Mean
MaxLength(dataset, column_list=None, filter_condition_dict=None, dataset_filter_by_data_type=None, duckdb_connection=None, null_behavior=NullBehavior.IGNORE)
¶
Calculate maximum string length for specified columns using DuckDB.
This function analyzes the length of string values in specified columns by calculating the maximum length of each string. It can filter columns by explicitly provided column names AND/OR by data type(s). The function only processes string-type columns (VARCHAR, STRING, TEXT, CHAR, CHARACTER VARYING) and provides different behaviors for handling NULL values.
Example
Consider a column 'products' with values: ["apple", "banana", "", "orange juice", None]
Maximum length calculation with different null_behavior: - IGNORE: Ignores NULL values, returns max length 11 (from "orange juice") - EMPTY_STRING: Treats NULL as empty string (length 0), returns max length 11 - FAIL: Raises an error due to NULL value presence
Returns:
Type | Description |
---|---|
List[Dict[str, Union[str, int, float, dict, None]]]
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List[Dict[str, Union[str, int, float, dict, None]]]: A list of dictionaries with the following keys: - column_name (str): Name of the analyzed column - max_length (int): Maximum string length found in the column - 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 - null_behavior (str): The null handling strategy used ('ignore', 'empty_string', or 'fail') |
Parameters:
Name | Type | Description | Default |
---|---|---|---|
dataset
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Any
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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 When providing a DataFrame along with duckdb_connection, the DataFrame will be registered as a temporary table in that connection. |
required |
column_list
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Optional[List[str]]
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List of column names to analyze. Can be used together with dataset_filter_by_data_type. Only string-type columns from this list will be processed. Defaults to None. |
None
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filter_condition_dict
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Optional[Dict[str, Union[str, int, float]]]
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Dictionary of filter conditions to apply before calculating string lengths. Format: {'column_name': value}. Supports string, integer, and float values. Example: {'category': 'electronics', 'status': 'active'}. Defaults to None. |
None
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dataset_filter_by_data_type
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Optional[List[str]]
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Data type(s) to filter columns. Can be a single type as string or list of types. Can be used together with column_list. The function will analyze all string-type columns that match these data types. Case-insensitive. Defaults to None. Example: ['VARCHAR'] or ['VARCHAR', 'TEXT'] |
None
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duckdb_connection
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Optional[DuckDBPyConnection]
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Existing DuckDB connection. If None, a new connection will be created and closed after execution. Can be used with either a table name string or a DataFrame input. Defaults to None. |
None
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null_behavior
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NullBehavior
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Specifies how NULL values should be handled: - IGNORE: Skip NULL values when calculating maximum length - EMPTY_STRING: Treat NULL values as empty strings (length 0) - FAIL: Raise an error if any NULL values are found Defaults to NullBehavior.IGNORE. |
IGNORE
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Raises:
Type | Description |
---|---|
ValueError
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In the following cases: - Neither column_list nor dataset_filter_by_data_type is provided - Invalid column names in column_list or filter_condition_dict - No columns match the specified data types - NULL values found when null_behavior is set to FAIL - Failed to register or access the dataset |
Source code in src/whistlingduck/analyzers/MaxLength.py
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