Development Setup#

This page will walk you through what you need to do if you want to be able to contribute code or documentation to the PUDL project.

These instructions assume that you are working on a Unix-like operating system (MacOS or Linux) and are already familiar with git, GitHub, and the Unix shell.

Warning

It’s not currently possible to install the development environment on Windows unless you use the Windows Subsystem for Linux (WSL).

Note

If you’re new to git and GitHub , you’ll want to check out:

Fork and Clone the PUDL Repository#

Unless you’re part of the Catalyst Cooperative organization already, you’ll need to fork the PUDL repository This makes a copy of it in your personal (or organizational) account on GitHub that is independent of, but linked to, the original “upstream” project.

Then, clone the repository from your fork to your local computer where you’ll be editing the code or docs. This will download the whole history of the project, including the most recent version, and put it in a local directory where you can make changes.

After cloning, you need to configure git to use the “ours” merge strategy for the lockfile. Run this command once from within the cloned repository:

$ git config --local merge.ours.driver true

Warning

Never manually merge pixi.lock! The lockfile (pixi.lock) is a generated file that must be regenerated programmatically. The git configuration above will automatically keep your version of the lockfile during merge conflicts, but you must then regenerate it to reflect the merged dependencies.

After merging changes from another branch (e.g. main) that modified pyproject.toml:

  1. Complete the merge (the lockfile will keep your version due to the merge strategy)

  2. Regenerate the lockfile to match the merged dependencies:

$ pixi update

  1. Commit the regenerated lockfile

This ensures your lockfile is consistent with the merged dependency specifications.

Create the PUDL Dev Environment#

We use pixi to manage our development environment.

Pixi installs packages from conda-forge. It provides reproducible environments through lockfiles that specify particular versions of all PUDL’s direct and indirect software dependencies. The dependencies are defined in pyproject.toml. The lockfile is updated weekly by our update-lockfiles.yml GitHub Action workflow. Pixi also lets us define common tasks, e.g. for running our tests. Previously we used a mix of mamba, conda-lock, and make to provide this functionality. Pixi is much faster, more flexible, under very active, development, and lets us use one tool instead of three.

See the Pixi installation guide.

With pixi installed, to install all of PUDL’s dependencies and set up the development environment, from the root of the PUDL repository run:

$ pixi install

This will create the environment and install the PUDL package in editable mode. Pixi automatically runs commands within the environment associated with your current directory when you prefix them with pixi run, so you don’t need to manually activate environments like you would with conda. If you prefer to enable the environment and forget about it, you can use pixi shell, but note that you will need to run exit to get out of that shell when switching environments.

pixi run is also used to run tasks that have been defined in pyproject.toml. To see all the available tasks defined in the project, run:

$ pixi task list

When defining a new task, make sure the name doesn’t clash with a generic shell command, otherwise the named task will take precedence and make it impossible to run the shell command in the pixi environment.

There’s additional information about running tests in the Testing PUDL documentation.

Updating the PUDL Development Environment#

You will need to periodically update your development environment to get newer versions of existing dependencies and incorporate any changes to the environment specification that have been made by other contributors.

The simplest way to update your environment is to run:

$ pixi install

This will update your local environment to be in sync with the committed pixi.lock file.

If you are adding or updating specific dependencies in pyproject.toml, you can update just that dependency:

$ pixi add "package-name>=version"  # For new dependencies
$ pixi update package-name           # To update an existing dependency

Our automated GitHub Action handles weekly updates to all dependencies. You should not generally need to update all dependencies yourself unless you’re working on dependency management. The command to update everything in pixi.lock is:

$ pixi update

You can also see what would be updated without actually changing pixi.lock with:

$ pixi update --dry-run

Note

Different development branches within the repository may have different lockfiles. When switching branches, run pixi install to sync your environment with the branch’s lockfile.

If you want to work with the most recent version of the code on a branch named new-feature, then from within the top directory of the PUDL repository you would do:

$ git checkout new-feature
$ git pull
$ pixi install

If you are working with locally processed data and there have been changes to the expectations about that data in the PUDL software, you may also need to regenerate your PUDL SQLite database or other outputs. See Running the ETL Pipeline for more details.

If you’re using an AI coding agent, you will want to install some project skills:

$ pixi run install-skills

If you want to add or update a skill to the project, run:

$ pixi run npx skills add <source>

Set Up Code Linting#

We use several automated tools to apply uniform coding style and formatting across the project codebase. This is known as code linting, and it reduces merge conflicts, makes the code easier to read, and helps catch some types of bugs before they are committed. These tools are part of the PUDL pixi environment and their configuration files are checked into the GitHub repository. If you’ve cloned the pudl repo and are working inside the pudl conda environment, they should be installed and ready to go.

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 before publishing them.

To make sure they are run before you commit any code, you need to enable the pre-commit hooks scripts with this command:

$ pixi run pre-commit-install

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

See also

Linting and Formatting#

  • ruff is a popular, fast Python linting and autofix framework, with a large selection of rules that can be configured (often mirroring plugins originally developed for flake8). We use it to check the formatting and syntax of the code and to ensure that we’re all using modern python syntax, type hinting, etc.

  • We also use ruff to format our code. It serves as a much faster drop-in replacement for longtime crowd favorite black

  • doc8 , lints our documentation files, which are 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.

  • typos checks for typos in the committed files. If you get an error, run typos path/to/file. Review all proposed corrections manually. If typos marks an issue as having more than one possible correction, manually identify and implement the desired fix in the file. If anything shouldn’t be updated (e.g., PUDL is not a typo!), add it to the pyproject.toml file under tool.typos.default.extend-words, using the format word=”word”. Run typos path/to/file again to verify that the remaining flagged typos are as anticipated. Once you’re satisfied, run typos path/to/directory -w to auto-correct any remaining typos. To ignore typos in a single line (e.g., code that corrects a typos), add # spellchecker:ignore as a comment to the end of the line.

Linting Within Your Editor#

If you are using an editor designed for Python development many of these code linting and formatting tools can be run automatically in the background while you write code or documentation. Popular editors that work with the above tools include:

Each of these editors have their own collection of plugins and settings for working with linters, formatters, and other code analysis tools.

See also

Real Python Guide to Code Editors and IDEs

Creating a Workspace#

PUDL Workspace Setup#

PUDL needs to know where to store its big piles of inputs and outputs. The PUDL_OUTPUT and PUDL_INPUT environment variables let PUDL know where all this stuff should go. We call this a “PUDL workspace”.

First, create a directory to store local caches of raw PUDL data. You can put this anywhere, but we put this in ~/pudl_input in the documentation. Then create an environment variable called PUDL_INPUT to store the path to this new directory and make sure that it is set whenever you start up a new shell. These shorthand commands will append a line to the end of your shell initialization file. If you need to change it later you’ll want to edit those files directly. Note that in the commands below you must replace the example path /absolute/path/to/pudl_input with the actual path to the directory you’ve created.

$ echo "export PUDL_INPUT=/absolute/path/to/pudl_input" >> ~/.zshrc # if you are using zsh
$ echo "export PUDL_INPUT=/absolute/path/to/pudl_input" >> ~/.bashrc # if you are using bash
$ set -Ux PUDL_INPUT /absolute/path/to/pudl_input # if you are using fish shell

The directory stored in PUDL_INPUT contains versions of PUDL’s raw data archives on Zenodo for each datasource:

pudl_input/
├── ferc1/
│   ├── 10.5281-zenodo.5534788/
│   │   ├── datapackage.json
│   │   ├── ferc1-1994.zip
│   │   ├── ferc1-1995.zip
│   │   └── ...
│   ├── 10.5281-zenodo.7314437/
│   │   └── ...
│   └── ...
├── eia860/
│   └── ...
└── ...

Warning

The data stored at the PUDL_INPUT directory can grow to be dozens of gigabytes in size. This is because when the raw data are updated, a new version of the archive is downloaded to the PUDL_INPUT directory. To slim down the size you can always delete out of date archives the code no longer depends on.

Next, create a directory to store the outputs of the PUDL ETL. As above, you can put this anywhere, but typically this is ~/pudl_output. Then, as with PUDL_INPUT, create an environment variable called PUDL_OUTPUT to store the path to this new directory. In the commands below you must replace the example path /absolute/path/to/pudl_output with the actual path to the directory you want to use.

$ echo "export PUDL_OUTPUT=/absolute/path/to/pudl_output" >> ~/.zshrc # zsh
$ echo "export PUDL_OUTPUT=/absolute/path/to/pudl_output" >> ~/.bashrc # bash
$ set -Ux PUDL_OUTPUT /absolute/path/to/pudl_output # fish

The path stored in PUDL_OUTPUT contains all ETL outputs like pudl.sqlite and core_epacems__hourly_emissions.parquet.

Warning

Make sure you set these environment variables to point at separate directories! It is also strongly recommended that you create these directories outside of the pudl repository directory so the inputs and outputs are not tracked in git.

Remember that you’ll need to either source your shell profile after adding the new environment variable definitions above, or export them at the command line for them to be active in the current shell. Again, note that these are fake example paths:

$ export PUDL_OUTPUT=/absolute/path/to/pudl_output
$ export PUDL_INPUT=/absolute/path/to/pudl_input