Function condition_validator has a Cognitive Complexity of 7 (exceeds 5 allowed). Consider refactoring.

Open

def condition_validator(
    col_names: Union[str, List[str]],
    condition_name: Optional[str] = None,
    actions: Union[
        List[Callable[[str, str, Any, Optional[Any]], None]], Callable[[str, str, Any, Optional[Any]], None]

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Function resolve has a Cognitive Complexity of 7 (exceeds 5 allowed). Consider refactoring.

Open

    def resolve(
        self,
        *,
        pandas: Optional[pd.DataFrame] = None,
        row: Optional[Mapping[str, Any]] = None,

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Function __post_init__ has a Cognitive Complexity of 7 (exceeds 5 allowed). Consider refactoring.

Open

    def __post_init__(self):
        if self.column_name and self.column_type:
            logger.warning(f"ResolverSpec: column {self.column_name} also specified type, name takes precedence")
        if not (self.column_name or self.column_type):
            raise ValueError("ResolverSpec: resolver specification must supply name or type")

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Method doTrack has a Cognitive Complexity of 7 (exceeds 5 allowed). Consider refactoring.

Open

  private void doTrack(HashMap<String, ?> row) {
    boolean dirty = this.schema.resolve(row);
    if (dirty) {
      Set<String> schemaColumnNames = this.schema.getColNames();
      Set<String> newColumnNames = new HashSet<>();

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Function generate_profile_summary has a Cognitive Complexity of 7 (exceeds 5 allowed). Consider refactoring.

Open

def generate_profile_summary(
    target_view: DatasetProfileView, config: Optional[SummaryConfig]
) -> Optional[Dict[str, Any]]:
    if config is None:
        config = SummaryConfig()

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Function calculate_drift_values has a Cognitive Complexity of 7 (exceeds 5 allowed). Consider refactoring.

Open

def calculate_drift_values(
    target_view: DatasetProfileView, reference_view: DatasetProfileView, statistic=False
) -> Dict[str, Optional[Union[ColumnDriftValue, ColumnDriftStatistic]]]:
    """Calculate drift values between both profiles. Applicable for numerical and categorical features.

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Method merge has a Cognitive Complexity of 7 (exceeds 5 allowed). Consider refactoring.

Open

  public DatasetProfileView merge(DatasetProfileView otherView) {
    if (otherView == null) {
      return this;
    }

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Function _get_segments has a Cognitive Complexity of 7 (exceeds 5 allowed). Consider refactoring.

Open

    def _get_segments(self, reference_results: SegmentedResultSet, target_results: SegmentedResultSet):
        if len(reference_results.partitions) > 1 and len(target_results.partitions) > 1:
            logger.warning("More than one partition found. Only the first partition will be used for the estimation.")
        if len(reference_results.partitions) != len(target_results.partitions):
            raise ValueError("The number of partitions in the reference and target results must be the same.")

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Function whylogs_pandas_segmented_profiler has a Cognitive Complexity of 7 (exceeds 5 allowed). Consider refactoring.

Open

def whylogs_pandas_segmented_profiler(
    pdf_iterator: Iterable[pd.DataFrame], schema: Optional[DatasetSchema] = None
) -> Iterable[pd.DataFrame]:
    if schema is None or not schema.segments:
        raise ValueError(

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Function to_protobuf has a Cognitive Complexity of 7 (exceeds 5 allowed). Consider refactoring.

Open

    def to_protobuf(self) -> MetricMessage:
        msg = {}
        for sub_name, metrics in self.submetrics.items():
            for namespace, metric in metrics.items():
                sub_msg = metric.to_protobuf()

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Method merge has a Cognitive Complexity of 7 (exceeds 5 allowed). Consider refactoring.

Open

  public ColumnProfileView merge(ColumnProfileView otherView) {
    if (otherView == null) {
      // TODO: log warning that otehrwas null and this returns original
      return this;
    }

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Function __init__ has a Cognitive Complexity of 7 (exceeds 5 allowed). Consider refactoring.

Open

    def __init__(self, schedule: Schedule, fn: Callable[[], Any], timer_class: Type[Any] = Timer) -> None:
        self._logger = logging.getLogger(f"{type(self).__name__}_{id(self)}")
        self._fn = fn
        self._schedule = schedule
        self._running = True

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Function get_cardinality_estimate has a Cognitive Complexity of 7 (exceeds 5 allowed). Consider refactoring.

Open

def get_cardinality_estimate(column_profile: ColumnProfileView) -> CardinalityEstimate:
    cardinality = column_profile.get_metric("cardinality")
    counts = column_profile.get_metric("counts")
    est_value: Optional[float] = None
    est_ratio: Optional[float] = None

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Function to_summary_dict has a Cognitive Complexity of 7 (exceeds 5 allowed). Consider refactoring.

Open

    def to_summary_dict(self, cfg: Optional[SummaryConfig] = None) -> Dict[str, Any]:
        cfg = cfg or SummaryConfig()
        summary = {}
        for sub_name, metrics in self.submetrics.items():
            for namespace, metric in metrics.items():

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Function merge_submetrics has a Cognitive Complexity of 7 (exceeds 5 allowed). Consider refactoring.

Open

    def merge_submetrics(self: MULTI_METRIC, other: MULTI_METRIC) -> Dict[str, Dict[str, Metric]]:
        if self.namespace != other.namespace:
            raise ValueError(f"Attempt to merge MultiMetrics {self.namespace} and {other.namespace}")

        submetric_names = set(self.submetrics.keys())

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Function to_protobuf has a Cognitive Complexity of 7 (exceeds 5 allowed). Consider refactoring.

Open

    def to_protobuf(
        self,
    ) -> ModelProfileMessage:
        model_type = ModelType.UNKNOWN
        if not self.model_type:

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Function _do_match has a Cognitive Complexity of 7 (exceeds 5 allowed). Consider refactoring.

Open

    def _do_match(cls, dtype_or_type: Any, maybe_type: Optional[Any]) -> bool:
        # Pandas Categorical is Strings
        if CategoricalDtype is not None and isinstance(dtype_or_type, CategoricalDtype):
            return True

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Avoid too many return statements within this function.

Open

            return GCSWriter(**kwargs)  # type: ignore

Avoid too many return statements within this method.

Open

      return MetricComponentMessage.newBuilder().setD((float) value).build();

Avoid too many return statements within this method.

Open

      return (T) result;