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AI Slop Code RIsk Monitor

dask/dask

Parallel computing with task scheduling

17.7 Elevated pattern signal View on GitHub

Maintenance and Governance Review

This report summarizes scanner evidence for dask/dask, a Python project with 13,934 GitHub stars. SynthScan examined 198,026 lines of code across 413 source files, recording 3500 pattern matches distributed across 17 syntactic categories. The legacy adjusted pattern signal is 17.7 (Elevated pattern signal); it is not an authorship estimate.

Use the findings to ask whether maintainers can explain intent, verify dependencies, simplify unnecessary scaffolding, and focus review effort. Risk Payload v1 adds ownership, supply-chain, over-engineering, and review-effort vectors when available. These are prompts for human verification, not probabilities, security findings, or measured maintenance costs.

17.7
Adjusted Signal
17.7
Raw Pattern Score
100%
Time Factor
2026-09-29
Last Push
13.9K
Stars
Python
Language
198.0K
Lines of Code
413
Files
3.5K
Pattern Hits
2026-10-12
Scan Date
0.24
HC Hit Rate

Risk Review · v3

Use each vector to guide manual verification of the underlying findings.

Cognitive Ownership Risk 42.2/100 · MEDIUM

Can maintainers explain intent, assumptions, and trade-offs? 2420 finding(s).

Hallucinated Dependency & Supply Chain Risk 18.6/100 · LOW

Are imports declared and package/API names verified? 918 finding(s).

Agent Over-Engineering Ratio 44.6/100 · MEDIUM

Are wrappers, guards, and repeated structures necessary? 2258 finding(s).

PR Review Velocity Impact 64.3/100 · HIGH

Which changes need focused human review? 3500 finding(s).

What These Metrics Mean

Adjusted Signal
Legacy pattern score normalized per 1,000 scanned lines and multiplied by the repository-level time factor. It is not an estimate of AI authorship.
Raw Pattern Score
Sum of severity- and context-weighted pattern findings before applying the time factor.
Time Factor
A coarse multiplier based on repository last-push metadata. It does not identify when individual code was written.
Pattern Hits
Count of configured pattern findings. Review each location and surrounding code before acting.
HC Hit Rate
High- and critical-severity findings per scanned file. Severity is a configured detector weight, not proof of a vulnerability or authorship.
Lines / Files
Scan coverage denominators used by the legacy normalized score.

Pattern-Signal History

This chart tracks the legacy adjusted pattern score across scan runs. Changes can reflect source changes, scan coverage, or detector/scoring versions; they do not measure AI adoption or prove that a team refactored code. Compare runs only when their scoring versions are compatible. The dashed line tracks the raw pattern-hit count.

Severity Breakdown

Groups findings by configured severity weight. Severity is not a confidence estimate, security rating, or proof that a package is missing. Verify imports against the project's manifests and inspect each finding in its local design context.

CRITICAL 1HIGH 99MEDIUM 37LOW 3363

Directory Score Breakdown

This horizontal bar chart shows where configured pattern scores accumulate across directories. Treat the bars as locations to inspect, not as evidence of authorship or code quality. Use the file-level findings to decide whether a directory needs a focused ownership, dependency, complexity, or review check.

Pattern Findings

The scanner identified 3500 distinct pattern matches across 17 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a detector match to inspect in context. 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 configured finding weight (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — legacy comment-context matches receive a ×1.5 score weight. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier under the legacy scoring model.

Hyper-Verbose Identifiers2045 hits · 1767 pts
SeverityFileLineSnippetContext
LOWconftest.py72def pytest_assertrepr_compare(op, left, right):CODE
LOWconftest.py102def allow_distributed_async_clients():CODE
LOWdask/conftest.py23def pytest_collection_modifyitems(config, items):CODE
LOWdask/_expr.py96 def _tree_repr_argument_construction(self, i, op, header):CODE
LOWdask/system.py17def _try_extract_cgroup_cpu_quota():CODE
LOWdask/config.py700def expand_environment_variables(config: Any) -> Any:CODE
LOWdask/utils_test.py76 def test_data_not_in_dict_is_ok(self):CODE
LOWdask/utils_test.py86 def test_get_with_list_top_level(self):CODE
LOWdask/utils_test.py102 def test_get_with_nested_list(self):CODE
LOWdask/utils_test.py108 def test_get_works_with_unhashables_in_values(self):CODE
LOWdask/optimization.py71def default_fused_linear_keys_renamer(keys):CODE
LOWdask/optimization.py409def default_fused_keys_renamer(keys, max_fused_key_length=120):CODE
LOWdask/_pandas_compat.py96def check_groupby_axis_deprecation():CODE
LOWdask/_pandas_compat.py110def check_observed_deprecation():CODE
LOWdask/_pandas_compat.py124def check_convert_dtype_deprecation():CODE
LOWdask/_pandas_compat.py138def check_apply_dataframe_deprecation():CODE
LOWdask/_pandas_compat.py154def is_any_real_numeric_dtype(arr_or_dtype) -> bool:CODE
LOWdask/delayed.py77def _finalize_args_collections(args, collections):CODE
LOWdask/utils.py2222def get_default_shuffle_method() -> str:CODE
LOWdask/blockwise.py1423def zero_broadcast_dimensions(lol, nblocks):CODE
LOWdask/highlevelgraph.py34def compute_layer_dependencies(layers):CODE
LOWdask/highlevelgraph.py37 def _find_layer_containing_key(key):CODE
LOW⚡dask/_compatibility.py50def import_optional_dependency(CODE
LOW⚡dask/_compatibility.py60def import_optional_dependency(CODE
LOW⚡dask/_compatibility.py69def import_optional_dependency(CODE
LOW⚡dask/layers.py110def normalize_array_slice_dep(dep):CODE
LOW⚡dask/layers.py115def normalize_array_block_id_dep(dep):CODE
LOW⚡dask/layers.py120def normalize_array_values_dep(dep):CODE
LOWdask/layers.py256def _expand_keys_around_center(k, dims, name=None, axes=None):CODE
LOWdask/sizeof.py115 def sizeof_numba_devicendarray(x):CODE
LOWdask/sizeof.py255 def sizeof_pyarrow_chunked_array(data):CODE
LOWdask/sizeof.py304def _register_entry_point_plugins():CODE
LOWdask/tokenize.py83def _maybe_raise_nondeterministic(msg: str) -> None:CODE
LOWdask/tokenize.py185def normalize_builtin_function_or_method(func):CODE
LOW⚡dask/tokenize.py350 def normalize_extension_array(arr):CODE
LOW⚡dask/tokenize.py357 def normalize_extension_array(arr):CODE
LOW⚡dask/tokenize.py364 def normalize_categorical_dtype(dtype):CODE
LOWdask/multiprocessing.py25def _reduce_method_descriptor(m):CODE
LOWdask/multiprocessing.py263def initialize_worker_process(user_initializer=None):CODE
LOWdask/base.py483def _rebuild_composite_collection(CODE
LOWdask/dataframe/accessor.py105def register_dataframe_accessor(name):CODE
LOWdask/dataframe/_pyarrow.py42def is_object_string_dataframe(x) -> bool:CODE
LOWdask/dataframe/methods.py191def describe_numeric_aggregate(CODE
LOWdask/dataframe/methods.py238def describe_nonnumeric_aggregate(stats, name):CODE
LOWdask/dataframe/multi.py254 def _is_index_level_reference(x, key):CODE
LOWdask/dataframe/multi.py278 def _is_column_label_reference(df, key):CODE
LOWdask/dataframe/core.py64def _get_divisions_map_partitions(CODE
LOWdask/dataframe/core.py271def _map_freq_to_period_start(freq):CODE
LOWdask/dataframe/core.py445def _sqrt_and_convert_to_timedelta(partition, axis, dtype=None, *args, **kwargs):CODE
LOW⚡dask/dataframe/shuffle.py216def ensure_cleanup_on_exception(p):CODE
LOW⚡dask/dataframe/backends.py237def get_pyarrow_schema_pandas(obj, preserve_index=None):CODE
LOW⚡dask/dataframe/backends.py242def get_pyarrow_table_from_pandas(obj, **kwargs):CODE
LOW⚡dask/dataframe/backends.py248def get_pandas_dataframe_from_pyarrow(meta, table, **kwargs):CODE
LOWdask/dataframe/backends.py274def make_meta_pandas_datetime_tz(x, index=None):CODE
LOWdask/dataframe/backends.py502def _meta_lib_from_array_numpy(x):CODE
LOWdask/dataframe/backends.py510def union_categoricals_pandas(to_union, sort_categories=False, ignore_order=False):CODE
LOWdask/dataframe/backends.py524def get_parallel_type_dataframe(_):CODE
LOWdask/dataframe/backends.py586def _union_categoricals_wrapper(CODE
LOWdask/dataframe/backends.py782def is_categorical_dtype_pandas(obj):CODE
LOWdask/dataframe/backends.py803def to_pandas_dispatch_from_pandas(data, **kwargs):CODE
1985 more matches not shown…
Unused Imports902 hits · 713 pts
SeverityFileLineSnippetContext
LOWconftest.py1CODE
LOWconftest.py27CODE
LOWconftest.py32CODE
LOWconftest.py37CODE
LOWconftest.py42CODE
LOWconftest.py47CODE
LOWconftest.py52CODE
LOWdask/threaded.py7CODE
LOWdask/conftest.py1CODE
LOWdask/system.py1CODE
LOWdask/config.py1CODE
LOWdask/utils_test.py1CODE
LOWdask/local.py110CODE
LOWdask/order.py1CODE
LOWdask/optimization.py1CODE
LOWdask/_pandas_compat.py7CODE
LOWdask/datasets.py1CODE
LOWdask/cache.py1CODE
LOWdask/__init__.py1CODE
LOWdask/__init__.py3CODE
LOWdask/__init__.py3CODE
LOWdask/__init__.py4CODE
LOWdask/__init__.py4CODE
LOWdask/__init__.py4CODE
LOWdask/__init__.py4CODE
LOWdask/__init__.py13CODE
LOWdask/__init__.py13CODE
LOWdask/__init__.py13CODE
LOWdask/__init__.py13CODE
LOWdask/__init__.py13CODE
LOWdask/__init__.py13CODE
LOWdask/__init__.py13CODE
LOWdask/__init__.py22CODE
LOWdask/__init__.py23CODE
LOWdask/__init__.py24CODE
LOWdask/core.py1CODE
LOWdask/_dispatch.py1CODE
LOWdask/ml.py1CODE
LOWdask/_collections.py1CODE
LOWdask/backends.py1CODE
LOWdask/distributed.py1CODE
LOWdask/distributed.py11CODE
LOWdask/context.py5CODE
LOWdask/delayed.py1CODE
LOWdask/cli.py1CODE
LOWdask/utils.py1CODE
LOWdask/callbacks.py1CODE
LOWdask/task_spec.py1CODE
LOWdask/task_spec.py3CODE
LOWdask/task_spec.py3CODE
LOWdask/task_spec.py3CODE
LOWdask/task_spec.py3CODE
LOWdask/task_spec.py3CODE
LOWdask/task_spec.py3CODE
LOWdask/graph_manipulation.py6CODE
LOWdask/dot.py1CODE
LOWdask/_compatibility.py1CODE
LOWdask/typing.py1CODE
LOWdask/sizeof.py1CODE
LOWdask/rewrite.py1CODE
842 more matches not shown…
Empty Error Handlers84 hits · 420 pts
SeverityFileLineSnippetContext
HIGHdask/_expr.py42except AttributeError:CODE
HIGHdask/_expr.py472except KeyError:CODE
HIGHdask/system.py39except Exception:CODE
HIGHdask/system.py27except Exception:CODE
HIGHdask/config.py283except (SyntaxError, ValueError):CODE
HIGHdask/config.py368except OSError:CODE
HIGHdask/config.py231except OSError:CODE
HIGHdask/utils_test.py57except KeyError:CODE
HIGHdask/utils_test.py69except KeyError:CODE
HIGHdask/local.py135except Empty:CODE
HIGHdask/optimization.py357except TypeError:CODE
HIGHdask/core.py339except Exception:CODE
HIGHdask/core.py356except TypeError: # not hashableCODE
HIGHdask/core.py148except TypeError: # not hashableCODE
HIGHdask/delayed.py926except AttributeError:CODE
HIGHdask/utils.py2049except TypeError: # `obj` not hashableCODE
HIGHdask/utils.py1367except (ImportError, ValueError):CODE
HIGHdask/utils.py421except AttributeError:CODE
HIGHdask/utils.py481except OSError:CODE
HIGHdask/utils.py757except KeyError:CODE
HIGHdask/utils.py768except KeyError:CODE
HIGHdask/utils.py489except AttributeError:CODE
HIGHdask/highlevelgraph.py537except KeyError:CODE
HIGHdask/highlevelgraph.py541except (KeyError, IndexError, TypeError):CODE
HIGHdask/highlevelgraph.py548except KeyError:CODE
HIGHdask/graph_manipulation.py131except ImportError:CODE
HIGHdask/graph_manipulation.py138except ImportError:CODE
HIGHdask/rewrite.py395except TypeError:CODE
HIGHdask/hashing.py17except ImportError:CODE
HIGHdask/hashing.py36except ImportError:CODE
HIGHdask/hashing.py50except ImportError:CODE
HIGHdask/hashing.py82except (TypeError, OverflowError):CODE
HIGHdask/hashing.py89except (TypeError, OverflowError):CODE
HIGHdask/base.py250except AttributeError:CODE
HIGHdask/base.py1294except (ImportError, ValueError):CODE
HIGHdask/base.py998except ImportError:CODE
HIGHdask/_task_spec.py229except TypeError:CODE
HIGHdask/dataframe/accessor.py20except Exception:CODE
HIGHdask/dataframe/accessor.py41except Exception:CODE
HIGHdask/dataframe/core.py85except Exception:CODE
HIGHdask/dataframe/backends.py54except ImportError:CODE
HIGHdask/dataframe/backends.py232except ImportError:CODE
HIGHdask/dataframe/backends.py868except ImportError:CODE
HIGHdask/dataframe/backends.py334except Exception:CODE
HIGHdask/dataframe/utils.py42except ImportError:CODE
HIGHdask/dataframe/utils.py509except (TypeError, IndexError, ValueError):CODE
HIGHdask/dataframe/indexing.py56except TypeError:CODE
HIGHdask/dataframe/groupby.py571except Exception:CODE
HIGHdask/dataframe/groupby.py1061except KeyError:CODE
HIGHdask/dataframe/groupby.py538except KeyError:CODE
HIGHdask/dataframe/partitionquantiles.py452except (ValueError, TypeError):CODE
HIGHdask/dataframe/dask_expr/_expr.py871except Exception:CODE
HIGHdask/dataframe/dask_expr/_collection.py757except TypeError:CODE
HIGHdask/dataframe/dask_expr/tests/_util.py40except ImportError:CODE
HIGHdask/dataframe/io/__init__.py12except ImportError:CODE
HIGHdask/dataframe/io/parquet/arrow.py694except OSError:CODE
HIGHdask/dataframe/tests/test_accessors.py24except AttributeError:CODE
HIGHdask/bytes/tests/test_s3.py102except urllib.request.URLError:CODE
HIGHdask/array/core.py841except Exception:CODE
HIGHdask/array/core.py1361except (AttributeError, KeyError):CODE
24 more matches not shown…
Deep Nesting226 hits · 208 pts
SeverityFileLineSnippetContext
LOWdask/threaded.py62CODE
LOWdask/_expr.py299CODE
LOWdask/_expr.py367CODE
LOWdask/_expr.py612CODE
LOWdask/_expr.py1161CODE
LOWdask/_expr.py1237CODE
LOWdask/config.py209CODE
LOWdask/config.py499CODE
LOWdask/config.py439CODE
LOWdask/local.py144CODE
LOWdask/local.py382CODE
LOWdask/order.py81CODE
LOWdask/order.py618CODE
LOWdask/order.py226CODE
LOWdask/order.py299CODE
LOWdask/order.py446CODE
LOWdask/optimization.py20CODE
LOWdask/optimization.py86CODE
LOWdask/optimization.py378CODE
LOWdask/optimization.py458CODE
LOWdask/core.py111CODE
LOWdask/core.py323CODE
LOWdask/core.py362CODE
LOWdask/delayed.py414CODE
LOWdask/utils.py147CODE
LOWdask/utils.py334CODE
LOWdask/utils.py379CODE
LOWdask/utils.py465CODE
LOWdask/utils.py225CODE
LOWdask/utils.py2269CODE
LOWdask/utils.py227CODE
LOWdask/blockwise.py914CODE
LOWdask/blockwise.py1109CODE
LOWdask/blockwise.py1262CODE
LOWdask/blockwise.py657CODE
LOWdask/blockwise.py746CODE
LOWdask/highlevelgraph.py127CODE
LOWdask/highlevelgraph.py201CODE
LOWdask/highlevelgraph.py238CODE
LOWdask/dot.py64CODE
LOWdask/dot.py126CODE
LOWdask/dot.py318CODE
LOWdask/_compatibility.py69CODE
LOWdask/layers.py323CODE
LOWdask/base.py90CODE
LOWdask/base.py428CODE
LOWdask/base.py515CODE
LOWdask/base.py877CODE
LOWdask/base.py1225CODE
LOWdask/base.py547CODE
LOWdask/_task_spec.py117CODE
LOWdask/_task_spec.py203CODE
LOWdask/_task_spec.py276CODE
LOWdask/_task_spec.py620CODE
LOWdask/_task_spec.py647CODE
LOWdask/_task_spec.py938CODE
LOWdask/dataframe/multi.py77CODE
LOWdask/dataframe/multi.py296CODE
LOWdask/dataframe/backends.py279CODE
LOWdask/dataframe/backends.py378CODE
166 more matches not shown…
Cross-Language Confusion15 hits · 92 pts
SeverityFileLineSnippetContext
HIGHdask/base.py1273 # If undefined, fallback to `config` or worst case CPU_COUNT.STRING
HIGHdask/dataframe/core.py146 and columns.equals(df.columns)CODE
HIGHdask/dataframe/groupby.py50 return df.index.equals(by.index)CODE
HIGH⚡dask/dataframe/dask_expr/io/parquet.py133 if part_expr.equals(pc.scalar(True)):CODE
HIGH⚡dask/dataframe/dask_expr/io/parquet.py136 if pqformat.read_options.equals(pa_ds.ParquetFileFormat().read_options):CODE
HIGH⚡dask/dataframe/dask_expr/io/parquet.py140 assert fs.equals(self._fragment.filesystem)CODE
HIGHdask/dataframe/io/parquet/core.py531 # Start conventional (non-null) filteringCOMMENT
HIGH⚡dask/dataframe/tests/test_groupby.py1460 assert res0_a.equals(res0_b)CODE
HIGH⚡dask/dataframe/tests/test_groupby.py1461 assert res1_a.equals(res1_b)CODE
HIGH⚡dask/dataframe/tests/test_dataframe.py4467 assert res.dtypes.equals(ddf2.dtypes)CODE
HIGHdask/dataframe/tests/test_dataframe.py5214 assert schema.equals(table.schema)CODE
HIGHdask/dataframe/tests/test_dataframe.py5231 assert schema.equals(table.schema)CODE
HIGHdask/array/stats.py440 # If df is undefined, variances are zero (assumes n1 > 0 & n2 > 0).COMMENT
HIGHdask/array/overlap.py943 return bn.push(array, limit, axis)CODE
HIGHdask/array/tests/test_overlap.py769 expected = bottleneck.push(array, axis=0, n=n)CODE
Excessive Try-Catch Wrapping55 hits · 62 pts
SeverityFileLineSnippetContext
LOWdask/system.py27 except Exception:CODE
LOWdask/system.py39 except Exception:CODE
LOWdask/config.py184 except Exception as exc:CODE
LOWdask/core.py339 except Exception:CODE
LOWdask/backends.py141 except Exception as e:CODE
LOWdask/cli.py178 except Exception as e:CODE
MEDIUMdask/utils.py785def __doc__(self):CODE
MEDIUMdask/utils.py1897def has_keyword(func, keyword):CODE
LOWdask/utils.py685 except Exception:CODE
LOWdask/utils.py690 except Exception:CODE
LOWdask/utils.py753 except Exception:CODE
LOWdask/utils.py1116 except Exception as e:CODE
LOWdask/utils.py1137 except Exception as e:CODE
LOWdask/utils.py1900 except Exception:CODE
LOWdask/utils.py1998 except Exception:CODE
LOWdask/sizeof.py310 except Exception:CODE
LOWdask/rewrite.py408 except Exception:CODE
LOWdask/tokenize.py211 except Exception:CODE
LOWdask/tokenize.py247 except Exception:CODE
LOWdask/tokenize.py253 except Exception:CODE
LOWdask/tokenize.py474 except Exception:CODE
MEDIUMdask/tokenize.py350def normalize_extension_array(arr):CODE
LOWdask/multiprocessing.py120 except Exception as e:CODE
LOWdask/_task_spec.py787 except Exception:CODE
LOWdask/dataframe/accessor.py20 except Exception:CODE
LOWdask/dataframe/accessor.py41 except Exception:CODE
LOWdask/dataframe/core.py44 except Exception:CODE
LOWdask/dataframe/core.py85 except Exception:CODE
LOW⚡dask/dataframe/shuffle.py225 except Exception:CODE
LOW⚡dask/dataframe/shuffle.py230 except Exception:CODE
MEDIUMdask/dataframe/shuffle.py110def set_partitions_pre(s, divisions, ascending=True, na_position="last"):CODE
LOWdask/dataframe/backends.py334 except Exception:CODE
LOWdask/dataframe/backends.py659 except Exception:CODE
LOWdask/dataframe/utils.py150 except Exception as e:CODE
LOWdask/dataframe/groupby.py571 except Exception:CODE
LOWdask/dataframe/partitionquantiles.py322 except Exception:CODE
MEDIUMdask/dataframe/dask_expr/_expr.py153def __getattr__(self, key):CODE
LOWdask/dataframe/dask_expr/_expr.py456 except Exception:CODE
LOWdask/dataframe/dask_expr/_expr.py871 except Exception:CODE
LOWdask/dataframe/io/csv.py119 except Exception as e:CODE
LOWdask/dataframe/tests/test_utils_dataframe.py388 except Exception as e:CODE
LOWdask/dataframe/tests/test_utils_dataframe.py397 except Exception as e:CODE
MEDIUMdask/dataframe/tests/test_utils_dataframe.py384def test_raise_on_meta_error():CODE
LOWdask/dataframe/tests/test_dataframe.py4515 except Exception:CODE
LOWdask/array/core.py489 except Exception as e:CODE
LOWdask/array/core.py841 except Exception:CODE
LOWdask/array/core.py5180 except Exception:CODE
LOWdask/array/utils.py97 except Exception:CODE
LOWdask/array/utils.py163 except Exception:CODE
LOWdask/array/_array_expr/_map_blocks.py310 except Exception:CODE
LOWdask/array/_array_expr/_blockwise.py280 except Exception:CODE
LOWdask/array/_array_expr/_utils.py64 except Exception:CODE
LOWdask/tests/test_callbacks.py53 except Exception as e:CODE
LOWdask/tests/test_callbacks.py62 except Exception as e:CODE
LOWdask/diagnostics/profile.py279 except Exception: # could be a few different exceptionsCODE
AI Structural Patterns51 hits · 48 pts
SeverityFileLineSnippetContext
LOWdask/local.py382CODE
LOWdask/utils.py2122CODE
LOWdask/dot.py126CODE
LOWdask/dot.py421CODE
LOWdask/dataframe/groupby.py593CODE
LOWdask/dataframe/dask_expr/_reductions.py1219CODE
LOWdask/dataframe/dask_expr/_collection.py5140CODE
LOWdask/dataframe/dask_expr/_collection.py5594CODE
LOWdask/dataframe/dask_expr/_collection.py5687CODE
LOWdask/dataframe/dask_expr/_collection.py1636CODE
LOWdask/dataframe/dask_expr/_collection.py1801CODE
LOWdask/dataframe/dask_expr/_collection.py2132CODE
LOWdask/dataframe/dask_expr/_collection.py2407CODE
LOWdask/dataframe/dask_expr/_collection.py2859CODE
LOWdask/dataframe/dask_expr/_collection.py3342CODE
LOWdask/dataframe/dask_expr/_collection.py3534CODE
LOWdask/dataframe/dask_expr/io/parquet.py337CODE
LOWdask/dataframe/io/csv.py418CODE
LOWdask/dataframe/io/csv.py764CODE
LOWdask/dataframe/io/csv.py715CODE
LOWdask/dataframe/io/sql.py195CODE
LOWdask/dataframe/io/sql.py422CODE
LOWdask/dataframe/io/json.py20CODE
LOWdask/dataframe/io/json.py108CODE
LOWdask/dataframe/io/parquet/core.py226CODE
LOWdask/array/numpy_compat.py170CODE
LOWdask/array/creation.py857CODE
LOWdask/array/creation.py1144CODE
LOWdask/array/creation.py1210CODE
LOWdask/array/core.py551CODE
LOWdask/array/core.py3468CODE
LOWdask/array/gufunc.py172CODE
LOWdask/array/gufunc.py647CODE
LOWdask/array/utils.py299CODE
LOWdask/array/blockwise.py17CODE
LOWdask/array/reductions.py83CODE
LOWdask/array/reductions.py1517CODE
LOWdask/array/reductions.py1561CODE
LOWdask/array/reductions.py1640CODE
LOWdask/array/reductions.py1839CODE
LOWdask/array/routines.py538CODE
LOWdask/array/routines.py1958CODE
LOWdask/array/_reductions_generic.py25CODE
LOWdask/array/_array_expr/_map_blocks.py16CODE
LOWdask/array/_array_expr/_gufunc.py173CODE
LOWdask/array/_array_expr/_gufunc.py683CODE
LOWdask/array/_array_expr/_reductions.py199CODE
LOWdask/array/_array_expr/_reductions.py25CODE
LOWdask/array/_array_expr/_collection.py694CODE
LOWdask/array/_array_expr/_collection.py1005CODE
LOWdask/bag/text.py17CODE
AI Slop Vocabulary20 hits · 40 pts
SeverityFileLineSnippetContext
MEDIUMdask/local.py635 """Sorting key function that is robust to different typesSTRING
MEDIUMdask/utils.py1974 # If we convert the key, recurse to utilize LRU cache betterCOMMENT
LOWdask/blockwise.py1282 # Fast path: if there's only one input we can just use it as-is.COMMENT
LOWdask/dot.py228 # IPython can't display this format natively, so just return None.COMMENT
MEDIUMdask/dataframe/dask_expr/_quantile.py111 # Add 0 and 100 during calculation for more robust behavior (hopefully)COMMENT
MEDIUMdask/dataframe/dask_expr/_merge.py303 # 1. Add/leverage partition statisticsCOMMENT
LOWdask/dataframe/dask_expr/_reductions.py1071 # Drop all of the columns, just pass through the indexCOMMENT
LOWdask/dataframe/dask_expr/io/parquet.py1432 # empty dataframe - just use metaCOMMENT
LOWdask/dataframe/io/parquet/arrow.py1327 # Check if this is a very simple case where we can just returnCOMMENT
LOWdask/dataframe/tests/test_groupby.py2225 # just pass the pandas result as meta for convenienceCOMMENT
LOWdask/array/slicing.py257 # No lists, hooray! just use slice_slices_and_integersCOMMENT
LOWdask/array/core.py6001 # output has a zero dimension, just create a new zero-shape array with theCOMMENT
LOWdask/array/gufunc.py479 # NOTE: we likely could just use `meta` instead of `tmp._meta`,COMMENT
LOWdask/array/utils.py156 # min/max functions have no identity, just use the same input type when there's only oneCOMMENT
MEDIUMdask/array/percentile.py177 # Add 0 and 100 during calculation for more robust behavior (hopefully)COMMENT
MEDIUM⚡dask/array/tests/test_array_core.py2349 # disabled things are nuanced and hardware-dependent. Don't risk it.COMMENT
MEDIUMdask/array/tests/test_array_core.py2330 # disabled things are nuanced and hardware-dependent. Don't risk it.COMMENT
LOWdask/array/_array_expr/_slicing.py299 # No lists, hooray! just use slice_slices_and_integersCOMMENT
LOWdask/array/_array_expr/_gufunc.py457 # NOTE: we likely could just use `meta` instead of `tmp._meta`,COMMENT
LOWdask/array/_array_expr/_utils.py57 # min/max functions have no identity, just use the same input type when there's only oneCOMMENT
Redundant / Tautological Comments24 hits · 38 pts
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LOWdask/_expr.py386 # Check if we've already simplified for these dependentsCOMMENT
LOWdask/_expr.py615 # Check if we are replacing a literalCOMMENT
LOWdask/dataframe/dask_expr/_collection.py3098 # Check if key is in columns if keyCOMMENT
LOWdask/dataframe/dask_expr/_collection.py5936 # Check if `func` supports column projectionCOMMENT
LOWdask/dataframe/dask_expr/_groupby.py1536 # Check if we can project columnsCOMMENT
LOWdask/dataframe/io/utils.py188 # Check if we are using `fsspec.parquet`.COMMENT
LOWdask/dataframe/io/tests/test_parquet.py3040 # Check if we can avoid writing an actual fileCOMMENT
LOWdask/dataframe/io/orc/arrow.py73 # Check if we can aggregate adjacent parts togetherCOMMENT
LOWdask/dataframe/io/parquet/arrow.py326 # Check if we need to generate a fragment for filtering.COMMENT
LOWdask/dataframe/io/parquet/arrow.py454 # Check if filesystem was specified as a dataset optionCOMMENT
LOWdask/dataframe/io/parquet/arrow.py1327 # Check if this is a very simple case where we can just returnCOMMENT
LOWdask/dataframe/io/parquet/arrow.py1449 # Check if we are using a simple file-partition mapCOMMENT
LOWdask/dataframe/io/parquet/arrow.py1583 # Check if we have empty parts to returnCOMMENT
LOWdask/dataframe/io/parquet/arrow.py1646 # Check if we have partitioning information.COMMENT
LOWdask/dataframe/io/parquet/arrow.py1649 # Check if we need to generate a fragment.COMMENT
LOWdask/dataframe/io/parquet/utils.py59 # Check if fs was specified as a dataset optionCOMMENT
LOWdask/array/core.py3409 # Check if dtype.itemsize is greater than 0COMMENT
LOWdask/array/gufunc.py429 #### Check if core dimensions consist of only one chunkCOMMENT
LOWdask/array/gufunc.py436 #### Check if loop dimensions consist of same chunksizes, when they have sizes > 1COMMENT
LOWdask/array/tests/test_array_function.py169 # Check if it's an equivalent arrayCOMMENT
LOW⚡dask/array/tests/test_routines.py765 # Check if the sum of the bins equals the number of samplesCOMMENT
LOW⚡dask/array/tests/test_routines.py792 # Check if return type is same as histCOMMENT
LOWdask/array/_array_expr/_gufunc.py431 #### Check if core dimensions consist of only one chunkCOMMENT
LOWdask/array/_array_expr/_gufunc.py438 #### Check if loop dimensions consist of same chunksizes, when they have sizes > 1COMMENT
Over-Commented Block37 hits · 36 pts
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LOWcontinuous_integration/pixi-recipes/s3fs/recipe.yaml1package:COMMENT
LOWdask/order.py401 known_runnable_paths[current] = [path]COMMENT
LOWdask/order.py461 return TrueCOMMENT
LOWdask/order.py481 # dependencies are in resultCOMMENT
LOWdask/order.py501 # 1. Determine the target node by calling ``get_target`` and append theCOMMENT
LOWdask/order.py521 # Given this, the algorithm is as follows:COMMENT
LOWdask/multiprocessing.py41# By default, tracebacks can't be serialized using pickle. However, theCOMMENT
LOWdask/_task_spec.py301 # user is requesting and by collapsing we'd no longer be able toCOMMENT
LOWdask/dataframe/_pyarrow_compat.py1from __future__ import annotationsCOMMENT
LOWdask/dataframe/partitionquantiles.py321 return np.array(None, dtype=dtype)COMMENT
LOWdask/dataframe/dask_expr/_expr.py2141 # anymore. Otherwise, a chain of Filters might block ProjectionsCOMMENT
LOWdask/dataframe/io/parquet/arrow.py1001 except StopIteration:COMMENT
LOWdask/dataframe/io/parquet/arrow.py1021 # | F | True | None | 1 row-group per partition |COMMENT
LOWdask/dataframe/io/parquet/core.py301 agg_name = f"agg-{name}"COMMENT
LOWdask/array/reshape.py141 # The previous step squashed the whole dimension into a singleCOMMENT
LOWdask/array/slicing.py1341 # of the result of the original slice.COMMENT
LOWdask/array/slicing.py1561 """COMMENT
LOWdask/array/slicing.py1681 if is_dask_collection(index):COMMENT
LOWdask/array/slicing.py1721 f"of shape {tuple(implied_shape)}"COMMENT
LOWdask/array/slicing.py1741 # For example:COMMENT
LOWdask/array/slicing.py1761 # array. An element of `None` will end upCOMMENT
LOWdask/array/slicing.py1841 in_keys = list(flatten(array.__dask_keys__()))COMMENT
LOWdask/array/rechunk.py81 indicator with a corresponding cumulative sum,COMMENT
LOWdask/array/stats.py21#COMMENT
LOWdask/array/routines.py1461 # This tuple of zeros represents the chunk index along the columnsCOMMENT
LOWdask/array/tests/test_reshape.py201 (2, 2, 3, 4),COMMENT
LOWdask/array/_array_expr/_gufunc.py501 # output_shape = loop_output_shape + core_output_shapeCOMMENT
LOWdocs/source/conf.py1#COMMENT
LOWdocs/source/conf.py81# General information about the project.COMMENT
LOWdocs/source/conf.py101# default_role = NoneCOMMENT
LOWdocs/source/conf.py121COMMENT
LOWdocs/source/conf.py141COMMENT
LOWdocs/source/conf.py161COMMENT
LOWdocs/source/conf.py181# If true, "Created using Sphinx" is shown in the HTML footer. Default is True.COMMENT
LOWdocs/source/conf.py201latex_elements: dict[str, str] = {COMMENT
LOWdocs/source/conf.py221# not chapters.COMMENT
LOWdocs/source/conf.py281COMMENT
Self-Referential Comments15 hits · 33 pts
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MEDIUMdask/dataframe/io/io.py173 # Create a mapping of chunk number in the incoming array toCOMMENT
MEDIUMdask/dataframe/io/tests/test_parquet.py3059 # Create a Dask DataFrame if size (100, 10) with 5 partitions and write to localCOMMENT
MEDIUMdask/dataframe/io/tests/test_parquet.py3088 # Create a Dask DataFrame with 5 partitions and write to local, partitioning on the column A and column BCOMMENT
MEDIUMdask/dataframe/io/tests/test_parquet.py3903 # Create a pandas-metadata-free partitioned parquet. By default it willCOMMENT
MEDIUMdask/dataframe/io/tests/test_sql.py131 # Create an empty table in a different schema.STRING
MEDIUMdask/dataframe/io/tests/test_sql.py143 # Create the schema and the table.STRING
MEDIUMdask/array/slicing.py1319 # Initialize output variablesSTRING
MEDIUMdask/array/slicing.py1843 # Create a new "setitem" dask entry for each block in the arraySTRING
MEDIUMdask/array/slicing.py2006 # Create the part of the full assignment value that is to beSTRING
MEDIUMdask/array/slicing.py2019 # Define the assignment function for this block.STRING
MEDIUMdask/array/tests/test_array_core.py5207 # Create a dask array with chunks that don't align with shardsCOMMENT
MEDIUMdask/array/tests/test_array_core.py5228 # Create a sharded zarr arrayCOMMENT
MEDIUMdask/tests/test_spark_compat.py37 # Create a spark session. Note that we set the timezone to UTC to avoidCOMMENT
MEDIUMdask/tests/test_delayed.py394 # Create a list with a dask value, and test that it's not computedCOMMENT
MEDIUMdocs/source/conf.py5# This file is execfile()d with the current directory set to its containing dir.COMMENT
Decorative Section Separators8 hits · 24 pts
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MEDIUMdask/dataframe/methods.py38# ---------------------------------COMMENT
MEDIUMdask/dataframe/methods.py40# ---------------------------------COMMENT
MEDIUMdask/dataframe/methods.py428# ---------------------------------COMMENT
MEDIUMdask/dataframe/methods.py430# ---------------------------------COMMENT
MEDIUMdask/dataframe/io/tests/test_parquet.py268 # ----------COMMENT
MEDIUMdask/dataframe/io/parquet/core.py20# ----------------------------------------------------------------------COMMENT
MEDIUMdask/array/stats.py85# -----------------COMMENT
MEDIUMdask/array/stats.py87# -----------------COMMENT
Modern Structural Boilerplate14 hits · 14 pts
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LOWdask/delayed.py48__all__ = ["Delayed", "delayed"]CODE
LOWdask/callbacks.py7__all__ = ["Callback", "add_callbacks"]CODE
LOWdask/task_spec.py5__all__ = [CODE
LOWdask/sizeof.py16logger = logging.getLogger(__name__)CODE
LOWdask/dataframe/__init__.py75__all__ = [CODE
LOWdask/dataframe/shuffle.py13logger = logging.getLogger(__name__)CODE
LOWdask/dataframe/extensions.py20__all__ = [CODE
LOWdask/dataframe/_compat.py50__all__ = [CODE
LOWdask/dataframe/dask_expr/datasets.py16__all__ = ["timeseries"]CODE
LOWdask/dataframe/dask_expr/diagnostics/__init__.py6__all__ = ["analyze", "explain"]CODE
LOWdask/dataframe/io/demo.py18__all__ = [CODE
LOWdask/array/__init__.py46__all__ = [CODE
LOWdask/array/stats.py70__all__ = [CODE
LOWdask/bag/__init__.py3__all__ = [CODE
Hallucination Indicators1 hit · 10 pts
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CRITICALdask/dataframe/dask_expr/tests/test_merge.py282 assert sorted(result.expr.frame.frame.left.operand("columns")) == ["b", "x"]CODE
Dead Code1 hit · 2 pts
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MEDIUMdask/_task_spec.py913CODE
Slop Phrases1 hit · 2 pts
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LOWdask/dataframe/tests/test_accessors.py161 # make sure to pass through args & kwargsCOMMENT
Overly Generic Function Names1 hit · 1 pts
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LOWdask/local.py246def execute_task(key, task_info, dumps, loads, get_id, pack_exception):CODE