CONTRIBUTING.md

Adding new functions/tests

Interface

• All user exposed quality checks and processing algorithms need to implement the following interface:

  der yourTestFunction(
      data: pandas.DataFrame,
      field: str,
      flagger: saqc.flagger.BaseFlagger,
      *args: Any,
      **kwargs: Any
      ) -> (pd.DataFrame, saqc.flagger.BaseFlagger)

Argument Descriptions

Name	Description
data	The actual dataset
field	The field/column within data, the function is checking/processing
flagger	A instance of a flagger, responsible for the translation of test results into quality attributes
args	Any other arguments needed to parametrize the function
kwargs	Any other keyword arguments needed tp parametrize the function

Integrate into SaQC

In order make your function available to the system it needs to be registered. We provide the decorator register in the module saqc.functions.register, to integrate your test functions into SaQC and expose them via a name of your choice. A complete, yet useless example might look like that:

@register("myFunc")
def yourTestFunction(data, field, flagger, *args, **kwargs):
    return data, flagger

Example

The function flagRange provides a simple, yet complete implementation of the entire test function contribution process. You might want to look into this implementation before you start.

Adding a new flagger

TODO

Testing

SaQC comes with an extensive test suite based on pytest. In order to run all tests use:

python -m pytest .

Coding conventions

Naming

Code

We follow the follwing naming conventions

• Classes: CamelCase
• Functions: camelCase
• Variables/Arguments: snake_case

Test Functions

• testnames: testModule_testName

Formatting

We use (black)[https://black.readthedocs.io/en/stable/]

Imports

Only absolute imports are accepted