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Header cleanser

Please see the set of transform project conventions for details on general project conventions, transform configuration, testing and IDE set up.

Summary

This module is designed to detect and remove license and copyright information from code files. It leverages the ScanCode Toolkit to accurately identify and process licenses and copyrights in various programming languages.

After locating the position of license or copyright in the input code/sample, this module delete/remove those lines and returns the updated code as parquet file.

Configuration and command line Options

The set of dictionary keys holding configuration for values are as follows:

  • contents_column_name - used to define input column name. Default value is 'contents'.
  • license - write 'true' to remove license from input data else 'false'. By default set as 'true'.
  • copyright - write 'true' to remove copyright from input data else 'false'. by default set as 'true'.

Running

You can run the header_cleanser_local.py (python-only implementation) or header_cleanser_local_ray.py (ray-based implementation) to transform the test1.parquet file in test input data to an output directory. The directory will contain both the new annotated test1.parquet file and the metadata.json file.

Running

Launched Command Line Options

When running the transform with the Ray launcher (i.e. TransformLauncher), the following command line arguments are available in addition to the python launcher.

  • --header_cleanser_contents_column_name - set the contents_column_name configuration key.
  • --header_cleanser_license - set the license configuration key.
  • --header_cleanser_copyright - set the copyright configuration key.

Running the samples

To run the samples, use the following make targets

  • run-cli-sample - runs src/header_cleanser_transform_python.py using command line args
  • run-local-python-sample - runs src/header_cleanser_local_python.py
  • run-local-sample - runs src/header_cleanser_local.py

These targets will activate the virtual environment and set up any configuration needed. Use the -n option of make to see the detail of what is done to run the sample.

For example,

make run-cli-sample
...

Then

ls output

To see results of the transform.

Transforming data using the transform image

To use the transform image to transform your data, please refer to the running images quickstart, substituting the name of this transform image and runtime as appropriate.