nbcelltests


Namenbcelltests JSON
Version 0.3.2 PyPI version JSON
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SummaryCell-by-cell tests for JupyterLab
upload_time2024-06-05 23:57:37
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authorNone
requires_python>=3.8
licenseApache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. Definitions. "License" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document. "Licensor" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License. "Legal Entity" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, "control" means (i) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (ii) ownership of fifty percent (50%) or more of the outstanding shares, or (iii) beneficial ownership of such entity. "You" (or "Your") shall mean an individual or Legal Entity exercising permissions granted by this License. "Source" form shall mean the preferred form for making modifications, including but not limited to software source code, documentation source, and configuration files. "Object" form shall mean any form resulting from mechanical transformation or translation of a Source form, including but not limited to compiled object code, generated documentation, and conversions to other media types. "Work" shall mean the work of authorship, whether in Source or Object form, made available under the License, as indicated by a copyright notice that is included in or attached to the work (an example is provided in the Appendix below). "Derivative Works" shall mean any work, whether in Source or Object form, that is based on (or derived from) the Work and for which the editorial revisions, annotations, elaborations, or other modifications represent, as a whole, an original work of authorship. For the purposes of this License, Derivative Works shall not include works that remain separable from, or merely link (or bind by name) to the interfaces of, the Work and Derivative Works thereof. "Contribution" shall mean any work of authorship, including the original version of the Work and any modifications or additions to that Work or Derivative Works thereof, that is intentionally submitted to Licensor for inclusion in the Work by the copyright owner or by an individual or Legal Entity authorized to submit on behalf of the copyright owner. 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Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license to reproduce, prepare Derivative Works of, publicly display, publicly perform, sublicense, and distribute the Work and such Derivative Works in Source or Object form. 3. Grant of Patent License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable (except as stated in this section) patent license to make, have made, use, offer to sell, sell, import, and otherwise transfer the Work, where such license applies only to those patent claims licensable by such Contributor that are necessarily infringed by their Contribution(s) alone or by combination of their Contribution(s) with the Work to which such Contribution(s) was submitted. If You institute patent litigation against any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Work or a Contribution incorporated within the Work constitutes direct or contributory patent infringement, then any patent licenses granted to You under this License for that Work shall terminate as of the date such litigation is filed. 4. Redistribution. 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keywords celltests jupyter jupyterlab notebook notebooks testing tests
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Cell-by-cell testing for production Jupyter notebooks in JupyterLab

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# Overview
`nbcelltests` is designed for writing tests for linearly executed notebooks. Its primary use is for unit testing reports.

## Installation
Python package installation: `pip install nbcelltests`

To use in JupyterLab, you will also need the lab and server extensions. Typically, these are
automatically installed alongside nbcelltests, so you should not need to do anything special
to use them. The lab extension will require a rebuild of JupyterLab, which you'll be prompted
to do on starting JupyterLab the first time after installing celltests (or you can do manually
with `jupyter lab build`). Note that you must have node.js installed (as for any lab extension).

To see what extensions you have, check the output of `jupyter labextension list` (look for
`nbcelltests`), and `jupyter serverextension list` (look for `nbcelltests`).
If for some reason you need to manually install the extensions, you can do so as follows:

```bash
jupyter labextension install nbcelltests
jupyter serverextension enable --py nbcelltests
```

(Note: if using in an environment, you might wish to add `--sys-prefix` to the `serverextension` command.)

## "Linearly executed notebooks?"
When converting notebooks into html/pdf/email reports, they are executed top-to-bottom one time, and are expected to contain as little code as reasonably possible, focusing primarily on the plotting and markdown bits. Libraries for this type of thing include [Papermill](https://github.com/nteract/papermill), [JupyterLab Emails](https://github.com/timkpaine/jupyterlab_email), etc.

## Doesn't this already exist?
[Nbval](https://github.com/computationalmodelling/nbval) is a great product (we leverage it in this project) and I recommend using it for notebook regression tests. But it only allows for testing for unexpected failures or simple output equality tests.

## So why do I want this again?
This doesn't necessarily help you if your data sources go down, but its likely you'll notice this anyway. Where this comes in handy is:

- when the environment (e.g. package versions) are changing in your system
- when you play around in the notebook (e.g. nonlinear execution) but aren't sure if your reports will still generate
- when your software lifecycle systems have a hard time dealing with notebooks (can't lint/audit them as code unless integrated nbdime/nbconvert to script, tough to test, tough to ensure what works today works tomorrow)

## So what does this do?
Given a notebook, you can write mocks and assertions for individual cells. You can then generate a testing script for this notebook, allowing you to hook it into your testing system and thereby provide unittests of your report.

## Writing tests
When you write tests for a cell, we create a new method on a `unittest` class corresponding to the index of your cell, and including the cumulative tests for all previous cells (to mimic what has happened so far in the notebook's linear execution). You can write whatever mocking and asserts you like, and can call `%cell` to inject the contents of the cell into your test.
![](https://raw.githubusercontent.com/timkpaine/nbcelltests/main/docs/demo.gif)
The tests themselves are stored in the cell metadata, similar to celltags, slide information, etc.

## Running tests
You can run the tests offline from an `.ipynb` file, or you can execute them from the browser and view the results of `pytest-html`'s html plugin.
![](https://raw.githubusercontent.com/timkpaine/nbcelltests/main/docs/demo2.gif)

## Extra Tests
- Max number of lines per cell
- Max number of cells per notebook
- Max number of function definitions per notebook
- Max number of class definitions per notebook
- Percentage of cells tested

## Example
In the committed `examples/Example.ipynb` notebook, but modified so that cell 0 has its import statement copied 10 times (to trigger test and lint failures):


### Tests
The following output is generated by running `nbcelltests test examples/Example.ipynb`
```bash
examples/_Example_test.py::TestNotebook::test_cell_coverage PASSED                                                                               [ 20%]
examples/_Example_test.py::TestNotebook::test_code_cell_1 PASSED                                                                                 [ 40%]
examples/_Example_test.py::TestNotebook::test_code_cell_2 PASSED                                                                                 [ 60%]
examples/_Example_test.py::TestNotebook::test_code_cell_3 PASSED                                                                                 [ 80%]
examples/_Example_test.py::TestNotebook::test_code_cell_4 PASSED                                                                                 [100%]
```
### Lint
The following output is generated by running `nbcelltests lint examples/Example.ipynb`

```bash
PASSED: Checking lines in cell (max=10; actual=2) (Cell 1)
PASSED: Checking lines in cell (max=10; actual=1) (Cell 2)
PASSED: Checking lines in cell (max=10; actual=1) (Cell 3)
PASSED: Checking lines in cell (max=10; actual=1) (Cell 4)
PASSED: Checking cells per notebook (max=10; actual=4)
PASSED: Checking functions per notebook (max=10; actual=0)
PASSED: Checking classes per notebook (max=10; actual=0)
FAILED: Checking lint:
	examples/Example.ipynb (in /var/folders/s3/1mjw0y192zg3450tkkn1yfnm0000gn/T/tmpp91li59p.py):32:1: F821 undefined name 'test3'
	examples/Example.ipynb (in /var/folders/s3/1mjw0y192zg3450tkkn1yfnm0000gn/T/tmpp91li59p.py):32:6: W291 trailing whitespace
```

NB: In jupyterlab, notebooks will be lint checked in-process using the version of
python that is running jupyter lab itself. A notebook intended to be
run with a Python 2 kernel could therefore generate syntax errors
during lint checking.

## Development

See [CONTRIBUTING.md](https://github.com/jpmorganchase/nbcelltests/blob/main/CONTRIBUTING.md) for guidelines.


## License

This software is licensed under the Apache 2.0 license. See the
[LICENSE](https://github.com/jpmorganchase/nbcelltests/blob/main/LICENSE) and [AUTHORS](https://github.com/jpmorganchase/nbcelltests/blob/main/AUTHORS) files for details.

            

Raw data

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    "keywords": "Celltests, Jupyter, JupyterLab, Notebook, Notebooks, Testing, Tests",
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    "author_email": "The nbcelltests authors <t.paine154@gmail.com>",
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    "description": "<img src=\"https://raw.githubusercontent.com/jpmorganchase/nbcelltests/main/docs/logo.png\" width=400></img>\n\n\nCell-by-cell testing for production Jupyter notebooks in JupyterLab\n\n[![Build Status](https://github.com/jpmorganchase/nbcelltests/actions/workflows/build.yml/badge.svg?branch=main)](https://github.com/jpmorganchase/nbcelltests/actions?query=workflow%3A%22Build+Status%22)\n[![codecov](https://codecov.io/gh/jpmorganchase/nbcelltests/branch/main/graph/badge.svg)](https://codecov.io/gh/jpmorganchase/nbcelltests)\n[![PyPI](https://img.shields.io/pypi/l/nbcelltests.svg)](https://pypi.python.org/pypi/nbcelltests)\n[![PyPI](https://img.shields.io/pypi/v/nbcelltests.svg)](https://pypi.python.org/pypi/nbcelltests)\n[![npm](https://img.shields.io/npm/v/nbcelltests.svg)](https://www.npmjs.com/package/nbcelltests)\n\n\n# Overview\n`nbcelltests` is designed for writing tests for linearly executed notebooks. Its primary use is for unit testing reports.\n\n## Installation\nPython package installation: `pip install nbcelltests`\n\nTo use in JupyterLab, you will also need the lab and server extensions. Typically, these are\nautomatically installed alongside nbcelltests, so you should not need to do anything special\nto use them. The lab extension will require a rebuild of JupyterLab, which you'll be prompted\nto do on starting JupyterLab the first time after installing celltests (or you can do manually\nwith `jupyter lab build`). Note that you must have node.js installed (as for any lab extension).\n\nTo see what extensions you have, check the output of `jupyter labextension list` (look for\n`nbcelltests`), and `jupyter serverextension list` (look for `nbcelltests`).\nIf for some reason you need to manually install the extensions, you can do so as follows:\n\n```bash\njupyter labextension install nbcelltests\njupyter serverextension enable --py nbcelltests\n```\n\n(Note: if using in an environment, you might wish to add `--sys-prefix` to the `serverextension` command.)\n\n## \"Linearly executed notebooks?\"\nWhen converting notebooks into html/pdf/email reports, they are executed top-to-bottom one time, and are expected to contain as little code as reasonably possible, focusing primarily on the plotting and markdown bits. Libraries for this type of thing include [Papermill](https://github.com/nteract/papermill), [JupyterLab Emails](https://github.com/timkpaine/jupyterlab_email), etc.\n\n## Doesn't this already exist?\n[Nbval](https://github.com/computationalmodelling/nbval) is a great product (we leverage it in this project) and I recommend using it for notebook regression tests. But it only allows for testing for unexpected failures or simple output equality tests.\n\n## So why do I want this again?\nThis doesn't necessarily help you if your data sources go down, but its likely you'll notice this anyway. Where this comes in handy is:\n\n- when the environment (e.g. package versions) are changing in your system\n- when you play around in the notebook (e.g. nonlinear execution) but aren't sure if your reports will still generate\n- when your software lifecycle systems have a hard time dealing with notebooks (can't lint/audit them as code unless integrated nbdime/nbconvert to script, tough to test, tough to ensure what works today works tomorrow)\n\n## So what does this do?\nGiven a notebook, you can write mocks and assertions for individual cells. You can then generate a testing script for this notebook, allowing you to hook it into your testing system and thereby provide unittests of your report.\n\n## Writing tests\nWhen you write tests for a cell, we create a new method on a `unittest` class corresponding to the index of your cell, and including the cumulative tests for all previous cells (to mimic what has happened so far in the notebook's linear execution). You can write whatever mocking and asserts you like, and can call `%cell` to inject the contents of the cell into your test.\n![](https://raw.githubusercontent.com/timkpaine/nbcelltests/main/docs/demo.gif)\nThe tests themselves are stored in the cell metadata, similar to celltags, slide information, etc.\n\n## Running tests\nYou can run the tests offline from an `.ipynb` file, or you can execute them from the browser and view the results of `pytest-html`'s html plugin.\n![](https://raw.githubusercontent.com/timkpaine/nbcelltests/main/docs/demo2.gif)\n\n## Extra Tests\n- Max number of lines per cell\n- Max number of cells per notebook\n- Max number of function definitions per notebook\n- Max number of class definitions per notebook\n- Percentage of cells tested\n\n## Example\nIn the committed `examples/Example.ipynb` notebook, but modified so that cell 0 has its import statement copied 10 times (to trigger test and lint failures):\n\n\n### Tests\nThe following output is generated by running `nbcelltests test examples/Example.ipynb`\n```bash\nexamples/_Example_test.py::TestNotebook::test_cell_coverage PASSED                                                                               [ 20%]\nexamples/_Example_test.py::TestNotebook::test_code_cell_1 PASSED                                                                                 [ 40%]\nexamples/_Example_test.py::TestNotebook::test_code_cell_2 PASSED                                                                                 [ 60%]\nexamples/_Example_test.py::TestNotebook::test_code_cell_3 PASSED                                                                                 [ 80%]\nexamples/_Example_test.py::TestNotebook::test_code_cell_4 PASSED                                                                                 [100%]\n```\n### Lint\nThe following output is generated by running `nbcelltests lint examples/Example.ipynb`\n\n```bash\nPASSED: Checking lines in cell (max=10; actual=2) (Cell 1)\nPASSED: Checking lines in cell (max=10; actual=1) (Cell 2)\nPASSED: Checking lines in cell (max=10; actual=1) (Cell 3)\nPASSED: Checking lines in cell (max=10; actual=1) (Cell 4)\nPASSED: Checking cells per notebook (max=10; actual=4)\nPASSED: Checking functions per notebook (max=10; actual=0)\nPASSED: Checking classes per notebook (max=10; actual=0)\nFAILED: Checking lint:\n\texamples/Example.ipynb (in /var/folders/s3/1mjw0y192zg3450tkkn1yfnm0000gn/T/tmpp91li59p.py):32:1: F821 undefined name 'test3'\n\texamples/Example.ipynb (in /var/folders/s3/1mjw0y192zg3450tkkn1yfnm0000gn/T/tmpp91li59p.py):32:6: W291 trailing whitespace\n```\n\nNB: In jupyterlab, notebooks will be lint checked in-process using the version of\npython that is running jupyter lab itself. A notebook intended to be\nrun with a Python 2 kernel could therefore generate syntax errors\nduring lint checking.\n\n## Development\n\nSee [CONTRIBUTING.md](https://github.com/jpmorganchase/nbcelltests/blob/main/CONTRIBUTING.md) for guidelines.\n\n\n## License\n\nThis software is licensed under the Apache 2.0 license. See the\n[LICENSE](https://github.com/jpmorganchase/nbcelltests/blob/main/LICENSE) and [AUTHORS](https://github.com/jpmorganchase/nbcelltests/blob/main/AUTHORS) files for details.\n",
    "bugtrack_url": null,
    "license": "Apache License Version 2.0, January 2004 http://www.apache.org/licenses/  TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION  1. Definitions.  \"License\" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document.  \"Licensor\" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License.  \"Legal Entity\" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, \"control\" means (i) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (ii) ownership of fifty percent (50%) or more of the outstanding shares, or (iii) beneficial ownership of such entity.  \"You\" (or \"Your\") shall mean an individual or Legal Entity exercising permissions granted by this License.  \"Source\" form shall mean the preferred form for making modifications, including but not limited to software source code, documentation source, and configuration files.  \"Object\" form shall mean any form resulting from mechanical transformation or translation of a Source form, including but not limited to compiled object code, generated documentation, and conversions to other media types.  \"Work\" shall mean the work of authorship, whether in Source or Object form, made available under the License, as indicated by a copyright notice that is included in or attached to the work (an example is provided in the Appendix below).  \"Derivative Works\" shall mean any work, whether in Source or Object form, that is based on (or derived from) the Work and for which the editorial revisions, annotations, elaborations, or other modifications represent, as a whole, an original work of authorship. For the purposes of this License, Derivative Works shall not include works that remain separable from, or merely link (or bind by name) to the interfaces of, the Work and Derivative Works thereof.  \"Contribution\" shall mean any work of authorship, including the original version of the Work and any modifications or additions to that Work or Derivative Works thereof, that is intentionally submitted to Licensor for inclusion in the Work by the copyright owner or by an individual or Legal Entity authorized to submit on behalf of the copyright owner. For the purposes of this definition, \"submitted\" means any form of electronic, verbal, or written communication sent to the Licensor or its representatives, including but not limited to communication on electronic mailing lists, source code control systems, and issue tracking systems that are managed by, or on behalf of, the Licensor for the purpose of discussing and improving the Work, but excluding communication that is conspicuously marked or otherwise designated in writing by the copyright owner as \"Not a Contribution.\"  \"Contributor\" shall mean Licensor and any individual or Legal Entity on behalf of whom a Contribution has been received by Licensor and subsequently incorporated within the Work.  2. Grant of Copyright License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license to reproduce, prepare Derivative Works of, publicly display, publicly perform, sublicense, and distribute the Work and such Derivative Works in Source or Object form.  3. Grant of Patent License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable (except as stated in this section) patent license to make, have made, use, offer to sell, sell, import, and otherwise transfer the Work, where such license applies only to those patent claims licensable by such Contributor that are necessarily infringed by their Contribution(s) alone or by combination of their Contribution(s) with the Work to which such Contribution(s) was submitted. If You institute patent litigation against any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Work or a Contribution incorporated within the Work constitutes direct or contributory patent infringement, then any patent licenses granted to You under this License for that Work shall terminate as of the date such litigation is filed.  4. Redistribution. You may reproduce and distribute copies of the Work or Derivative Works thereof in any medium, with or without modifications, and in Source or Object form, provided that You meet the following conditions:  (a) You must give any other recipients of the Work or Derivative Works a copy of this License; and  (b) You must cause any modified files to carry prominent notices stating that You changed the files; and  (c) You must retain, in the Source form of any Derivative Works that You distribute, all copyright, patent, trademark, and attribution notices from the Source form of the Work, excluding those notices that do not pertain to any part of the Derivative Works; and  (d) If the Work includes a \"NOTICE\" text file as part of its distribution, then any Derivative Works that You distribute must include a readable copy of the attribution notices contained within such NOTICE file, excluding those notices that do not pertain to any part of the Derivative Works, in at least one of the following places: within a NOTICE text file distributed as part of the Derivative Works; within the Source form or documentation, if provided along with the Derivative Works; or, within a display generated by the Derivative Works, if and wherever such third-party notices normally appear. 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