Release Testing Utilities

You can use the John Snow Labs library to automatically test 10000+ models and 100+ Notebooks in 1 line of code within a small machine like a single Google Colab Instance and generate very handy error reports of potentially broken Models, Notebooks or Models hub Markdown Snippets.

You can test the following things with the test_markdown() function :

• A local Models Hub Markdown snippet via path.
• a remote Models Hub Markdown snippet via URL.
• a local folder of Models Hub Markdown files. Generates report
• a list of local paths or urls to .md files. Generates a report

Test-Report Pandas Dataframe has the columns:

Test a Local Models Hub Markdown Snippet

from johnsnowlabs.utils.modelhub_markdown import test_markdown
test_markdown('path/to/my/file.md')

Test a Remote Models Hub Markdown Snippet

from johnsnowlabs.utils.modelhub_markdown import test_markdown
test_markdown('https://nlp.johnsnowlabs.com/2022/08/31/legpipe_deid_en.html')

Test a Folder with Models Hub Markdown Snippets

This will scan the folder for all files ending with .md , test them and generate a report

from johnsnowlabs.utils.modelhub_markdown import test_markdown
test_markdown('my/markdown/folder')

Test a List of Markdown References

Can be mixed with Urls and paths, will generate a report

from johnsnowlabs.utils.notebooks import test_ipynb
md_to_test = ['legpipe_deid_en.html',
  'path/to/local/markdown_snippet.md',]
test_markdown(md_to_test)

Utilities for Testing Notebooks

You can use the John Snow Labs library to automatically test 10000+ models and 100+ Notebooks in 1 line of code within a small machine like a single Google Colab Instance and generate very handy error reports of potentially broken Models, Notebooks or Models hub Markdown Snippets.

You can test the following things with the test_ipynb() function :

• A local .ipynb file
• a remote .ipynb URL, point to RAW githubuser content URL of the file when using git.
• a local folder of ipynb files, generates report
• a list of local paths or urls to .ipynb files. Generates a Report
• The entire John Snow Labs Workshop Certification Folder Generates a Report
• A sub-folder of the John Snow Labs Workshop Certification Folder , i.e. only OCR or only Legal. Generates a Report

The generated Test-Report Pandas Dataframe has the columns:

Test a Local Notebook

from johnsnowlabs.utils.notebooks import test_ipynb
test_ipynb('path/to/local/notebook.ipynb')

Test a Remote Notebook

from johnsnowlabs.utils.notebooks import test_ipynb
test_ipynb('https://raw.githubusercontent.com/JohnSnowLabs/spark-nlp-workshop/master/tutorials/Certification_Trainings/Healthcare/5.Spark_OCR.ipynb',)

Test a Folder with Notebooks

This will scan the folder for all files ending with .ipynb , test them and generate a report

from johnsnowlabs.utils.notebooks import test_ipynb
test_ipynb('my/notebook/folder')

Test a List of Notebook References

Can be mixed with Urls and paths, will generate a report

from johnsnowlabs.utils.notebooks import test_ipynb
nb_to_test = [
  'https://raw.githubusercontent.com/JohnSnowLabs/spark-nlp-workshop/master/tutorials/Certification_Trainings/Healthcare/5.Spark_OCR.ipynb',
  'path/to/local/notebook.ipynb',]
test_ipynb(nb_to_test)

Run All Certification Notebooks

Will generate a report

from johnsnowlabs.utils.notebooks import test_ipynb
test_result = test_ipynb('WORKSHOP')

Run Finance Certification Notebooks only

Will generate a report

from johnsnowlabs.utils.notebooks import test_ipynb
test_result = test_ipynb('WORKSHOP-FIN')

Run Legal notebooks only

Will generate a report

from johnsnowlabs.utils.notebooks import test_ipynb
test_result = test_ipynb('WORKSHOP-LEG')

Run Medical notebooks only

Will generate a report

from johnsnowlabs.utils.notebooks import test_ipynb
test_result = test_ipynb('WORKSHOP-MED')

Run Open Source notebooks only

Will generate a report

from johnsnowlabs.utils.notebooks import test_ipynb
test_result = test_ipynb('WORKSHOP-OS')