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Copy file name to clipboardExpand all lines: CHANGELOG.md
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You should also add project tags for each release in Github, see [Managing releases in a repository](https://docs.github.com/en/repositories/releasing-projects-on-github/managing-releases-in-a-repository).
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## [Unreleased]
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- Added example auto-built Sphinx documentation in the `docs` folder
Copy file name to clipboardExpand all lines: README.md
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```
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.
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├── cdstemplate # The python package root - Any code you'd like to be able to import lives here
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│ ├── corpus_counter_script.py # A script that takes a list of documents as input and outputs a CSV of word counts
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│ ├── __init__.py # Indicates that this directory is a python package, you can put special import instructions here
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│ ├── word_count.py # A module that has functions and classes to import
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│ └── utils.py # A module that handles logging and other internals
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├── corpus_counter_script.py # A script that takes a list of documents as input and outputs a CSV of word counts
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├── __init__.py # Indicates that this directory is a python package, you can put special import instructions here
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├── word_count.py # A module that has functions and classes to import
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└── utils.py # A module that handles logging and other internals
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├── CHANGELOG.md # Versioning information
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├── dag_workflow.png # An image that is linked to in this README
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├── data # Data files which may or may not be tracked in Git, but we reserve a folder for them so that users can all have the same relative paths
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│ ├── gutenberg # Sample text input files, the raw inputs to our experiment pipeline.
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│ └── gutenberg_counts.csv # The expected output file for our experiment. It's generated by `dvc repro` and is ignored by git.
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├── gutenberg # Sample text input files, the raw inputs to our experiment pipeline.
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└── gutenberg_counts.csv # The expected output file for our experiment. It's generated by `dvc repro` and is ignored by git.
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├── docs # Sphinx auto-documentation uses this folder to run its scripts and store documentation
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├── _build # Contains the Sphinx doctree and html documentation source code
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├── doctrees # A folder with doctree construction information
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└── html # A folder that contains the html code for all automatically created documentation
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├── _static # A folder that can contain static code
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├── _templates # A folder that can contain Sphinx templates
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├── conf.py # A function that configures Sphinx according to user specifications
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├── index.rst # A directory that users can input new functions into for auto-documentation
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├── make.bat # A function that runs auto-documentation
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└── Makefile # A function that creates html documentation based on functions in the index.rst file
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├── dvc.lock # Data Version Control uses this file to compare experiment versions. It's tracked in Git, but don't edit it manually.
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├── dvc.yaml # Create the Data Version Control pipeline stages here
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├── notebooks
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│ └── word_count_prototype.ipynb # A jupyter notebook that makes pretty plots
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└── word_count_prototype.ipynb # A jupyter notebook that makes pretty plots
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├── pyproject.toml # The setuptools build tools are installed, so you project can be installed
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├── README.md # You're reading it now!
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├── setup.cfg # Project metadata and dependencies are declared for proper installation
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└── tests
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└── test_word_count.py # Unit and smoke tests for the word_count module
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├── .dvc # The configuration file for Data Version Control
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├── .github
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| └── workflows/python_package.yml # Github Workflow file, configures running tests on Github every time a pull request to the main branch is made
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└── workflows/python_package.yml # Github Workflow file, configures running tests on Github every time a pull request to the main branch is made
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├── .gitignore # Lists files that should not be included in version control, created from Github's template .gitignore for Python.
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└── .dvcignore # Lists files that Data Version Control should skip when checking for changes in stage dependencies.
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```
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-_README.md_ : Summarize the project's purpose and give installation instructions.
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-_CHANGELOG.md_ : Tell the user what has changed between versions and why, see [Keep A CHANGELOG](https://keepachangelog.com/en/1.0.0/)
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- docstrings: Appear directly in your code and give an overview of each function or object. They can be printed using `help(object)` from the python interpreter or used to automatically generate API documentation with a tool like [Sphinx](https://www.sphinx-doc.org/en/master/index.html). There are many different docstring formats. Your team can choose any they like, just be consistent. This template uses [reStructuredText style](https://peps.python.org/pep-0287/).
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- Sphinx : Create html documentation for your functions based on the docstrings you write in the code. Use [Sphinx](https://www.sphinx-doc.org/en/master/index.html) to streamline the documentation process.
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Read [Real Python's Documenting Python Code: A Complete Guide](https://realpython.com/documenting-python-code/) for more ideas about effectively documenting code. The `.md` files are written using [Markdown](https://www.markdownguide.org/), a handy formatting language that is automatically rendered in Github.
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