Skip to content

Latest commit

 

History

History
179 lines (137 loc) · 5.82 KB

programmatic.md

File metadata and controls

179 lines (137 loc) · 5.82 KB
Raw

Define programmatic scans using Python

To automate the search for bad-quality data, you can use the Soda Core Python library to programmatically execute scans.

Alternatively, you can install and use the Soda Core CLI to run scans; see Install Soda Core.

Based on a set of conditions or a specific event schedule, you can instruct Soda Core to automatically scan a data source. For example, you may wish to scan your data at several points along your data pipeline, perhaps when new data enters a data source, after it is transformed, and before it is exported to another data source.

Basic programmatic scan
Tips and best practices
Scan exit codes
Configure a failed row sampler
Save failed row samples to an alternate destination

Basic programmatic scan

from soda.scan import Scan

scan = Scan()
scan.set_data_source_name("events")

# Add configuration YAML files
#########################
# Choose one of the following to specify data source connection configurations :
# 1) From a file
scan.add_configuration_yaml_file(file_path="~/.soda/my_local_soda_environment.yml")
# 2) Inline in the code
scan.add_configuration_yaml_str(
    """
    data_source events:
      type: snowflake
      connection:
      host: ${SNOWFLAKE_HOST}
      username: ${SNOWFLAKE_USERNAME}
      password: ${SNOWFLAKE_PASSWORD}
      database: events
      schema: public
"""
)

# Add variables
###############
scan.add_variables({"date": "2022-01-01"})


# Add check YAML files
##################
scan.add_sodacl_yaml_file("./my_programmatic_test_scan/sodacl_file_one.yml")
scan.add_sodacl_yaml_file("./my_programmatic_test_scan/sodacl_file_two.yml")
scan.add_sodacl_yaml_files("./my_scan_dir")
scan.add_sodacl_yaml_files("./my_scan_dir/sodacl_file_three.yml")


# Execute the scan
##################
scan.execute()

# Set logs to verbose mode, equivalent to CLI -V option
##################
scan.set_verbose(True)

# Set scan definition name, equivalent to CLI -s option;
# see Tips and best practices below
##################
scan.set_scan_definition_name("YOUR_SCHEDULE_NAME")


# Inspect the scan result
#########################
scan.get_scan_results()

# Inspect the scan logs
#######################
scan.get_logs_text()

# Typical log inspection
##################
scan.assert_no_error_logs()
scan.assert_no_checks_fail()

# Advanced methods to inspect scan execution logs
#################################################
scan.has_error_logs()
scan.get_error_logs_text()

# Advanced methods to review check results details
########################################
scan.get_checks_fail()
scan.has_check_fails()
scan.get_checks_fail_text()
scan.assert_no_checks_warn_or_fail()
scan.get_checks_warn_or_fail()
scan.has_checks_warn_or_fail()
scan.get_checks_warn_or_fail_text()
scan.get_all_checks_text()

Tips and best practices

  • You can save Soda Core scan results anywhere in your system; the scan_result object contains all the scan result information. To import the Soda Core library in Python so you can utilize the Scan() object, install a Soda Core package, then use from soda.scan import Scan.
  • Be sure to include any variables in your programmatic scan before the check YAML files. Soda requires the variable input for any variables defined in the check YAML files.

Scan exit codes

Soda Core's scan output includes an exit code which indicates the outcome of the scan.

Exit code Description
0 all checks passed, all good from both runtime and Soda perspective
1 Soda issues a warning on a check(s)
2 Soda issues a failure on a check(s)
3 Soda encountered a runtime issue

To obtain the exit code, you can add the following to your programmatic scan.

exit_code = scan.execute()
print(exit_code)

Configure a failed row sampler

Optionally, you can add a custom sampler to collect samples of rows with a fail check result. Refer to the following example that prints the failed row samples in the CLI.

from soda.scan import Scan
from soda.sampler.sampler import Sampler
from soda.sampler.sample_context import SampleContext


# Create a custom sampler by extending the Sampler class
class CustomSampler(Sampler):
    def store_sample(self, sample_context: SampleContext):
        # Retrieve the rows from the sample for a check
        rows = sample_context.sample.get_rows()
        # Check SampleContext for more details that you can extract
        # This example simply prints the failed row samples
        print(sample_context.query)
        print(sample_context.sample.get_schema())
        print(rows)


if __name__ == '__main__':
    # Create Scan object
    s = Scan()
    # Configure an instance of custom sampler
    s.sampler = CustomSampler()

    s.set_scan_definition_name("test_scan")
    s.set_data_source_name("aa_vk")
    s.add_configuration_yaml_str(f"""
    data_source test:
      type: postgres
      schema: public
      connection:
        host: localhost
        port: 5433
        username: ***
        password: ***
        database: postgres
    """)

    s.add_sodacl_yaml_str(f"""
    checks for dim_account:
        - invalid_percent(account_type) = 0:
            valid format: email

    """)
    s.execute()
    print(s.get_logs_text())

Save failed row samples to an alternate destination

If you prefer to send the output of the failed row sampler to an independent tool, you can do so by customizing the sampler as above, then using the Python API to save the rows to a JSON file. Refer to docs.python.org for details.