## get_validation_summary()


Access validation summary information when authoring final actions.


Usage

``` python
get_validation_summary()
```


This function provides a convenient way to access summary information about the validation process within a final action. It returns a dictionary with key metrics from the validation process. This function can only be used within callables crafted for the <a href="FinalActions.html#pointblank.FinalActions" class="gdls-link"><code>FinalActions</code></a> class.


## Returns


`dict | None`  
A dictionary containing validation metrics. If called outside of an final action context, this function will return `None`.


## Description Of The Summary Fields

The summary dictionary contains the following fields:

- `n_steps` (`int`): The total number of validation steps.
- `n_passing_steps` (`int`): The number of validation steps where all test units passed.
- `n_failing_steps` (`int`): The number of validation steps that had some failing test units.
- `n_warning_steps` (`int`): The number of steps that exceeded a 'warning' threshold.
- `n_error_steps` (`int`): The number of steps that exceeded an 'error' threshold.
- `n_critical_steps` (`int`): The number of steps that exceeded a 'critical' threshold.
- `list_passing_steps` (`list[int]`): List of step numbers where all test units passed.
- `list_failing_steps` (`list[int]`): List of step numbers for steps having failing test units.
- `dict_n` (`dict`): The number of test units for each validation step.
- `dict_n_passed` (`dict`): The number of test units that passed for each validation step.
- `dict_n_failed` (`dict`): The number of test units that failed for each validation step.
- `dict_f_passed` (`dict`): The fraction of test units that passed for each validation step.
- `dict_f_failed` (`dict`): The fraction of test units that failed for each validation step.
- `dict_warning` (`dict`): The 'warning' level status for each validation step.
- `dict_error` (`dict`): The 'error' level status for each validation step.
- `dict_critical` (`dict`): The 'critical' level status for each validation step.
- [all_passed](Validate.all_passed.md#pointblank.Validate.all_passed) (`bool`): Whether or not every validation step had no failing test units.
- `highest_severity` (`str`): The highest severity level encountered during validation. This can be one of the following: `"warning"`, `"error"`, or `"critical"`, `"some failing"`, or `"all passed"`.
- `tbl_row_count` (`int`): The number of rows in the target table.
- `tbl_column_count` (`int`): The number of columns in the target table.
- `tbl_name` (`str`): The name of the target table.
- `validation_duration` (`float`): The duration of the validation in seconds.
- `dimension_scores` (`dict`): The test-unit-weighted health score (`0`-`100`) for each data quality dimension present in the validation (e.g., `{"completeness": 99.2, "validity": 97.8}`).
- `overall_health_score` (`float`): The overall, test-unit-weighted health score (`0`-`100`) across all dimensions.

Note that the summary dictionary is only available within the context of a final action. If called outside of a final action (i.e., when no final action is being executed), this function will return `None`.


## Examples

Final actions are executed after the completion of all validation steps. They provide an opportunity to take appropriate actions based on the overall validation results. Here's an example of a final action function (`send_report()`) that sends an alert when critical validation failures are detected:

``` python
import pointblank as pb

def send_report():
    summary = pb.get_validation_summary()
    if summary["highest_severity"] == "critical":
        # Send an alert email
        send_alert_email(
            subject=f"CRITICAL validation failures in {summary['tbl_name']}",
            body=f"{summary['n_critical_steps']} steps failed with critical severity."
        )

validation = (
    pb.Validate(
        data=my_data,
        final_actions=pb.FinalActions(send_report)
    )
    .col_vals_gt(columns="revenue", value=0)
    .interrogate()
)
```

Note that `send_alert_email()` in the example above is a placeholder function that would be implemented by the user to send email alerts. This function is not provided by the Pointblank package.

The [get_validation_summary()](get_validation_summary.md#pointblank.get_validation_summary) function can also be used to create custom reporting for validation results:

``` python
def log_validation_results():
    summary = pb.get_validation_summary()

    print(f"Validation completed with status: {summary['highest_severity'].upper()}")
    print(f"Steps: {summary['n_steps']} total")
    print(f"  - {summary['n_passing_steps']} passing, {summary['n_failing_steps']} failing")
    print(
        f"  - Severity: {summary['n_warning_steps']} warnings, "
        f"{summary['n_error_steps']} errors, "
        f"{summary['n_critical_steps']} critical"
    )

    if summary['highest_severity'] in ["error", "critical"]:
        print("⚠️ Action required: Please review failing validation steps!")
```

Final actions work well with both simple logging and more complex notification systems, allowing you to integrate validation results into your broader data quality workflows.


#### See Also

[Have](Have.md), [custom](custom.md)