Repository Analysis

unit8co/darts

A python library for user-friendly forecasting and anomaly detection on time series.

22.3 Moderate AI signal View on GitHub

Analysis Overview

This report presents the forensic synthetic code analysis of unit8co/darts, a Python project with 9,466 GitHub stars. SynthScan v2.0 examined 161,336 lines of code across 331 source files, recording 2194 pattern matches distributed across 16 syntactic categories. The overall adjusted score of 22.3 places this repository in the Moderate 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).

22.3
Adjusted Score
22.3
Raw Score
100%
Time Factor
2026-07-14
Last Push
9.5K
Stars
Python
Language
161.3K
Lines of Code
331
Files
2.2K
Pattern Hits
2026-07-14
Scan Date
0.99
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 328MEDIUM 30LOW 1836

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 2194 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.

Cross-Language Confusion273 hits · 1509 pts
SeverityFileLineSnippetContext
HIGHdarts/timeseries.py5274 if not self._time_index.equals(other._time_index):CODE
HIGHdarts/timeseries.py5280 if not self.components.equals(other.components):CODE
HIGHdarts/timeseries.py5286 elif isinstance(sc_self, pd.DataFrame) and not sc_self.equals(sc_other):CODE
HIGHdarts/timeseries.py5886 ts.static_covariates.columns.equals(series[0].static_covariates.columns)CODE
HIGHdarts/metrics/utils.py470 if not pred_series.components.equals(actual_series.components):CODE
HIGHdarts/metrics/utils.py478 if not predicted_components.equals(actual_series.components):CODE
HIGHdarts/metrics/utils.py860 is undefined, so the result is ``np.nan``.STRING
HIGHdarts/tests/test_timeseries.py110 assert ts_pd_series.equals(pd_series)CODE
HIGHdarts/tests/test_timeseries.py117 assert ts_pd_df.equals(pd_df)CODE
HIGHdarts/tests/test_timeseries.py120 assert ts_pd_df.equals(pd_df.reset_index())CODE
HIGHdarts/tests/test_timeseries.py165 assert ts_pl_df.equals(pl_df)CODE
HIGHdarts/tests/test_timeseries.py175 assert ts_pl_df_2.equals(pl_df)CODE
HIGHdarts/tests/test_timeseries.py229 assert series.time_index.equals(pd.RangeIndex(stop=1))CODE
HIGHdarts/tests/test_timeseries.py232 assert series.time_index.equals(pd.RangeIndex(start=10, stop=11))CODE
HIGHdarts/tests/test_timeseries.py236 assert series.time_index.equals(pd.RangeIndex(start=10, stop=20))CODE
HIGHdarts/tests/test_timeseries.py240 assert series.time_index.equals(pd.RangeIndex(start=10, stop=50))CODE
HIGHdarts/tests/test_timeseries.py244 assert series.time_index.equals(pd.RangeIndex(start=10, stop=40))CODE
HIGHdarts/tests/test_timeseries.py248 assert series.time_index.equals(pd.RangeIndex(start=10, stop=40, step=4))CODE
HIGHdarts/tests/test_timeseries.py252 assert series.time_index.equals(pd.RangeIndex(start=0, stop=0, step=1))CODE
HIGHdarts/tests/test_timeseries.py2497 assert test_series.time_index.equals(appended.time_index)CODE
HIGHdarts/tests/test_timeseries.py2498 assert appended.components.equals(seriesA.components)CODE
HIGHdarts/tests/test_timeseries.py2517 assert test_series.time_index.equals(appended.time_index)CODE
HIGHdarts/tests/test_timeseries.py2523 assert test_series.time_index.equals(appended_sq.time_index)CODE
HIGHdarts/tests/test_timeseries.py2524 assert appended_sq.components.equals(seriesA.components)CODE
HIGHdarts/tests/test_timeseries.py2533 assert test_series.time_index.equals(prepended.time_index)CODE
HIGHdarts/tests/test_timeseries.py2534 assert prepended.components.equals(seriesB.components)CODE
HIGHdarts/tests/test_timeseries.py2553 assert test_series.time_index.equals(prepended.time_index)CODE
HIGHdarts/tests/test_timeseries.py2554 assert prepended.components.equals(test_series.components)CODE
HIGHdarts/tests/test_timeseries.py2560 assert test_series.time_index.equals(prepended_sq.time_index)CODE
HIGHdarts/tests/test_timeseries.py2561 assert prepended_sq.components.equals(test_series.components)CODE
HIGHdarts/tests/test_timeseries.py206 assert ts.time_index.equals(CODE
HIGHdarts/tests/test_timeseries.py270 assert series.time_index.equals(CODE
HIGHdarts/tests/test_timeseries.py362 assert ts_from_int_idx.time_index.equals(ts_from_range_idx.time_index)CODE
HIGHdarts/tests/test_timeseries.py696 assert appended.time_index.equals(expected_idx)CODE
HIGHdarts/tests/test_timeseries.py697 assert appended.components.equals(series_1.components)CODE
HIGHdarts/tests/test_timeseries.py801 assert appended.time_index.equals(expected_idx)CODE
HIGHdarts/tests/test_timeseries.py802 assert appended.components.equals(series.components)CODE
HIGHdarts/tests/test_timeseries.py817 assert prepended.time_index.equals(expected_idx)CODE
HIGHdarts/tests/test_timeseries.py818 assert prepended.components.equals(series_1.components)CODE
HIGHdarts/tests/test_timeseries.py1395 assert series.time_index.equals(series_target.time_index)CODE
HIGHdarts/tests/test_timeseries.py2113 assert ts.time_index.equals(idx)CODE
HIGHdarts/tests/test_timeseries.py2123 assert ts.time_index.equals(idx)CODE
HIGHdarts/tests/test_timeseries.py2355 assert s_int.components.equals(series.components)CODE
HIGHdarts/tests/test_timeseries.py2376 assert s_int.time_index.equals(s_int_idx)CODE
HIGHdarts/tests/test_timeseries.py2436 assert s1_int.time_index.equals(s2_int.time_index) and s1_int.time_index.equals(CODE
HIGHdarts/tests/test_timeseries.py2461 assert seriesB.time_index.equals(CODE
HIGHdarts/tests/test_timeseries.py2468 assert seriesC.time_index.equals(CODE
HIGHdarts/tests/test_timeseries_static_covariates.py826 assert ts_multi.static_covariates.index.equals(CODE
HIGHdarts/tests/test_timeseries_static_covariates.py829 assert ts_multi.static_covariates.columns.equals(static_covs.columns)CODE
HIGHdarts/tests/test_timeseries_static_covariates.py836 assert ts_multi.static_covariates.index.equals(ts_multi.components)CODE
HIGHdarts/tests/test_timeseries_static_covariates.py837 assert ts_multi.static_covariates.columns.equals(static_covs.columns)CODE
HIGHdarts/tests/test_timeseries_static_covariates.py1050 assert ts_scaled.static_covariates.equals(ts.static_covariates)CODE
HIGHdarts/tests/test_timeseries_static_covariates.py1053 assert ts_inv.static_covariates.equals(ts.static_covariates)CODE
HIGHdarts/tests/test_timeseries_static_covariates.py1081 assert ts.static_covariates.index.equals(ts.components)CODE
HIGHdarts/tests/test_timeseries_static_covariates.py1084 assert ts0.static_covariates.index.equals(ts.components)CODE
HIGHdarts/tests/test_timeseries_static_covariates.py1087 assert ts1.static_covariates.index.equals(pd.Index(["comp1"]))CODE
HIGHdarts/tests/test_timeseries_static_covariates.py1090 assert ts2.static_covariates.index.equals(pd.Index(["comp2"]))CODE
HIGHdarts/tests/test_timeseries_static_covariates.py1093 assert ts3.static_covariates.index.equals(pd.Index(["comp1", "comp2"]))CODE
HIGHdarts/tests/test_timeseries_static_covariates.py1096 assert ts4.static_covariates.index.equals(pd.Index(["comp1", "comp2"]))CODE
HIGHdarts/tests/test_timeseries_static_covariates.py1107 assert ts.static_covariates.index.equals(CODE
213 more matches not shown…
Hyper-Verbose Identifiers1277 hits · 1191 pts
SeverityFileLineSnippetContext
LOWdocs/fix_package_titles.py18def extract_docstring_from_file(file_path):CODE
LOWdocs/fix_package_titles.py114def process_package_docstrings(app, docname, source):CODE
LOWdarts/logging.py31def raise_deprecation_warning(CODE
LOWdarts/logging.py143def execute_and_suppress_output(function, logger, suppression_threshold_level, *args):CODE
LOWdarts/logging.py164def suppress_lightning_warnings(suppress_all: bool = False):CODE
LOWdarts/config.py162 def _on_plotting_style_change(self, value: bool) -> None:CODE
LOWdarts/timeseries.py5039 def _observed_freq_datetime_index(index: pd.DatetimeIndex) -> set:CODE
LOWdarts/timeseries.py5062 def _observed_freq_integer_index(index: pd.Index) -> set:CODE
LOWdarts/timeseries.py5213 def _get_first_timestamp_after(self, ts: pd.Timestamp) -> pd.Timestamp | int:CODE
LOWdarts/timeseries.py5216 def _get_last_timestamp_before(self, ts: pd.Timestamp) -> pd.Timestamp | int:CODE
LOWdarts/metrics/__init__.py229def _build_time_dependent_metrics():CODE
LOWdarts/metrics/__init__.py234def _build_classification_metrics():CODE
LOWdarts/metrics/utils.py128 def wrapper_classification_support(*args, **kwargs):CODE
LOWdarts/metrics/utils.py330 def wrapper_multivariate_support(*args, **kwargs) -> METRIC_OUTPUT_TYPE:CODE
LOWdarts/metrics/utils.py705def _get_highest_probability_label(CODE
LOWdarts/ad/utils.py88def eval_metric_from_binary_prediction(CODE
LOWdarts/ad/utils.py294def show_anomalies_from_scores(CODE
LOWdarts/ad/utils.py742def _plot_series_and_anomalies(CODE
LOWdarts/ad/scorers/scorers.py124 def eval_metric_from_prediction(CODE
LOWdarts/ad/scorers/scorers.py169 def show_anomalies_from_prediction(CODE
LOWdarts/ad/scorers/scorers.py258 def _score_core_from_prediction(CODE
LOWdarts/ad/scorers/scorers.py314 def _extract_deterministic_series(self, series: TimeSeries, name_series: str):CODE
LOWdarts/ad/scorers/scorers.py326 def _extract_deterministic_values(self, series: np.ndarray, name_series: str):CODE
LOWdarts/ad/scorers/scorers.py655 def _score_core_from_prediction(CODE
LOWdarts/ad/scorers/scorers.py884 def _convert_tabular_to_series(CODE
LOWdarts/ad/scorers/scorers.py938 def _score_core_from_prediction(CODE
LOWdarts/ad/scorers/norm_scorer.py55 def _score_core_from_prediction(CODE
LOWdarts/ad/scorers/difference_scorer.py23 def _score_core_from_prediction(CODE
LOW…ocessing/transformers/static_covariates_transformer.py229 def _process_static_cov_columns(CODE
LOW…ocessing/transformers/static_covariates_transformer.py265 def _create_category_mappings(CODE
LOW…ocessing/transformers/static_covariates_transformer.py331 def _create_inv_component_masks(CODE
LOWdarts/dataprocessing/transformers/midas.py437 def _process_static_covariates(CODE
LOWdarts/dataprocessing/encoders/encoder_base.py151 def generate_train_inference_idx(CODE
LOWdarts/dataprocessing/encoders/encoders.py1561 def _process_input_transformer(CODE
LOWdarts/datasets/dataset_loaders.py90 def _check_dataset_integrity_or_raise(self):CODE
LOWdarts/tests/test_timeseries.py122 def test_df_time_col_not_present(self):CODE
LOWdarts/tests/test_timeseries.py128 def test_df_invalid_time_col_dtype(self):CODE
LOWdarts/tests/test_timeseries.py185 def test_creation_from_dataframe_with_dates(self, backend, date_type):CODE
LOWdarts/tests/test_timeseries.py220 def test_integer_range_indexing(self):CODE
LOWdarts/tests/test_timeseries.py2511def helper_test_append_values(test_series: TimeSeries):CODE
LOWdarts/tests/test_timeseries.py2547def helper_test_prepend_values(test_series: TimeSeries):CODE
LOWdarts/tests/test_timeseries.py2800 def test_creation_with_hierarchy_sunny_day(self):CODE
LOWdarts/tests/test_timeseries.py2808 def test_with_hierarchy_sunny_day(self):CODE
LOWdarts/tests/test_timeseries.py2812 def test_with_hierarchy_rainy_day(self):CODE
LOWdarts/tests/test_timeseries.py2991 def test_head_sunny_day_sample_axis(self):CODE
LOWdarts/tests/test_timeseries.py2996 def test_head_overshot_time_axis(self):CODE
LOWdarts/tests/test_timeseries.py3001 def test_head_overshot_component_axis(self):CODE
LOWdarts/tests/test_timeseries.py3005 def test_head_overshot_sample_axis(self):CODE
LOWdarts/tests/test_timeseries.py3009 def test_head_numeric_time_index(self):CODE
LOWdarts/tests/test_timeseries.py3014 def test_tail_overshot_time_axis(self):CODE
LOWdarts/tests/test_timeseries.py3019 def test_tail_overshot_component_axis(self):CODE
LOWdarts/tests/test_timeseries.py3023 def test_tail_overshot_sample_axis(self):CODE
LOWdarts/tests/test_timeseries.py3027 def test_tail_numeric_time_index(self):CODE
LOWdarts/tests/test_timeseries.py78 def test_from_times_and_values(self):CODE
LOWdarts/tests/test_timeseries.py419 def test_univariate_component(self):CODE
LOWdarts/tests/test_timeseries.py625 def test_intersect_more_freqs(self, config):CODE
LOWdarts/tests/test_timeseries.py758 def test_append_and_prepend_values(self, config):CODE
LOWdarts/tests/test_timeseries.py1009 def test_getitem_datetime_index(self):CODE
LOWdarts/tests/test_timeseries.py1078 def test_getitem_integer_index(self):CODE
LOWdarts/tests/test_timeseries.py1132 def test_getitem_list_of_integers(self, is_dti):CODE
1217 more matches not shown…
Cross-File Repetition55 hits · 275 pts
SeverityFileLineSnippetContext
HIGHdarts/ad/scorers/nll_gamma_scorer.py0nll laplace scorer parameters ---------- window integer value indicating the size of the window w used by the scorer to STRING
HIGHdarts/ad/scorers/scorers.py0nll laplace scorer parameters ---------- window integer value indicating the size of the window w used by the scorer to STRING
HIGHdarts/ad/scorers/nll_poisson_scorer.py0nll laplace scorer parameters ---------- window integer value indicating the size of the window w used by the scorer to STRING
HIGHdarts/ad/scorers/nll_gaussian_scorer.py0nll laplace scorer parameters ---------- window integer value indicating the size of the window w used by the scorer to STRING
HIGHdarts/ad/scorers/nll_exponential_scorer.py0nll laplace scorer parameters ---------- window integer value indicating the size of the window w used by the scorer to STRING
HIGHdarts/ad/scorers/nll_laplace_scorer.py0nll laplace scorer parameters ---------- window integer value indicating the size of the window w used by the scorer to STRING
HIGH…aprocessing/transformers/test_base_data_transformer.py0applies the (invertible) transform `transformed_series = scale * series + translation`. when 'fitting' this transform, tSTRING
HIGH…cessing/transformers/test_fittable_data_transformer.py0applies the (invertible) transform `transformed_series = scale * series + translation`. when 'fitting' this transform, tSTRING
HIGH…nsformers/test_invertible_fittable_data_transformer.py0applies the (invertible) transform `transformed_series = scale * series + translation`. when 'fitting' this transform, tSTRING
HIGH…ssing/transformers/test_invertible_data_transformer.py0applies the (invertible) transform `transformed_series = scale * series + translation`. when 'fitting' this transform, tSTRING
HIGH…aprocessing/transformers/test_base_data_transformer.py0implements the transform `scale * series + translation`. if `component_mask` is in `kwargs`, this is manually applied anSTRING
HIGH…cessing/transformers/test_fittable_data_transformer.py0implements the transform `scale * series + translation`. if `component_mask` is in `kwargs`, this is manually applied anSTRING
HIGH…nsformers/test_invertible_fittable_data_transformer.py0implements the transform `scale * series + translation`. if `component_mask` is in `kwargs`, this is manually applied anSTRING
HIGH…ssing/transformers/test_invertible_data_transformer.py0implements the transform `scale * series + translation`. if `component_mask` is in `kwargs`, this is manually applied anSTRING
HIGH…aprocessing/transformers/test_base_data_transformer.py0tests for correct transformation of multiple series when different param values are used for different parallel jobs (i.STRING
HIGH…nsformers/test_invertible_fittable_data_transformer.py0tests for correct transformation of multiple series when different param values are used for different parallel jobs (i.STRING
HIGH…ssing/transformers/test_invertible_data_transformer.py0tests for correct transformation of multiple series when different param values are used for different parallel jobs (i.STRING
HIGH…aprocessing/transformers/test_base_data_transformer.py0tests that `stack_samples` and `unstack_samples` correctly implemented when considering multi-sample timeseries.STRING
HIGH…cessing/transformers/test_fittable_data_transformer.py0tests that `stack_samples` and `unstack_samples` correctly implemented when considering multi-sample timeseries.STRING
HIGH…nsformers/test_invertible_fittable_data_transformer.py0tests that `stack_samples` and `unstack_samples` correctly implemented when considering multi-sample timeseries.STRING
HIGH…ssing/transformers/test_invertible_data_transformer.py0tests that `stack_samples` and `unstack_samples` correctly implemented when considering multi-sample timeseries.STRING
HIGH…aprocessing/transformers/test_base_data_transformer.py0tests that automatic component masking is correctly implemented, and that manual component masking is also handled correSTRING
HIGH…cessing/transformers/test_fittable_data_transformer.py0tests that automatic component masking is correctly implemented, and that manual component masking is also handled correSTRING
HIGH…nsformers/test_invertible_fittable_data_transformer.py0tests that automatic component masking is correctly implemented, and that manual component masking is also handled correSTRING
HIGH…ssing/transformers/test_invertible_data_transformer.py0tests that automatic component masking is correctly implemented, and that manual component masking is also handled correSTRING
HIGH…tils/historical_forecasts/test_historical_forecasts.py0check that passing sample weights work and that it yields different results than without sample weights.STRING
HIGHdarts/tests/models/forecasting/test_residuals.py0check that passing sample weights work and that it yields different results than without sample weights.STRING
HIGHdarts/tests/models/forecasting/test_backtesting.py0check that passing sample weights work and that it yields different results than without sample weights.STRING
HIGH…s/tabularization/test_create_lagged_prediction_data.py0tests the `create_lagged_training_data` function defined in `darts.utils.data.tabularization`. there are broadly two 'grSTRING
HIGH…s/tests/utils/tabularization/test_get_feature_times.py0tests the `create_lagged_training_data` function defined in `darts.utils.data.tabularization`. there are broadly two 'grSTRING
HIGH…ils/tabularization/test_create_lagged_training_data.py0tests the `create_lagged_training_data` function defined in `darts.utils.data.tabularization`. there are broadly two 'grSTRING
HIGH…s/tabularization/test_create_lagged_prediction_data.py0helper function called by `get_feature_times` that extracts all times within `future_covariates` that can be used to creSTRING
HIGH…s/tests/utils/tabularization/test_get_feature_times.py0helper function called by `get_feature_times` that extracts all times within `future_covariates` that can be used to creSTRING
HIGH…ils/tabularization/test_create_lagged_training_data.py0helper function called by `get_feature_times` that extracts all times within `future_covariates` that can be used to creSTRING
HIGHdarts/tests/models/forecasting/test_timesfm2p5.py0load validation inputs for patchtstfmmodel fidelity tests. the data imports here are adapted from the `20-sklearnmodel-eSTRING
HIGHdarts/tests/models/forecasting/test_chronos2.py0load validation inputs for patchtstfmmodel fidelity tests. the data imports here are adapted from the `20-sklearnmodel-eSTRING
HIGHdarts/tests/models/forecasting/test_patchtst_fm.py0load validation inputs for patchtstfmmodel fidelity tests. the data imports here are adapted from the `20-sklearnmodel-eSTRING
HIGHdarts/utils/likelihood_models/sklearn.py0samples a prediction from the likelihood distribution and the predicted parameters.STRING
HIGHdarts/utils/likelihood_models/torch.py0samples a prediction from the likelihood distribution and the predicted parameters.STRING
HIGHdarts/utils/likelihood_models/statsforecast.py0samples a prediction from the likelihood distribution and the predicted parameters.STRING
HIGHdarts/models/forecasting/catboost_model.py0sklearn classifier model can be used to fit any scikit-learn-like classifier class to predict the target time series witSTRING
HIGHdarts/models/forecasting/xgboost.py0sklearn classifier model can be used to fit any scikit-learn-like classifier class to predict the target time series witSTRING
HIGHdarts/models/forecasting/linear_regression_model.py0sklearn classifier model can be used to fit any scikit-learn-like classifier class to predict the target time series witSTRING
HIGHdarts/models/forecasting/lgbm.py0sklearn classifier model can be used to fit any scikit-learn-like classifier class to predict the target time series witSTRING
HIGHdarts/models/forecasting/sklearn_model.py0sklearn classifier model can be used to fit any scikit-learn-like classifier class to predict the target time series witSTRING
HIGHdarts/models/forecasting/catboost_model.py0fit/train the model on one or multiple series. parameters ---------- series timeseries or sequence[timeseries] object coSTRING
HIGHdarts/models/forecasting/xgboost.py0fit/train the model on one or multiple series. parameters ---------- series timeseries or sequence[timeseries] object coSTRING
HIGHdarts/models/forecasting/lgbm.py0fit/train the model on one or multiple series. parameters ---------- series timeseries or sequence[timeseries] object coSTRING
HIGHdarts/models/forecasting/sklearn_model.py0fit/train the model on one or multiple series. parameters ---------- series timeseries or sequence[timeseries] object coSTRING
HIGHdarts/models/forecasting/catboost_model.py0returns the name of the categorical features parameter from model's `fit` method .STRING
HIGHdarts/models/forecasting/lgbm.py0returns the name of the categorical features parameter from model's `fit` method .STRING
HIGHdarts/models/forecasting/sklearn_model.py0returns the name of the categorical features parameter from model's `fit` method .STRING
HIGHdarts/models/forecasting/sf_auto_ces.py0auto-theta based on the `statsforecasts package <https://github.com/nixtla/statsforecast>`__. automatically selects the STRING
HIGHdarts/models/forecasting/sf_auto_ets.py0auto-theta based on the `statsforecasts package <https://github.com/nixtla/statsforecast>`__. automatically selects the STRING
HIGHdarts/models/forecasting/sf_auto_theta.py0auto-theta based on the `statsforecasts package <https://github.com/nixtla/statsforecast>`__. automatically selects the STRING
Unused Imports275 hits · 238 pts
SeverityFileLineSnippetContext
LOWdarts/__init__.py8CODE
LOWdarts/__init__.py8CODE
LOWdarts/__init__.py8CODE
LOWdarts/__init__.py8CODE
LOWdarts/__init__.py8CODE
LOWdarts/__init__.py15CODE
LOWdarts/__init__.py15CODE
LOWdarts/__init__.py15CODE
LOWdarts/__init__.py15CODE
LOWdarts/typing.py16CODE
LOWdarts/timeseries.py42CODE
LOWdarts/metrics/__init__.py109CODE
LOWdarts/metrics/__init__.py110CODE
LOWdarts/metrics/__init__.py111CODE
LOWdarts/metrics/__init__.py112CODE
LOWdarts/metrics/__init__.py113CODE
LOWdarts/metrics/__init__.py114CODE
LOWdarts/metrics/__init__.py115CODE
LOWdarts/metrics/__init__.py118CODE
LOWdarts/metrics/__init__.py119CODE
LOWdarts/metrics/__init__.py120CODE
LOWdarts/metrics/__init__.py121CODE
LOWdarts/metrics/__init__.py122CODE
LOWdarts/metrics/__init__.py123CODE
LOWdarts/metrics/__init__.py124CODE
LOWdarts/metrics/__init__.py125CODE
LOWdarts/metrics/__init__.py126CODE
LOWdarts/metrics/__init__.py127CODE
LOWdarts/metrics/__init__.py128CODE
LOWdarts/metrics/__init__.py129CODE
LOWdarts/metrics/__init__.py130CODE
LOWdarts/metrics/__init__.py131CODE
LOWdarts/metrics/__init__.py132CODE
LOWdarts/metrics/__init__.py133CODE
LOWdarts/metrics/__init__.py134CODE
LOWdarts/metrics/__init__.py135CODE
LOWdarts/metrics/__init__.py136CODE
LOWdarts/metrics/__init__.py137CODE
LOWdarts/metrics/__init__.py138CODE
LOWdarts/metrics/__init__.py139CODE
LOWdarts/metrics/__init__.py140CODE
LOWdarts/metrics/__init__.py141CODE
LOWdarts/metrics/__init__.py142CODE
LOWdarts/metrics/__init__.py143CODE
LOWdarts/metrics/__init__.py144CODE
LOWdarts/metrics/__init__.py145CODE
LOWdarts/metrics/__init__.py146CODE
LOWdarts/metrics/__init__.py147CODE
LOWdarts/metrics/__init__.py148CODE
LOWdarts/metrics/__init__.py149CODE
LOWdarts/metrics/__init__.py150CODE
LOWdarts/metrics/__init__.py151CODE
LOWdarts/metrics/__init__.py152CODE
LOWdarts/metrics/__init__.py153CODE
LOWdarts/metrics/__init__.py154CODE
LOWdarts/ad/__init__.py34CODE
LOWdarts/ad/__init__.py35CODE
LOWdarts/ad/__init__.py38CODE
LOWdarts/ad/__init__.py39CODE
LOWdarts/ad/__init__.py40CODE
215 more matches not shown…
AI Structural Patterns123 hits · 112 pts
SeverityFileLineSnippetContext
LOWdarts/timeseries.py110CODE
LOWdarts/timeseries.py581CODE
LOWdarts/timeseries.py686CODE
LOWdarts/timeseries.py849CODE
LOWdarts/timeseries.py1220CODE
LOWdarts/timeseries.py4375CODE
LOWdarts/timeseries.py4466CODE
LOWdarts/metrics/metrics.py41CODE
LOWdarts/metrics/metrics.py226CODE
LOWdarts/metrics/metrics.py411CODE
LOWdarts/metrics/metrics.py542CODE
LOWdarts/metrics/metrics.py668CODE
LOWdarts/metrics/metrics.py853CODE
LOWdarts/metrics/metrics.py984CODE
LOWdarts/metrics/metrics.py1197CODE
LOWdarts/metrics/metrics.py1319CODE
LOWdarts/metrics/metrics.py1511CODE
LOWdarts/metrics/metrics.py1821CODE
LOWdarts/metrics/metrics.py2127CODE
LOWdarts/metrics/metrics.py2521CODE
LOWdarts/metrics/metrics.py2581CODE
LOWdarts/metrics/metrics.py2904CODE
LOWdarts/metrics/metrics.py3324CODE
LOWdarts/metrics/metrics.py3429CODE
LOWdarts/metrics/metrics.py3526CODE
LOWdarts/metrics/metrics.py3658CODE
LOWdarts/metrics/metrics.py3757CODE
LOWdarts/metrics/metrics.py3867CODE
LOWdarts/metrics/metrics.py3962CODE
LOWdarts/metrics/metrics.py4074CODE
LOWdarts/metrics/metrics.py4264CODE
LOWdarts/metrics/metrics.py4382CODE
LOWdarts/metrics/metrics.py4500CODE
LOWdarts/ad/utils.py294CODE
LOWdarts/ad/anomaly_model/forecasting_am.py66CODE
LOWdarts/ad/anomaly_model/forecasting_am.py153CODE
LOWdarts/ad/anomaly_model/forecasting_am.py240CODE
LOWdarts/ad/anomaly_model/forecasting_am.py325CODE
LOWdarts/ad/anomaly_model/forecasting_am.py424CODE
LOWdarts/ad/anomaly_model/forecasting_am.py534CODE
LOWdarts/dataprocessing/dtw/_plot.py4CODE
LOW…taprocessing/transformers/fittable_data_transformer.py25CODE
LOWdarts/dataprocessing/transformers/window_transformer.py14CODE
LOWdarts/tests/metrics/test_metrics.py2205CODE
LOWdarts/tests/models/forecasting/test_sklearn_models.py74CODE
LOWdarts/utils/timeseries_generation.py93CODE
LOWdarts/utils/timeseries_generation.py154CODE
LOWdarts/utils/timeseries_generation.py223CODE
LOWdarts/utils/timeseries_generation.py305CODE
LOWdarts/utils/_plotting.py171CODE
LOWdarts/utils/_plotting.py346CODE
LOWdarts/utils/statistics.py1108CODE
LOW…ical_forecasts/optimized_historical_forecasts_torch.py21CODE
LOW…ical_forecasts/optimized_historical_forecasts_torch.py141CODE
LOW…forecasts/optimized_historical_forecasts_regression.py23CODE
LOWdarts/utils/data/torch_datasets/training_dataset.py60CODE
LOWdarts/utils/data/torch_datasets/training_dataset.py346CODE
LOWdarts/utils/data/torch_datasets/training_dataset.py449CODE
LOWdarts/utils/data/torch_datasets/inference_dataset.py62CODE
LOWdarts/utils/data/tabularization/tabularization.py32CODE
63 more matches not shown…
Redundant / Tautological Comments45 hits · 82 pts
SeverityFileLineSnippetContext
LOWdocs/fix_package_titles.py104 # Check if it's a package (has __init__.py)COMMENT
LOWdocs/fix_package_titles.py107 # Check if it's a module (has .py file)COMMENT
LOWdocs/fix_package_titles.py130 # Check if this is a package RST file (contains ".. currentmodule::")COMMENT
LOWdarts/tests/test_timeseries_plotly.py222 # Check if the alpha is present in the fillcolor stringCOMMENT
LOWdarts/tests/test_timeseries_plotly.py459 # Check if the trace color is green (Plotly stores this in marker or line)COMMENT
LOWdarts/tests/ad/test_detectors.py64 # Check if return type is TimeSeries when input is a single seriesCOMMENT
LOWdarts/tests/ad/test_detectors.py66 # Check if return type is Sequence when input is a Sequence of seriesCOMMENT
LOWdarts/tests/ad/test_detectors.py82 # Check if return type is float when input is a seriesCOMMENT
LOWdarts/tests/ad/test_detectors.py87 # Check if return type is Sequence when input is a Sequence of seriesCOMMENT
LOWdarts/tests/ad/test_detectors.py96 # Check if return type is Sequence when input is a multivariate seriesCOMMENT
LOWdarts/tests/ad/test_detectors.py103 # Check if return type is Sequence when input is a multivariate seriesCOMMENT
LOWdarts/tests/ad/test_detectors.py159 # Check if _fit_called is FalseCOMMENT
LOWdarts/tests/ad/test_detectors.py174 # Check if _fit_called is True after being fittedCOMMENT
LOWdarts/tests/ad/test_detectors.py185 # Check if _fit_called is True after being fittedCOMMENT
LOWdarts/tests/ad/test_scorers.py173 # Check if return type is float when input is a seriesCOMMENT
LOWdarts/tests/ad/test_scorers.py178 # Check if return type is Sequence when input is a Sequence of seriesCOMMENT
LOWdarts/tests/ad/test_scorers.py184 # Check if return type is Sequence when input is a multivariate seriesCOMMENT
LOWdarts/tests/ad/test_scorers.py190 # Check if return type is Sequence when input is a multivariate seriesCOMMENT
LOWdarts/tests/ad/test_scorers.py202 # Check if return type is float when input is a seriesCOMMENT
LOWdarts/tests/ad/test_scorers.py205 # Check if return type is Sequence when input is a sequence of seriesCOMMENT
LOWdarts/tests/ad/test_scorers.py209 # Check if return type is Sequence when input is a multivariate seriesCOMMENT
LOWdarts/tests/ad/test_scorers.py212 # Check if return type is Sequence when input is a sequence of multivariate seriesCOMMENT
LOWdarts/tests/ad/test_scorers.py217 # Check if return type is float when input is a seriesCOMMENT
LOWdarts/tests/ad/test_scorers.py222 # Check if return type is Sequence when input is a Sequence of seriesCOMMENT
LOWdarts/tests/ad/test_scorers.py229 # Check if return type is Sequence when input is a multivariate seriesCOMMENT
LOWdarts/tests/ad/test_scorers.py235 # Check if return type is Sequence when input is a multivariate seriesCOMMENT
LOWdarts/tests/ad/test_scorers.py243 # Check if return type is float when input is a seriesCOMMENT
LOWdarts/tests/ad/test_scorers.py250 # Check if return type is Sequence when input is a Sequence of seriesCOMMENT
LOWdarts/tests/ad/test_scorers.py257 # Check if return type is a float when input is a multivariate series and component_wise is set to `False`COMMENT
LOWdarts/tests/ad/test_scorers.py264 # Check if return type is Sequence when input is a multivariate series and component_wise is set to `False`COMMENT
LOWdarts/tests/ad/test_scorers.py273 # Check if return type is a float when input is a multivariate series and component_wise is set to `True`COMMENT
LOWdarts/tests/ad/test_scorers.py280 # Check if return type is Sequence when input is a multivariate series and component_wise is set to `True`COMMENT
LOWdarts/tests/ad/test_scorers.py589 # Check if _fit_called is True after being fittedCOMMENT
LOWdarts/tests/ad/test_scorers.py597 # Check if _fit_called is True after being fittedCOMMENT
LOWdarts/tests/ad/test_scorers.py607 # Check if _fit_called is True after being fittedCOMMENT
LOWdarts/tests/ad/test_scorers.py617 # Check if _fit_called is True after being fittedCOMMENT
LOWdarts/tests/ad/test_scorers.py451 # Check if trainable is False, being a NonFittableAnomalyScorerCOMMENT
LOWdarts/tests/ad/test_scorers.py492 # Check if _fit_called is FalseCOMMENT
LOWdarts/tests/ad/test_anomaly_model.py475 # Check if return type is float when input is a seriesCOMMENT
LOWdarts/tests/ad/test_anomaly_model.py481 # Check if return type is Sequence when input is a Sequence of seriesCOMMENT
LOWdarts/tests/ad/test_aggregators.py229 # Check if return type is the same number of series in inputCOMMENT
LOWdarts/tests/ad/test_aggregators.py464 # Check if _fit_called is False before calling fitCOMMENT
LOWdarts/tests/ad/test_aggregators.py470 # Check if _fit_called is True after calling fitCOMMENT
LOWdarts/models/forecasting/sklearn_model.py456 # Check if only default lags are providedCOMMENT
LOWdarts/models/forecasting/sklearn_model.py1049 # Check if multi-output regression is requiredCOMMENT
Deep Nesting67 hits · 58 pts
SeverityFileLineSnippetContext
LOWdarts/timeseries.py110CODE
LOWdarts/timeseries.py1780CODE
LOWdarts/timeseries.py2354CODE
LOWdarts/timeseries.py5572CODE
LOWdarts/ad/utils.py142CODE
LOWdarts/dataprocessing/dtw/cost_matrix.py115CODE
LOWdarts/dataprocessing/transformers/reconciliation.py231CODE
LOW…ocessing/transformers/static_covariates_transformer.py265CODE
LOW…ocessing/transformers/static_covariates_transformer.py450CODE
LOWdarts/dataprocessing/transformers/midas.py317CODE
LOWdarts/dataprocessing/encoders/encoders.py1450CODE
LOWdarts/datasets/dataset_loaders.py144CODE
LOWdarts/tests/test_timeseries.py1261CODE
LOWdarts/tests/test_timeseries_plot.py79CODE
LOWdarts/tests/dataprocessing/encoders/test_encoders.py325CODE
LOWdarts/tests/utils/test_timeseries_generation.py209CODE
LOWdarts/tests/utils/torch_datasets/test_torch_datasets.py45CODE
LOW…tils/historical_forecasts/test_historical_forecasts.py1688CODE
LOW…tils/historical_forecasts/test_historical_forecasts.py2895CODE
LOW…tils/historical_forecasts/test_historical_forecasts.py4525CODE
LOW…tils/historical_forecasts/test_historical_forecasts.py4636CODE
LOW…s/tabularization/test_create_lagged_prediction_data.py231CODE
LOW…ils/tabularization/test_create_lagged_training_data.py258CODE
LOW…ils/tabularization/test_create_lagged_training_data.py414CODE
LOWdarts/tests/models/forecasting/test_TCN.py74CODE
LOWdarts/tests/models/forecasting/test_dlinear_nlinear.py132CODE
LOW…/tests/models/forecasting/test_probabilistic_models.py620CODE
LOWdarts/tests/models/forecasting/test_sklearn_models.py380CODE
LOWdarts/tests/models/forecasting/test_sklearn_models.py695CODE
LOWdarts/tests/models/forecasting/test_sklearn_models.py1668CODE
LOWdarts/tests/models/forecasting/test_sklearn_models.py395CODE
LOWdarts/tests/models/forecasting/test_conformal_model.py1184CODE
LOWdarts/utils/_plotting.py27CODE
LOWdarts/utils/_plotting.py171CODE
LOWdarts/utils/utils.py756CODE
LOWdarts/utils/statistics.py140CODE
LOWdarts/utils/ts_utils.py56CODE
LOWdarts/utils/ts_utils.py185CODE
LOWdarts/utils/historical_forecasts/utils.py40CODE
LOWdarts/utils/historical_forecasts/utils.py1024CODE
LOWdarts/utils/historical_forecasts/utils.py1334CODE
LOW…forecasts/optimized_historical_forecasts_regression.py23CODE
LOWdarts/utils/data/torch_datasets/dataset.py71CODE
LOWdarts/utils/data/tabularization/tabularization.py1528CODE
LOWdarts/utils/data/tabularization/tabularization.py1780CODE
LOWdarts/utils/likelihood_models/sklearn.py670CODE
LOWdarts/models/components/tft_submodels.py369CODE
LOWdarts/models/forecasting/ensemble_model.py78CODE
LOWdarts/models/forecasting/ensemble_model.py241CODE
LOWdarts/models/forecasting/ensemble_model.py755CODE
LOWdarts/models/forecasting/prophet_model.py630CODE
LOWdarts/models/forecasting/tft_model.py989CODE
LOWdarts/models/forecasting/conformal_models.py1085CODE
LOWdarts/models/forecasting/forecasting_model.py668CODE
LOWdarts/models/forecasting/forecasting_model.py2001CODE
LOWdarts/models/forecasting/fft.py82CODE
LOWdarts/models/forecasting/sf_croston.py16CODE
LOWdarts/models/forecasting/torch_forecasting_model.py452CODE
LOWdarts/models/forecasting/torch_forecasting_model.py3001CODE
LOWdarts/models/forecasting/sklearn_model.py317CODE
7 more matches not shown…
Self-Referential Comments15 hits · 45 pts
SeverityFileLineSnippetContext
MEDIUMdarts/tests/test_timeseries.py2500 # Creating a gap is not allowedCOMMENT
MEDIUMdarts/tests/test_timeseries.py2536 # Creating a gap is not allowedCOMMENT
MEDIUMdarts/tests/test_timeseries_plotly.py302 # Create a univariate deterministic seriesCOMMENT
MEDIUMdarts/tests/test_timeseries_plotly.py349 # Define a side effect for the mock importCOMMENT
MEDIUM…tils/historical_forecasts/test_historical_forecasts.py4530 # Create a custom model that tracks fit and predict argumentsCOMMENT
MEDIUM…tils/historical_forecasts/test_historical_forecasts.py4646 # Create a custom Pipeline subclass that tracks fit, transform, and inverse_transform argumentsCOMMENT
MEDIUMdarts/tests/models/forecasting/test_prophet.py370 # Create a simple timeseriesCOMMENT
MEDIUM…ts/models/forecasting/test_local_forecasting_models.py649 # Create a custom model that tracks fit and predict argumentsCOMMENT
MEDIUMdarts/tests/optional_deps/test_ray.py52 # Create the model using model_args from Ray TuneCOMMENT
MEDIUMdarts/tests/optional_deps/test_ray.py92 # Define the trainable function that will be tuned by Ray TuneCOMMENT
MEDIUMdarts/tests/optional_deps/test_ray.py110 # Create the Tuner object and run the hyperparameter searchCOMMENT
MEDIUMdarts/models/forecasting/block_rnn_model.py161 # Defining the RNN moduleCOMMENT
MEDIUMdarts/models/forecasting/transformer_model.py273 # Defining the Transformer moduleCOMMENT
MEDIUMdarts/models/forecasting/pl_forecasting_module.py491 # Create the optimizer and (optionally) the learning rate schedulerCOMMENT
MEDIUMdarts/models/forecasting/rnn_model.py260 # Defining the RNN moduleCOMMENT
AI Slop Vocabulary13 hits · 24 pts
SeverityFileLineSnippetContext
MEDIUMdarts/timeseries.py4236 # More robust than predicting from window params, as some functionsCOMMENT
MEDIUMdarts/metrics/utils.py65# Note: for new metrics added to this module to be able to leverage the two decorators, it is required both havingCOMMENT
MEDIUMdarts/dataprocessing/transformers/midas.py124 """MIDAS needs the high frequency period name in order to easily reverse_transformSTRING
LOWdarts/dataprocessing/encoders/encoder_base.py275 # user supplied covariates: simply return the covariate time index; guarantees that an exception isCOMMENT
LOWdarts/dataprocessing/encoders/encoder_base.py316 # user supplied covariates: simply return the covariate time index; guarantees that an exception isCOMMENT
LOWdarts/dataprocessing/encoders/encoder_base.py374 # user supplied covariates: simply return the covariate time index; guarantees that models raise anCOMMENT
LOWdarts/dataprocessing/encoders/encoder_base.py378 # simply return the target time index.COMMENT
LOWdarts/dataprocessing/encoders/encoder_base.py424 # user supplied covariates: simply return the covariate time index; guarantees that an exception isCOMMENT
LOWdarts/dataprocessing/encoders/encoder_base.py428 # simply return the target time index.COMMENT
LOWdarts/tests/ad/test_scorers.py834 # test plotting (just call the functions)COMMENT
MEDIUMdarts/models/forecasting/sf_model.py24 """This serves as a protocol for expected StatsForecast model API."""STRING
MEDIUMdarts/models/forecasting/torch_forecasting_model.py3044 # warning messages formatted to facilitate copy-pastingCOMMENT
MEDIUMdarts/models/forecasting/linear_regression_model.py242 # assign the Quantile regressor to self.model to leverage existing logicCOMMENT
Decorative Section Separators7 hits · 21 pts
SeverityFileLineSnippetContext
MEDIUMdocs/fix_package_titles.py46 # ==================COMMENT
MEDIUMdocs/fix_package_titles.py153 # ============COMMENT
MEDIUMdocs/source/conf.py196# ---------------------------------------------------------------------------------COMMENT
MEDIUMdarts/tests/models/forecasting/foundation_test_utils.py16# ── Artefact paths ──────────────────────────────────────────────────────────COMMENT
MEDIUMdarts/tests/models/forecasting/foundation_test_utils.py30# ── HuggingFace mock download (Chronos-2 tiny artefact) ────────────────────COMMENT
MEDIUMdarts/tests/models/forecasting/foundation_test_utils.py53# ── TiRex stub ──────────────────────────────────────────────────────────────COMMENT
MEDIUMdarts/tests/models/forecasting/foundation_test_utils.py77# ── TimesFM 2.5 tiny model ─────────────────────────────────────────────────COMMENT
Modern Structural Boilerplate16 hits · 16 pts
SeverityFileLineSnippetContext
LOWdarts/config.py298 def set_option(self, pattern: str, value: Any) -> None:CODE
LOWdarts/config.py385def set_option(pat: str, value: Any) -> None:CODE
LOWdarts/__init__.py24__all__ = [CODE
LOWdarts/ad/anomaly_model/__init__.py28__all__ = [CODE
LOWdarts/ad/aggregators/__init__.py19__all__ = [CODE
LOWdarts/ad/scorers/__init__.py83__all__ = [CODE
LOWdarts/ad/detectors/__init__.py25__all__ = [CODE
LOWdarts/dataprocessing/__init__.py11__all__ = ["Pipeline"]CODE
LOWdarts/dataprocessing/dtw/__init__.py19__all__ = [CODE
LOWdarts/dataprocessing/encoders/encoder_base.py892 def _update_mask(self, covariates: list[TimeSeries]) -> None:CODE
LOWdarts/dataprocessing/encoders/__init__.py21__all__ = [CODE
LOWdarts/dataprocessing/encoders/encoders.py1388 def _setup_encoders(self, params: dict) -> None:CODE
LOWdarts/dataprocessing/encoders/encoders.py1427 def _setup_transformer(self, params: dict) -> None:CODE
LOWdarts/utils/__init__.py15__all__ = [CODE
LOWdarts/utils/data/tabularization/__init__.py23__all__ = [CODE
LOWexamples/utils/__init__.py3__all__ = ["fix_pythonpath_if_working_locally"]CODE
Over-Commented Block14 hits · 14 pts
SeverityFileLineSnippetContext
LOWdocs/source/conf.py1# Configuration file for the Sphinx documentation builder.COMMENT
LOWdocs/source/conf.py181}COMMENT
LOWdarts/dataprocessing/encoders/encoder_base.py381 # target index; always True for all models except SKLearnModels.COMMENT
LOWdarts/dataprocessing/encoders/encoder_base.py421COMMENT
LOWdarts/tests/ad/test_anomaly_model.py261 )COMMENT
LOWdarts/tests/explainability/test_shap_explainer.py201 "output_chunk_length": 4,COMMENT
LOWdarts/models/forecasting/timesfm2p5_model.py241COMMENT
LOWdarts/models/forecasting/block_rnn_model.py201 # B: batch sizeCOMMENT
LOWdarts/models/forecasting/nf_model.py221 """COMMENT
LOWdarts/models/forecasting/nf_model.py281 elif self.converts_to_multivariate:COMMENT
LOWdarts/models/forecasting/tirex_model.py101 Optional keyword arguments.COMMENT
LOWdarts/models/forecasting/tsmixer_model.py1"""COMMENT
LOWdarts/models/forecasting/tsmixer_model.py461COMMENT
LOW.github/scripts/libomp-macOS.sh1brew install libompCOMMENT
Excessive Try-Catch Wrapping10 hits · 9 pts
SeverityFileLineSnippetContext
LOWdocs/fix_package_titles.py81 except Exception:CODE
LOWdarts/metrics/utils.py730 except Exception:CODE
LOWdarts/datasets/dataset_loaders.py136 except Exception as e:CODE
LOWdarts/datasets/dataset_loaders.py159 except Exception as e:CODE
LOWdarts/datasets/dataset_loaders.py224 except Exception as e:CODE
LOWdarts/tests/test_logging.py25 except Exception:CODE
LOWdarts/tests/test_logging.py60 except Exception:CODE
LOWdarts/utils/ts_utils.py221 except Exception as err:CODE
LOWdarts/models/forecasting/forecasting_model.py2284 except Exception as err:STRING
LOWdarts/models/forecasting/global_baseline_models.py423 except Exception as err:CODE
Modern AI Meta-Vocabulary2 hits · 6 pts
SeverityFileLineSnippetContext
MEDIUMdarts/utils/historical_forecasts/utils.py699 # get the first and last historical forecast start points for either (re)training or (zero shot) predictionCOMMENT
MEDIUMdarts/models/forecasting/patchtst_fm_model.py271 # Build the full context windowCOMMENT
Fake / Example Data1 hit · 2 pts
SeverityFileLineSnippetContext
LOWdocs/fix_package_titles.py31 # Extract docstring (enclosed by `"""lorem ipsum"""` or `'''lorem ipsum'''`)COMMENT
Slop Phrases1 hit · 2 pts
SeverityFileLineSnippetContext
LOWdarts/explainability/utils.py170 # make sure to remove any encodings from covariates if downstream tasks require covariates without encodingsCOMMENT