Development Setup¶

If you want to contribute code or documentation directly, you’ll need to create your own fork of the project on Github, and set up some version of the development environment described below, before making pull requests to submit new code, documentation, or examples of use.

Note

If you’re new to git and Github, you may want to check out:

Overview¶

The setup process ought to look something like this…

Ensure you’ve got Python 3.7 installed, preferably via conda

Fork the PUDL repository to your own Github account.

Clone your fork of PUDL to your local computer.

Create the PUDL conda environment

Use pip to install the pudl package in an editable form.

Enable git pre-commit hooks.

Run the PUDL setup script to create a data management environment.

Try running the data processing pipeline make sure everything is working.

Download whatever data you intend to work with into the PUDL datastore.

Run the full data processing pipeline with all the data you downloaded.

Run the packaging, ETL, data validation, and doc tests.

Optionally set up your editor / IDE to follow our code style guidelines.

Todo

Check that the following reflects the exact details of a real setup.

$ git clone https://github.com/USERNAME/pudl.git
$ cd pudl
$ conda update conda
$ conda env create --name pudl --file environment.yml
$ conda activate pudl
$ pip install -e ./
$ cd ..
$ mkdir pudl_workspace
$ pudl_setup --pudl_dir=pudl_workspace
$ cd pudl_workspace
$ pudl_etl settings/pudl_etl_example.yml
$ pudl_data --sources eia923,eia860,ferc1,epacems,epaipm
$ tox -e linters
$ tox -e docs
$ tox -e etl -- --fast --pudl_dir=AUTO
$ pudl_etl settings/pudl_etl_full.yml
$ tox -e validate --pudl_dir=AUTO
$ pre-commit install

Fork and Clone the Repository¶

On the main page of the PUDL repository you should see a Fork button in the upper right hand corner. Forking the repository makes a copy of it in your personal (or organizational) account on Github that is independent of, but linked to, the original “upstream” project.

Depending on your operating system and the git client you’re using to access Github, the exact cloning process might be different, but if you’re using a UNIX-like terminal, cloning the repository from your fork will look like this (with your own Github username or organizational name in place of USERNAME of course):

$ git clone https://github.com/USERNAME/pudl.git

This will download the whole history of the project, including the most recent version, and put it in a local directory called pudl.

Repository Organization¶

Inside your newly cloned local repository, you should see the following:

Directory / File	Contents
`docs/`	Documentation source files for Sphinx and Read The Docs.
`src/`	Package source code, isolated to avoid unintended imports.
`results/`	A graveyard of old Jupyter Notebooks and outputs. Ignore!
`scripts/`	Development scripts not distributed with the package.
`test/`	Modules for use with PyTest.
`environment.yml`	File defining the `pudl` `conda` environment.
`MANIFEST.in`	Template describing files included in the python package.
`pyproject.toml`	Configuration for development tools used with the project.
`setup.py`	Python build and packaging script.
`tox.ini`	Configuration for the Tox build and test framework.

Todo

Delete ci directory when postgres is deprecated.

Development Environment¶

Install PUDL for Development¶

Cloning the PUDL repository to your computer allows you to edit the code, but you also need to install that code for use, if you want to be able to see and experiment with the effects of your edits. To edit and use the same code, a Python package needs to be installed in “editable” (aka “development”) mode.

From within the top level of the cloned repository (the directory which contains setup.py), run:

$ pip install --editable ./

The --editable option keeps pip from copying files into to the site-packages directory, and instead creates references to the code you’ll be editing, which is inside the the current current directory (also known as ./).

Automated Code Checking¶

We use automated tools to apply uniform coding style and formatting across the project codebase. This reduces merge conflicts, makes the code easier to read, and helps catch bugs before they are committed. These tools are part of the pudl conda environment, and their configuration files are checked into the Github repository, so they should be installed and ready to go if you’ve cloned the pudl repo and are working inside the pudl conda environment.

These tools can be run at three different stages in development:

inside your text editor or IDE, while you are writing code or documentation,
before you make a new commit to the repository using Git’s pre-commit hook scripts,
when the tests are run – either locally or on a continuous integration (CI) platform (PUDL uses Travis CI).

flake8¶

Flake8 is a popular Python linting framework, with a large selection of plugins. We use it to run the following checks:

PyFlakes, which checks Python code for correctness,
pycodestyle which checks whether code complies with PEP 8 formatting guidelines,
mccabe a tool that measures code complexity to highlight functions that need to be simplified or reorganized.
pydocstyle checks that Python docstrings comply with PEP 257 (via the flake8-docstrings plugin).
pep8-naming checks that variable names comply with Python naming conventions.
flake8-builtins checks to make sure you haven’t accidentally clobbered any reserved Python names with your own variables.

doc8¶

Doc8 is a lot like flake8, but for Python documentation written in the reStructuredText format and built by Sphinx. This is the de-facto standard for Python documentation. The doc8 tool checks for syntax errors and other formatting issues in the documentation source files under the docs/ directory.

autopep8¶

Instead of just alerting you that there’s a style issue in your Python code, autopep8 tries to fix it automatically, applying consistent formatting rules based on PEP 8.

isort¶

Similarly isort consistently groups and orders Python import statements in each module.

Python Editors¶

Many of the tools outlined above can be run automatically in the background while you are writing code or documentation, if you are using an editor that works well with for Python development. A couple of popular options are the free Atom editor developed by Github, and the less free Sublime Text editor. Both of them have many community maintained addons and plugins.

Git Pre-commit Hooks¶

Git hooks let you automatically run scripts at various points as you manage your source code. “Pre-commit” hook scripts are run when you try to make a new commit. These scripts can review your code and identify bugs, formatting errors, bad coding habits, and other issues before the code gets checked in. This gives you the opportunity to fix those issues first.

Pretty much all you need to do is enable pre-commit hooks:

$ pre-commit install

The scripts that run are configured in the .pre-commit-config.yaml file.

In addition to autopep8, isort, flake8, and doc8, the pre-commit hooks also run bandit (a tool for identifying common security issues in Python code) and several other checks that keep you from accidentally committing large binary files, leaving debugger breakpoints in your code, forgetting to resolve merge conflicts, and other gotchas that can be hard for humans to catch but are easy for a computer.

Note

If you want to make a pull request, it’s important that all these checks pass – otherwise the build will fail, since these same checks are tun by the tests on Travis.