airflow.operators.check_operator
¶
Module Contents¶
-
class
airflow.operators.check_operator.
CheckOperator
(sql, conn_id=None, *args, **kwargs)[source]¶ Bases:
airflow.models.BaseOperator
Performs checks against a db. The
CheckOperator
expects a sql query that will return a single row. Each value on that first row is evaluated using pythonbool
casting. If any of the values returnFalse
the check is failed and errors out.Note that Python bool casting evals the following as
False
:False
0
Empty string (
""
)Empty list (
[]
)Empty dictionary or set (
{}
)
Given a query like
SELECT COUNT(*) FROM foo
, it will fail only if the count== 0
. You can craft much more complex query that could, for instance, check that the table has the same number of rows as the source table upstream, or that the count of today’s partition is greater than yesterday’s partition, or that a set of metrics are less than 3 standard deviation for the 7 day average.This operator can be used as a data quality check in your pipeline, and depending on where you put it in your DAG, you have the choice to stop the critical path, preventing from publishing dubious data, or on the side and receive email alerts without stopping the progress of the DAG.
Note that this is an abstract class and get_db_hook needs to be defined. Whereas a get_db_hook is hook that gets a single record from an external source.
- Parameters
sql (str) – the sql to be executed. (templated)
-
airflow.operators.check_operator.
_convert_to_float_if_possible
(s)[source]¶ -
A small helper function to convert a string to a numeric value
-
if appropriate
- Parameters
s (str) – the string to be converted
-
class
airflow.operators.check_operator.
ValueCheckOperator
(sql, pass_value, tolerance=None, conn_id=None, *args, **kwargs)[source]¶ Bases:
airflow.models.BaseOperator
Performs a simple value check using sql code.
Note that this is an abstract class and get_db_hook needs to be defined. Whereas a get_db_hook is hook that gets a single record from an external source.
- Parameters
sql (str) – the sql to be executed. (templated)
-
class
airflow.operators.check_operator.
IntervalCheckOperator
(table, metrics_thresholds, date_filter_column='ds', days_back=- 7, ratio_formula='max_over_min', ignore_zero=True, conn_id=None, *args, **kwargs)[source]¶ Bases:
airflow.models.BaseOperator
Checks that the values of metrics given as SQL expressions are within a certain tolerance of the ones from days_back before.
Note that this is an abstract class and get_db_hook needs to be defined. Whereas a get_db_hook is hook that gets a single record from an external source.
- Parameters
table (str) – the table name
days_back (int) – number of days between ds and the ds we want to check against. Defaults to 7 days
ratio_formula (str) –
which formula to use to compute the ratio between the two metrics. Assuming cur is the metric of today and ref is the metric to today - days_back.
max_over_min: computes max(cur, ref) / min(cur, ref) relative_diff: computes abs(cur-ref) / ref
Default: ‘max_over_min’
ignore_zero (bool) – whether we should ignore zero metrics
metrics_threshold (dict) – a dictionary of ratios indexed by metrics
-
class
airflow.operators.check_operator.
ThresholdCheckOperator
(sql, min_threshold, max_threshold, conn_id=None, *args, **kwargs)[source]¶ Bases:
airflow.models.BaseOperator
Performs a value check using sql code against a mininmum threshold and a maximum threshold. Thresholds can be in the form of a numeric value OR a sql statement that results a numeric.
Note that this is an abstract class and get_db_hook needs to be defined. Whereas a get_db_hook is hook that gets a single record from an external source.
- Parameters