets.py	892	# Creating a NN to simulate the nuisance function	COMMENT
MEDIUM	dowhy/datasets.py	969	# The following code for loading the Lalonde dataset was copied from	COMMENT
MEDIUM	dowhy/datasets.py	1010	# The following code is a slight modification of	COMMENT
MEDIUM	dowhy/causal_model.py	351	# Define the third-party estimation method to be used	COMMENT
MEDIUM	dowhy/gcm/unit_change.py	1	"""This module provides the APIs for attributing the change in the output value of a deterministic mechanism for a stati	STRING
MEDIUM	dowhy/gcm/whatif.py	1	"""This module provides functionality to answer what-if questions."""	STRING
MEDIUM	dowhy/gcm/causal_mechanisms.py	1	"""This module implements different causal mechanisms."""	STRING
MEDIUM	dowhy/gcm/fitting_sampling.py	1	"""This module provides functionality for fitting probabilistic causal models and drawing samples from them."""	STRING
MEDIUM	dowhy/gcm/confidence_intervals.py	1	"""This module provides functionality to estimate confidence intervals via bootstrapping."""	STRING
MEDIUM	dowhy/gcm/influence.py	1	"""This module provides functions to estimate causal influences."""	STRING
MEDIUM	dowhy/gcm/influence.py	81	# Creating a smaller subgraph, which only contains upstream nodes that are connected to the target node.	COMMENT
MEDIUM	dowhy/gcm/influence.py	273	# Creating a smaller subgraph, which only contains upstream nodes that are connected to the target node.	COMMENT
MEDIUM	dowhy/gcm/confidence_intervals_cms.py	1	"""This module provides functionality to estimate confidence intervals via bootstrapping the fitting and sampling."""	STRING
MEDIUM	dowhy/gcm/shapley.py	1	"""This module provides functionality for shapley value estimation."""	STRING
MEDIUM	dowhy/gcm/falsify.py	1	"""This module provides functionality to falsify a user-given DAG given observed data."""	STRING
MEDIUM	dowhy/utils/timeseries.py	207	# Create a new edge with a tuple containing the time lag	COMMENT
MEDIUM	dowhy/utils/timeseries.py	216	# Create a new edge with a tuple containing the time lag	COMMENT

Deep Nesting73 hits · 73 pts

Severity	File	Line	Context
LOW	tests/causal_refuters/base.py	34	CODE
LOW	tests/gcm/ml/test_classification.py	31	CODE
LOW	tests/gcm/ml/test_classification.py	32	CODE
LOW	…usal_identifiers/test_efficient_backdoor_identifier.py	11	CODE
LOW	dowhy/causal_refuter.py	80	CODE
LOW	dowhy/causal_graph.py	28	CODE
LOW	dowhy/causal_graph.py	90	CODE
LOW	dowhy/graph.py	366	CODE
LOW	dowhy/graph.py	435	CODE
LOW	dowhy/datasets.py	631	CODE
LOW	dowhy/datasets.py	646	CODE
LOW	dowhy/datasets.py	686	CODE
LOW	dowhy/causal_model.py	21	CODE
LOW	dowhy/causal_model.py	271	CODE
LOW	dowhy/causal_model.py	549	CODE
LOW	dowhy/causal_identifier/backdoor.py	137	CODE
LOW	dowhy/causal_identifier/backdoor.py	249	CODE
LOW	dowhy/causal_identifier/efficient_backdoor.py	196	CODE
LOW	dowhy/causal_identifier/efficient_backdoor.py	250	CODE
LOW	dowhy/causal_identifier/auto_identifier.py	154	CODE
LOW	…hy/causal_estimators/two_stage_regression_estimator.py	165	CODE
LOW	dowhy/causal_estimators/distance_matching_estimator.py	172	CODE
LOW	dowhy/timeseries/temporal_shift.py	8	CODE
LOW	dowhy/timeseries/temporal_shift.py	78	CODE
LOW	dowhy/causal_refuters/placebo_treatment_refuter.py	97	CODE
LOW	dowhy/causal_refuters/evalue_sensitivity_analyzer.py	96	CODE
LOW	dowhy/causal_refuters/bootstrap_refuter.py	95	CODE
LOW	dowhy/causal_refuters/linear_sensitivity_analyzer.py	224	CODE
LOW	dowhy/causal_refuters/dummy_outcome_refuter.py	258	CODE
LOW	dowhy/causal_refuters/dummy_outcome_refuter.py	728	CODE
LOW	dowhy/causal_refuters/dummy_outcome_refuter.py	871	CODE
LOW	dowhy/causal_refuters/dummy_outcome_refuter.py	894	CODE
LOW	dowhy/causal_refuters/add_unobserved_common_cause.py	847	CODE
LOW	dowhy/causal_refuters/add_unobserved_common_cause.py	137	CODE
LOW	dowhy/causal_refuters/graph_refuter.py	69	CODE
LOW	dowhy/causal_refuters/overrule/utils.py	41	CODE
LOW	…/causal_refuters/overrule/BCS/load_process_data_BCS.py	67	CODE
LOW	…/causal_refuters/overrule/BCS/load_process_data_BCS.py	132	CODE
LOW	dowhy/causal_refuters/overrule/BCS/beam_search.py	56	CODE
LOW	…y/causal_refuters/overrule/BCS/overlap_boolean_rule.py	291	CODE
LOW	dowhy/gcm/model_evaluation.py	416	CODE
LOW	dowhy/gcm/model_evaluation.py	634	CODE
LOW	dowhy/gcm/model_evaluation.py	762	CODE
LOW	dowhy/gcm/model_evaluation.py	783	CODE
LOW	dowhy/gcm/model_evaluation.py	182	CODE
LOW	dowhy/gcm/model_evaluation.py	427	CODE
LOW	dowhy/gcm/equation_parser.py	38	CODE
LOW	dowhy/gcm/distribution_change_robust.py	203	CODE
LOW	dowhy/gcm/distribution_change_robust.py	294	CODE
LOW	dowhy/gcm/influence.py	160	CODE
LOW	dowhy/gcm/shapley.py	77	CODE
LOW	dowhy/gcm/shapley.py	289	CODE
LOW	dowhy/gcm/data_generator.py	229	CODE
LOW	dowhy/gcm/falsify.py	304	CODE
LOW	dowhy/gcm/falsify.py	745	CODE
LOW	dowhy/gcm/falsify.py	964	CODE
LOW	dowhy/gcm/auto.py	185	CODE
LOW	dowhy/gcm/auto.py	401	CODE
LOW	dowhy/gcm/auto.py	513	CODE
LOW	dowhy/gcm/auto.py	548	CODE
13 more matches not shown…

AI Structural Patterns53 hits · 53 pts

Severity	File	Line	Context
LOW	tests/causal_estimators/test_causalml_estimator.py	23	CODE
LOW	tests/causal_estimators/base.py	22	CODE
LOW	tests/causal_estimators/base.py	117	CODE
LOW	tests/causal_refuters/base.py	34	CODE
LOW	dowhy/datasets.py	71	CODE
LOW	dowhy/datasets.py	850	CODE
LOW	dowhy/datasets.py	1040	CODE
LOW	dowhy/causal_estimator.py	56	CODE
LOW	dowhy/causal_model.py	21	CODE
LOW	dowhy/causal_model.py	271	CODE
LOW	dowhy/causal_model.py	499	CODE
LOW	dowhy/causal_identifier/identified_estimand.py	12	CODE
LOW	dowhy/causal_estimators/econml.py	34	CODE
LOW	dowhy/causal_estimators/tabpfn_estimator.py	272	CODE
LOW	…sal_estimators/propensity_score_weighting_estimator.py	27	CODE
LOW	…hy/causal_estimators/two_stage_regression_estimator.py	34	CODE
LOW	…ausal_estimators/regression_discontinuity_estimator.py	21	CODE
LOW	…usal_estimators/propensity_score_matching_estimator.py	28	CODE
LOW	dowhy/causal_estimators/linear_regression_estimator.py	27	CODE
LOW	dowhy/causal_estimators/causalml.py	30	CODE
LOW	…y/causal_estimators/instrumental_variable_estimator.py	31	CODE
LOW	dowhy/causal_estimators/distance_matching_estimator.py	22	CODE
LOW	dowhy/causal_estimators/propensity_score_estimator.py	21	CODE
LOW	…ausal_estimators/generalized_linear_model_estimator.py	26	CODE
LOW	…stimators/propensity_score_stratification_estimator.py	27	CODE
LOW	dowhy/causal_estimators/doubly_robust_estimator.py	27	CODE
LOW	dowhy/causal_estimators/regression_estimator.py	21	CODE
LOW	…causal_refuters/partial_linear_sensitivity_analyzer.py	46	CODE
LOW	…causal_refuters/partial_linear_sensitivity_analyzer.py	522	CODE
LOW	dowhy/causal_refuters/bootstrap_refuter.py	147	CODE
LOW	dowhy/causal_refuters/assess_overlap_overrule.py	109	CODE
LOW	dowhy/causal_refuters/linear_sensitivity_analyzer.py	31	CODE
LOW	dowhy/causal_refuters/linear_sensitivity_analyzer.py	368	CODE
LOW	dowhy/causal_refuters/dummy_outcome_refuter.py	258	CODE
LOW	dowhy/causal_refuters/dummy_outcome_refuter.py	408	CODE
LOW	dowhy/causal_refuters/add_unobserved_common_cause.py	703	CODE
LOW	dowhy/causal_refuters/add_unobserved_common_cause.py	847	CODE
LOW	dowhy/causal_refuters/reisz.py	149	CODE
LOW	dowhy/causal_refuters/overrule/ruleset.py	27	CODE
LOW	…y/causal_refuters/overrule/BCS/overlap_boolean_rule.py	25	CODE
LOW	dowhy/gcm/model_evaluation.py	53	CODE
LOW	dowhy/gcm/distribution_change_robust.py	612	CODE
LOW	dowhy/gcm/distribution_change_robust.py	294	CODE
LOW	dowhy/gcm/distribution_change_robust.py	514	CODE
LOW	dowhy/gcm/influence.py	216	CODE
LOW	dowhy/gcm/distribution_change.py	87	CODE
LOW	dowhy/gcm/distribution_change.py	350	CODE
LOW	dowhy/gcm/falsify.py	518	CODE
LOW	dowhy/gcm/independence_test/kernel.py	113	CODE
LOW	dowhy/gcm/util/plotting.py	50	CODE
LOW	dowhy/utils/plotting.py	113	CODE
LOW	dowhy/api/causal_data_frame.py	35	CODE
LOW	dowhy/causal_prediction/algorithms/cacm.py	9	CODE

Redundant / Tautological Comments27 hits · 41 pts

Severity	File	Line	Snippet	Context
LOW⚡	tests/utils/test_plotting.py	21	# Check if calling the method causes some import or runtime errors	COMMENT
LOW	tests/causal_identifiers/test_optimize_backdoor.py	28	# Check if backdoor sets are valid i.e. if they block all paths between the treatment and the outcome	COMMENT
LOW	tests/causal_identifiers/test_optimize_backdoor.py	77	# Check if backdoor sets are valid i.e. if they block all paths between the treatment and the outcome	COMMENT
LOW	tests/causal_identifiers/test_optimize_backdoor.py	105	# Check if backdoor sets are valid i.e. if they block all paths between the treatment and the outcome	COMMENT
LOW	tests/causal_identifiers/test_optimize_backdoor.py	133	# Check if backdoor sets are valid i.e. if they block all paths between the treatment and the outcome	COMMENT
LOW	tests/causal_identifiers/test_optimize_backdoor.py	161	# Check if backdoor sets are valid i.e. if they block all paths between the treatment and the outcome	COMMENT
LOW	dowhy/causal_refuter.py	119	# Check if all are select or deselect variables	COMMENT
LOW	dowhy/causal_refuter.py	131	# Check if all the required_variables belong to confounders, instrumental variables or effect	COMMENT
LOW	dowhy/datasets.py	737	): # Check if current "node" has not been processed yet and if all the parent nodes have been processed	CODE
LOW	dowhy/causal_estimator.py	116	# Check if some parameters were set, otherwise set to default values	COMMENT
LOW	dowhy/causal_estimator.py	551	# Check if any parameter is changed from the previous std error estimate	COMMENT
LOW	dowhy/causal_estimator.py	887	# Check if estimator's target estimand is identified	COMMENT
LOW	dowhy/causal_model.py	432	# Check if estimator's target estimand is identified	COMMENT
LOW	dowhy/causal_identifier/backdoor.py	166	# Check if path is backdoor and does not have nodes1\node1 or nodes2\node2 as intermediate nodes	COMMENT
LOW	…hy/causal_estimators/two_stage_regression_estimator.py	92	# Check if the treatment is one-dimensional	COMMENT
LOW	dowhy/causal_estimators/distance_matching_estimator.py	136	# Check if the treatment is one-dimensional	COMMENT
LOW	dowhy/causal_estimators/propensity_score_estimator.py	128	# Check if the treatment is one-dimensional	COMMENT
LOW	dowhy/timeseries/temporal_shift.py	59	# Add the parent to the queue for further exploration	COMMENT
LOW	dowhy/causal_refuters/assess_overlap_overrule.py	210	# Check if all supported units are considered to be in the overlap set	COMMENT
LOW	dowhy/causal_refuters/dummy_outcome_refuter.py	608	# Check if we are using an estimator in the transformation list	COMMENT
LOW	dowhy/causal_refuters/overrule/BCS/beam_search.py	159	# Check if duplicate	COMMENT
LOW	dowhy/gcm/whatif.py	175	# Check if we need to apply an intervention on the given node.	COMMENT
LOW	dowhy/gcm/whatif.py	180	# Check if the intervention function changes the shape of the data.	COMMENT
LOW	dowhy/gcm/shapley.py	447	# Check if change in percentage is below threshold	COMMENT
LOW	dowhy/utils/timeseries.py	45	# Check if the edge already exists	COMMENT
LOW	dowhy/utils/timeseries.py	104	# Check if the edge already exists	COMMENT
LOW	dowhy/causal_prediction/algorithms/base_algorithm.py	28	# Check if the optimizer is currently supported	COMMENT

Modern Structural Boilerplate20 hits · 20 pts

Severity	File	Line	Snippet	Context
LOW	dowhy/causal_refuter.py	19	logger = logging.getLogger(__name__)	CODE
LOW	dowhy/__init__.py	39	__all__ = [	CODE
LOW	dowhy/causal_estimator.py	17	logger = logging.getLogger(__name__)	CODE
LOW	dowhy/causal_identifier/__init__.py	15	__all__ = [	CODE
LOW	dowhy/causal_identifier/auto_identifier.py	30	logger = logging.getLogger(__name__)	CODE
LOW	dowhy/causal_estimators/tabpfn_estimator.py	16	logger = logging.getLogger(__name__)	CODE
LOW	dowhy/causal_estimators/causalml.py	19	logger = logging.getLogger(__name__)	CODE
LOW	dowhy/causal_refuters/data_subset_refuter.py	14	logger = logging.getLogger(__name__)	CODE
LOW	dowhy/causal_refuters/placebo_treatment_refuter.py	18	logger = logging.getLogger(__name__)	CODE
LOW	dowhy/causal_refuters/bootstrap_refuter.py	16	logger = logging.getLogger(__name__)	CODE
LOW	dowhy/causal_refuters/__init__.py	33	__all__ = [	CODE
LOW	dowhy/causal_refuters/assess_overlap.py	8	logger = logging.getLogger(__name__)	CODE
LOW	dowhy/causal_refuters/dummy_outcome_refuter.py	21	logger = logging.getLogger(__name__)	CODE
LOW	dowhy/causal_refuters/add_unobserved_common_cause.py	25	logger = logging.getLogger(__name__)	CODE
LOW	dowhy/causal_refuters/random_common_cause.py	15	logger = logging.getLogger(__name__)	CODE
LOW	dowhy/gcm/config.py	15	def set_default_n_jobs(n_jobs: int) -> None:	CODE
LOW	dowhy/gcm/causal_models.py	66	def set_causal_mechanism(self, node: Any, mechanism: Union[StochasticModel, ConditionalStochasticModel]) -> None:	CODE
LOW	dowhy/gcm/causal_models.py	101	def set_causal_mechanism(self, node: Any, mechanism: Union[StochasticModel, FunctionalCausalModel]) -> None:	CODE
LOW	dowhy/gcm/equation_parser.py	35	logger = logging.getLogger(__name__)	CODE
LOW	dowhy/gcm/util/general.py	41	def set_random_seed(random_seed: int) -> None:	CODE

Cross-Language Confusion3 hits · 18 pts

Severity	File	Line	Snippet	Context
HIGH	dowhy/causal_refuter.py	167	"The normal-distribution p-value is undefined; returning p_value=1."	CODE
HIGH	dowhy/causal_refuters/evalue_sensitivity_analyzer.py	425	# if CI crosses null, set its E-value to 1	COMMENT
HIGH	dowhy/gcm/divergence.py	110	D_f(P \|\| Q) = \int f(p(x)/q(x)) q(x) dx ~= -1/N \sum_x log(p(Y = 1 \| x) / (1 - p(Y = 1 \| x)))	CODE

Decorative Section Separators4 hits · 16 pts

Severity	File	Line	Snippet	Context
MEDIUM⚡	tests/test_causal_refuter.py	40	# ---------------------------------------------------------------------------	COMMENT
MEDIUM⚡	tests/test_causal_refuter.py	42	# ---------------------------------------------------------------------------	COMMENT
MEDIUM	tests/causal_prediction/test_causal_prediction.py	9	# ── pure-Python tests (no torch / pytorch-lightning required) ─────────────────	COMMENT
MEDIUM⚡	tests/causal_prediction/test_causal_prediction.py	62	# ── torch-dependent tests (skipped when torch / pl are absent) ────────────────	COMMENT

Excessive Try-Catch Wrapping12 hits · 14 pts

Severity	File	Line	Snippet	Context
LOW	test_parallel_refuters.py	45	except Exception as e:	CODE
LOW	test_parallel_refuters.py	69	except Exception as e:	CODE
LOW	tests/test_causal_estimator.py	84	except Exception:	CODE
MEDIUM	tests/causal_estimators/test_causalml_estimator.py	159	print("Error with respect to the number of samples")	CODE
MEDIUM	tests/causal_estimators/base.py	17	print("Error tolerance is", error_tolerance)	CODE
LOW	dowhy/graph.py	465	except Exception as e:	CODE
LOW	dowhy/graph.py	471	except Exception as e:	CODE
LOW	dowhy/graph.py	482	except Exception as e:	CODE
LOW	dowhy/graph.py	489	except Exception as e:	CODE
LOW	dowhy/causal_estimators/tabpfn_estimator.py	57	except Exception as e:	CODE
LOW	dowhy/utils/encoding.py	54	except Exception as e:	CODE
LOW	dowhy/utils/plotting.py	61	except Exception as error:	CODE

Over-Commented Block12 hits · 12 pts

Severity	File	Line	Snippet	Context
LOW	tests/test_causal_estimator.py	21	class TestCausalEstimator(unittest.TestCase):	COMMENT
LOW	docs/source/conf.py	1	# -- coding: utf-8 --	COMMENT
LOW	docs/source/conf.py	81	# The suffix(es) of source filenames.	COMMENT
LOW	docs/source/conf.py	121	#	COMMENT
LOW	docs/source/conf.py	141		COMMENT
LOW	.github/workflows/repo-assist.lock.yml	1	# gh-aw-metadata: {"schema_version":"v3","frontmatter_hash":"6538abb568ad674ed3bfd5cd20c199190f28c126725f245a8bf6cbc92f9	COMMENT
LOW	.github/workflows/repo-assist.lock.yml	21	# Not all edits will cause changes to this file.	COMMENT
LOW	.github/workflows/repo-assist.lock.yml	41	# - COPILOT_GITHUB_TOKEN	COMMENT
LOW	dowhy/datasets.py	961	"gml_graph": gml_graph,	COMMENT
LOW	dowhy/datasets.py	1001	return lalonde	COMMENT
LOW	dowhy/datasets.py	1021	# 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the	COMMENT
LOW	dowhy/gcm/confidence_intervals_cms.py	21	#	COMMENT

Hallucination Indicators1 hit · 10 pts

Severity	File	Line	Snippet	Context
CRITICAL	dowhy/causal_prediction/models/networks.py	90	tmp = self.network.conv1.weight.data.clone()	CODE

AI Response Leakage1 hit · 8 pts

Severity	File	Line	Snippet	Context
HIGH	dowhy/gcm/confidence_intervals_cms.py	26	# In this example, gcm.confidence_intervals is expecting a callable with non-deterministic outputs for building the	COMMENT

AI Slop Vocabulary2 hits · 4 pts

Severity	File	Line	Snippet	Context
LOW	dowhy/graph.py	248	# First we can just call get_proper_causal_path_nodes, then	COMMENT
MEDIUM	dowhy/causal_estimators/doubly_robust_estimator.py	214	# Doubly robust formula	COMMENT

Fake / Example Data3 hits · 3 pts

Severity	File	Line	Snippet	Context
LOW	tests/causal_refuters/test_assess_overlap.py	10	def dummy_data():	CODE
LOW	tests/causal_refuters/test_assess_overlap.py	34	def refute(dummy_data):	CODE
LOW	tests/causal_refuters/test_assess_overlap.py	35	model = CausalModel(data=dummy_data, treatment="T", outcome="Y", common_causes=["X1", "X2"])	CODE

Modern AI Meta-Vocabulary1 hit · 2 pts

Severity	File	Line	Snippet	Context
MEDIUM	AGENTS.md	23	causal_model.py # CausalModel: orchestrates the 4-step workflow	CODE

Overly Generic Function Names1 hit · 1 pts

Severity	File	Line	Snippet	Context
LOW	dowhy/causal_refuters/dummy_outcome_refuter.py	728	def process_data(	CODE

Verbosity Indicators1 hit · 0 pts

Severity	File	Line	Snippet	Context
LOW	dowhy/causal_refuters/dummy_outcome_refuter.py	754	:param outcome_validation: This variable stores the dummy_outcome generated by the transformations	STRING

Analysis Overview

What These Metrics Mean

Score History

Severity Breakdown

Directory Score Breakdown

Pattern Findings