Compliance
Compliance(dataset, predicate, column_list=None, filter_condition_dict=None, dataset_filter_by_data_type=None, duckdb_connection=None, decimal_places=2)
¶
Calculate compliance metrics for a dataset using DuckDB.
This function measures the fraction of rows that comply with the given predicate. It supports filtering by column names and/or data types, and can apply additional filter conditions before calculating compliance. Window functions and subqueries are not supported in predicates.
Example
Given a predicate "age >= 18" on a dataset with ages [15, 20, 25, 16, 30]:
Compliance calculation: - Compliant rows: 3 (20, 25, 30) - Total rows: 5 - Compliance percentage = (3/5) * 100 = 60.00%
Forbidden Predicate Examples
The following predicates are not allowed and will raise ValueError: - Window functions: "COUNT(*) OVER (PARTITION BY user_id) = 1" - Subqueries: "salary > (SELECT AVG(salary) FROM table)" - Rank functions: "RANK() OVER (ORDER BY salary) = 1" - EXISTS clauses: "EXISTS (SELECT 1 FROM table WHERE id = user_id)"
Returns:
Type | Description |
---|---|
List[Dict[str, Union[str, int, float, dict, None]]]
|
List[Dict[str, Union[str, int, float, dict, None]]]: A list with one dictionary containing: - predicate (str): The compliance predicate used - compliant_count (int): Count of rows meeting the predicate - total_count (int): Total count of rows - compliance_percentage (float): Percentage of compliant rows - table_name (str): Name of the analyzed table - execution_timestamp_utc (str): Timestamp of execution in UTC - filter_conditions (dict|None): Applied filter conditions if any - filtered_by_data_type (list|None): Data types used for filtering if any |
Parameters:
Name | Type | Description | Default |
---|---|---|---|
dataset
|
Any
|
Input dataset that can be either: - A DataFrame (pandas, polars) or other DuckDB-compatible data structure - A string representing an existing table name in the DuckDB connection |
required |
predicate
|
str
|
SQL predicate to evaluate compliance (e.g., "age >= 18"). Must not contain window functions or subqueries. |
required |
column_list
|
Optional[List[str]]
|
List of columns used in the predicate. Required for validation but not for calculation. Defaults to None. |
None
|
filter_condition_dict
|
Optional[Dict[str, Union[str, int, float]]]
|
Dictionary of filter conditions to apply before calculating compliance. Format: {'column_name': value}. Supports string, integer, and float values. |
None
|
dataset_filter_by_data_type
|
Optional[List[str]]
|
Data type(s) to filter columns. Can be used together with column_list. |
None
|
duckdb_connection
|
Optional[DuckDBPyConnection]
|
Existing DuckDB connection. If None, a new connection will be created and closed after execution. |
None
|
decimal_places
|
int
|
Number of decimal places to round the compliance percentage. Defaults to 2. |
2
|
Raises:
Type | Description |
---|---|
ValueError
|
If the predicate contains window functions or subqueries, or if any of the input parameters are invalid. |
Source code in src/whistlingduck/analyzers/Compliance.py
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