Tinydocs
TinyDocs is a lightweight and efficient solution for documenting Python code on Github, without the need for setting up and maintaining a separate website like readthedocs.
Install / Use
/learn @antonio-leitao/TinydocsREADME
Are you in need of a simple and efficient solution for documenting your Python code, without the hassle of setting up and maintaining a full-fledged documentation website like readthedocs? Do you want something that can quickly and easily be integrated into GitHub, allowing your team to quickly access the documentation for a few classes and helper functions? Look no further!
readthedocs automatically generates the documentation of your .py files in a small elegant way that fits in a simple README.md. Check out the example function below or the example directory.
Contents
Installation
Best way to install tinydocs is through pip:
pip install tinydocs
Example
The following is the documentation generated for an example function. You can find how tinydocs handles and entire directory by checking the example directory.
Function
module.function(var1, var2, long_var_name=None, *args)
Warning Deprecation:
functionwill be removed in version 2.0.0, it is replaced bybetter_functionbecause the new one is blazingly fast.
This is an example documentation.
Several sentences providing an extended description. Refer to
variables using back-ticks, e.g. var.
Look at this really big equation that I took from [^1]
$$( \sum_{k=1}^n a_k b_k )^2 \leq ( \sum_{k=1}^n a_k^2 ) ( \sum_{k=1}^n b_k^2 )$$
<details closed><summary> <b>Parameters</b></summary><p/><ul><li><code>var1</code>: array_like<br> Array_like means all those objects -- lists, nested lists, etc. -- that can be converted to an array. We can also refer to variables like `var1`.</li><li><code>var2</code>: int<br> The type above can either refer to an actual Python type (e.g. ``int``), or describe the type of the variable in more detail, e.g. ``(N,) ndarray`` or ``array_like``.</li><li><code>long_var_name</code>: {'hi', 'ho'}, optional<br> Choices in brackets, default first when optional.</li><li><code>*args</code>: iterable<br> Other arguments.</li></ul></details><details closed><summary> <b>Returns</b></summary><p/><ul><li><code>var3</code>: int<br> Returns `var3` which is of type ``int``.</li></ul></details><details closed><summary> <b>Examples</b></summary><p/>These are written in doctest format, and should illustrate how to use the function.
>>> a = [1, 2, 3]
>>> b = deprecated_function(a)
>>> print(b)
[4,5,6]
</details>
[^1]: Trager, Scott. "The Earth's atmosphere: seeing, background, absorption & scattering" (PDF). S.C. Trager. Retrieved 31 May 2022
Syntax
Currently tinydocs only supports NumpyDoc syntax. This might change in the future. For a detailed guide check out numpy's style guidelines you can also check-out the example directory of this project.
Here is the docstring that generates the documentation on the example above, taken mostly from numpydoc's example.
def function(var1, var2, long_var_name=None, *args):
"""This is an example documentation.
Several sentences providing an extended description. Refer to
variables using back-ticks, e.g. `var`.
Parameters
----------
var1 : array_like
Array_like means all those objects -- lists, nested lists, etc. --
that can be converted to an array. We can also refer to
variables like `var1`.
var2 : int
The type above can either refer to an actual Python type
(e.g. ``int``), or describe the type of the variable in more
detail, e.g. ``(N,) ndarray`` or ``array_like``.
long_var_name : {'hi', 'ho'}, optional
Choices in brackets, default first when optional.
*args : iterable
Other arguments.
Returns
-------
var3 : int
Returns `var3` which is of type ``int``.
Notes
-----
Look at this really big equation that I took from [1]_
$$( \sum_{k=1}^n a_k b_k )^2 \leq ( \sum_{k=1}^n a_k^2 ) ( \sum_{k=1}^n b_k^2 )$$
Warnings
--------
Deprecation Warning: `deprecated_function` will be removed in version 2.0.0, it is
replaced by `better_function` because the new one is blazingly fast.
References
----------
.. [1] Trager, Scott. "The Earth's atmosphere: seeing, background, absorption &
scattering" (PDF). S.C. Trager. Retrieved 31 May 2022
Examples
--------
These are written in doctest format, and should illustrate how to
use the function.
>>> a = [1, 2, 3]
>>> b = deprecated_function(a)
>>> print(b)
[4,5,6]
"""
pass
Basic Usage
tinydocs can be run directly from the command line using:
tinydocs <options>
Note By design
--tinydocsonly looks at.pyfiles and skips over hidden directories and will ignore any opbject (files, functions or methods) that start with_(underscore).
--dir: Directory to document. Defaults to working directory.--output: Output path and name of documentation file. Defaults to--dir/TINYDOCS.mdwhen not supplied.--exclude-dirs: List of directories to exclude entirely from the documentation.--exclude-files: List of files to exclude individually from the documentation.--help: Help will always be given to those who ask for it.
Github Workflow
tinydocs incorporates very well with automatic deployment allowing you to update your documentation on every push. Here's an example workflow on
.github/workflows/tinydocs.yaml:
name: Update TINYDOCS.md
on:
push:
branches:
- "*"
jobs:
build:
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v2
- name: Setup Python
uses: actions/setup-python@v2
with:
python-version: 3.10
- name: Install tinydocs
run: pip install tinydocs
- name: Run tinydocs
run: tinydocs
- name: Commit and push TINYDOCS.md
run: |
git config --local user.email "github-actions@example.com"
git config --local user.name "GitHub Actions"
git add TINYDOCS.md
git commit -m "Update TINYDOCS.md"
git push
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