Functions¶

flowtask.events.events.alerts.functions ¶

average ¶

average(data, column, threshold, deviation, allow_below=False)

average.

Calculates the average of a value compared with a threshold. Args: data (dict): extract column from data. column (str): column to calculate. threshold (float): value to be used for threshold deviation (float): max deviation acceptable for threshold allow_below (bool): if True, the threshold is not evaluated on minimum values.

between ¶

between(data, column, value)

Checks if the actual value in the specified column is between two given values.

Parameters:

Name	Type	Description	Default
`data`	`dict`	Dictionary containing the column data.	required
`column`	`str`	Column name to evaluate.	required
`value`	`list`	A list containing two values: [min_value, max_value].	required

Returns:

Name	Type	Description
`tuple`	`Tuple[str, Union[int, float], bool]`	(column, actual_value, True/False)

equal ¶

equal(data, column, value)

Check if the actual value on a specified column in the data is equal to the given threshold value.

gt ¶

gt(data, column, value)

Check if the actual value on a specified column in the data is greater than to the given threshold value.

has_columns ¶

has_columns(data, column='columns', value=[])

Check if the actual value on a specified column in the data is equal to the given threshold value.

lt ¶

lt(data, column, value)

Check if the actual value on a specified column in the data is less than to the given threshold value.

max_value ¶

max_value(data, column, value)

Checks if the actual value of a specified column in the data is less than or equal to the given threshold value.

Parameters:

Name	Type	Description	Default
`data`	`dict`	Dictionary containing the data to be checked.	required
`column`	`str`	Name of the column in the data whose value needs to be checked.	required
`value`	`Union[int, float]`	The threshold value. The actual value in the data	required

Returns:

Name	Type	Description
`tuple`	`Tuple[str, Union[int, float], bool]`	A tuple containing: - column (str): Name of the column that was checked. - actual_value (Union[int, float]): The actual value from the data for the specified column. - val (bool): True if the actual value is less than or equal to the threshold, False otherwise.

min_value ¶

min_value(data, column, value)

Checks if the actual value of a specified column in the data is greater than or equal to the given threshold value.

Parameters:

Name	Type	Description	Default
`data`	`dict`	Dictionary containing the data to be checked.	required
`column`	`str`	Name of the column in the data whose value needs to be checked.	required
`value`	`Union[int, float]`	The threshold value. The actual value in the data should be greater than or equal to this.	required

Returns:

Name	Type	Description
`tuple`	`Tuple[str, Union[int, float], bool]`	A tuple containing: - column (str): Name of the column that was checked. - actual_value (Union[int, float]): The actual value from the data for the specified column. - val (bool): True if the actual value is greater than or equal to the threshold, False otherwise.

missing_columns ¶

missing_columns(data, column='columns', value=[])

Check if all required columns exist in the 'columns' field of the given data.

:param data: Dictionary containing the structure with "columns". :param column: Name of the column to check (by default: "columns"). :param value: List of columns to check. :return: Tuple (checked_key, missing_columns, bool)