Important

Opening this repository in VSCode may run a setup script on folder open if you trust the workspace (see detailed automatic task conditions). You may disable this behavior or choose to contribute from a Dev Container or Codespace instead.

Contributing#

Thank you for considering contributing to c_therm_tci! No contribution is too small, even if you are just submitting a Pull Request through the GitHub UI to fix some typos or clarify our language! Before attempting larger changes, please discuss it with us or participate in the relevant issue topic.

This guide gives the high-level details needed for you to jump right in, but links to more detail throughout. And remember, we’re always learning!

Overview#

This guide consists of the following:

We’re always learning: Some context for new and experienced contributors alike.
Workflow: A high-level overview of the contribution process.
Checks: Checks applied during pre-commit and in continuous integration (CI).
Code: This project’s code style and the tools that help you to maintain it.
Tests: Guidance on running, writing, and adding tests.
Documentation: Details on documentation.
First-time setup: Instructions for setting up a brand new machine from scratch.
Appendix: More detail on concepts and terminology linked to throughout this guide.

We’re always learning#

You already know that no contribution is too small, but also, no question is too small! We are here to help you contribute, so feel free to reach out with questions or submit your Pull Request as a “Draft” and mention (@) one of us if you need help along the way.

If you want to contribute but aren’t sure where to start, chime in on any good first issues (or any issue) that interests you and we’ll point you in the right direction! And remember that it’s natural to experience some anxiety or or discomfort during this process. If you’re new to contributing, you may be learning all of these things at once:

How to interact with maintainers (strangers?!).
How to write Python code.
How to work with tooling (What are all these squiggly underlines?).
How to test your code (Wait, you write Python code to test Python code?).
How to write documentation (I’ve got to learn Markdown as well?).
How to set up your machine.
And more…

This project and its guide are set up to smooth out that learning curve for you a little bit, but if you get lost somewhere along the way, remember that no question is too small!

Workflow#

[!IMPORTANT] Project tooling requires installation of cross-platform PowerShell. This guide also features VSCode-specific instruction, but you are not required to use VSCode to contribute. The decision to organize around a single IDE and shell enables the cross-platform, beginner-friendly contributing experience.

To make a new contribution, fork this repository, clone it, switch to a new branch (please don’t commit directly to main), run scripts/Sync-Py.ps1, make changes, commit and push them, and open a Pull Request targeting main. You may also open a draft Pull Request if you want feedback before your branch is ready to merge, but remember to mention (@) us. In more detail:

Perform first-time setup, including installing cross-platform PowerShell and Python 3.11 (details).
Fork the repository by selecting “Fork” near the top-right corner of the project page on GitHub. Clone your fork and open it locally, e.g. in VSCode (details).
If using VSCode, consider installing the recommended extensions when prompted (details).
Create a new branch and switch to it, e.g. git checkout -b my-new-feature or in VSCode or select + in the GitLens branches view (Palette: GitLens: Show Branches View).
If not already run automatically, run scripts/Sync-Py.ps1 to set up your contribution environment.
If using VSCode, respond Yes when prompted to select the virtual environment for your workspace, or select it later (details).
Make changes, commit, and push them. (details).
- Follow code style and ensure changes pass checks.
- Write tests for all code changes.
- Update documentation for all code changes.
Consider updating the changelog for any changes that are relevant to those using this library.
Open a Pull Request targeting main. Feel free to open a Draft Pull Request if needed, mentioning (@) someone with any questions.
Ensure CI checks pass.

Checks#

Code and documentation style is checked with pre-commit and in continuous integration (CI) when you submit a Pull Request. Please ask a question if you are having trouble passing local pre-commit checks. pyright checks Python type annotations, ruff checks and formats code, markdownlint-cli2 chcks and formats Markdown, and fawltydeps checks dependencies. VSCode is configured to auto-format on save, and certain tools will automatically apply fixes on save. See the contributor tools guide for more detail on interactive tool usage in VSCode.

[!IMPORTANT] If pre-commit fails while committing with the VSCode UI, it will throw up a dialog with a scary red “X” and an unhelpful message. Always select Show Command Output in this dialog and search for failed in the resulting window with Ctrl+F. Alternatively, run the pre-commit VSCode Task to get color-coded feedback in the terminal instead.

While pre-commit will run all necessary checks, manual checks for individual tools may be run from the command-line interface (CLI) and have the following VSCode interactions:

pre-commit and the pre-commit VSCode Task.
pyright and in the VSCode problems pane.
ruff check .; ruff format . and in the VSCode problems pane and the task: Run ruff VSCode Task.
markdownlint-cli2 and in the VSCode problems pane.
fawltydeps or e.g. fawltydeps --config-file docs/pyproject.toml.
sourcery review --fix --diff 'git diff main' and VSCode problems pane (optional).

Code#

To be continued…

Tests#

This project uses pytest to test the c_therm_tci code in src.

Documentation#

This project mostly follows the numpydoc docstring standard, with minor variations enforced by ruff. Notable deviations are:

Use the imperative mood in the one-line summary, and you can usually omit the article (“a”, “an”, “the”) on nouns in the one-line summary.
Simple functions may only need a one-line summary, or a one-line summary and an extended summary.
Don’t include types in parameters sections.
Never include an “Other Parameters” section.
Outside of numpydoc-styled sections, write simple paragraphs and use MyST Markdown sparingly as needed.
Avoid too much fancy formatting in the docstring, it should read well in plain text.

def say_hello(name: str, family: bool = False) -> str:
    """Greet guest.

    If the guest is a family member, greet them warmly.

    Parameters
    ----------
    name
      The name of the guest.
    family
      Whether the guest is a family member.
    """
    ...

Contributor tools guide#

This guide details VSCode-specific tool usage. The following technqiuqes are facilitated by project tools:

Learn gradually from immediate feedback
Check dependencies with fawltydeps
Keep track of expected data types
Check and format Markdown documentation
Automate tedium every time you save the file
Debug your code with VSCode debug configurations
Reduce friction and typos with refactoring

Learn gradually from immediate feedback#

If you’re editing files in VSCode, certain tools give feedback by placing squiggly underlines under problem areas. These are also shown in the Problems pane (Palette: View: Focus Problems). Interact with these warnings clicking the lightbulb that appears near your cursor or by pressing Ctrl+.. You can often click links in the Problems pane for more details.

Tools like ruff, pyright, markdownlint-cli2, and sourcery gently nudge us towards writing better code by bringing up things we might not have even known to search for. In VSCode, we can press Ctrl+. (or select the floating lightbulb) and interact with such warnings. You may invoke pyright at the command line or use Pylance in VSCode, which uses pyright to provide squiggly underlines for incorrect type annotations in code.

Sourcery#

The sourcery tool is only applied in CI. You may optionally use it locally, but since it requires a (free) individual account, you are not required to do so. This tool is recommended for Python learners, as it rewrites code in logically-equivalent but usually shorter or more idiomatic ways, giving a rationale for the change.

[!IMPORTANT] If you optionally choose to use sourcery in VSCode, you do not need to click Opt-In during on-boarding step. This project disables the generative AI-powered features of sourcery, and instead uses only its basic refactoring rules.

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Check dependencies with `fawltydeps`#

The fawltydeps tool ensures that all Python dependencies in use are declared, and that all declared dependencies are used. The various pyproject.toml files in this project correspond to the package itself (the root pyproject.toml) as well as documentation, scripts/tooling, and testing packages defined in the docs, scripts, tests subfolders, respectively. If your changes modify dependencies, add the appropriate dependencies to the appropriate pyproject.toml file.

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Keep track of expected data types#

Pylance uses pyright to look for issues with the “types” of variables passing through code. But how does Pylance know what “type” a certain variable should be? We can use “type annotations” to tell it what type we want a variable to have. For instance the first parameter in the do_something_fancy function signature is an_argument: int, where an_argument is the name of that first argument, and int is the type that we want it to be.

Python won’t guarantee that an_argument is an int, but Pylance will warn us if we try to pass something else in. Try passing a non-integer to do_something_fancy. This is useful for catching bugs early, and for documenting our code. We also see from the -> float annotation that do_something_fancy should return a float.

We can even “reveal” the expected types of things by holding down the Ctrl+Alt keys. We can see a ghostly : float appear next to the result variable in the main() function body. This tells us that Pylance has inferred result to be a floating point number.

You can interact with Pylance underlines much in the same way as you do with Ruff, the lightbulb or Ctrl+. will let you interact with them.

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Check and format Markdown documentation#

This template configures the Markdownlint and Markdown All-in-One extensions to help you in writing Markdown documentation. It’s a simple text format that automatically renders to HTML in Gists and elsewhere. Select the preview icon in the tab bar when modifying a Markdown document to get a live preview, formatted to look like GitHub Markdown by this extension.

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Automate tedium every time you save the file#

You may have noticed some spacing changes whenver you save the file. This is happening because we have enabled auto-formatting on save in .vscode/settings.json. This is also the case in notebooks. Whenever you save a Python file, ruff will automatically format it, check for stylistic issues, and fix some of them automatically. With auto-formatting, you’ll find yourself writing longer bits of code that may run long, but a quick Ctrl+S will format it neatly. Still, try to avoid packing too much code into one statement.

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Debug your code with VSCode debug configurations#

The configurations in .vscode/launch.json enable you to run your code in debug mode, that is, to freeze in the middle of executing your code and analyze local state. See VSCode’s Python debugging guide for details, but in short, you can debug your code by clicking in the “gutter” (to the left of the line number) to place a breakpoint, then press F5 or select the drop-down arrow next to the “play button” in the tab strip and select Debug Python file. The bundled debug configuration redirects output to the Debug Console pane, so all commands run there will receive input there, as opposed to the default configuration where output is echoed to the Terminal pane. back

Reduce friction and typos with refactoring#

It is easy to make mistakes whenever you copy/paste/modify. We can use our IDE’s “refactoring” tools instead, like Pylance in VSCode, to reduce the frequency of error-prone copy/paste/modify operations. Renaming functions or variables (collectively called “symbols”), bundling related bits of code into functions, or moving logic across files is part of a process called “refactoring”. In VSCode, these tools are accessible via a contextual floating lightbulb that appears near your cursor which can be triggered by selecting it or pressing Ctrl+.. Consider trying out some of these tools next time you’re writing code:

Import symbols automatically when you need them#

In order to use pi from Python’s math module, you need to type from math import pi at the top of the file, then use pi in your code. Instead, just start typing pi the first time you want to use it, then select the appropriate entry from the drop-down menu and press Tab to insert it. Pylance will automatically add the necessary import statement at the top of the file. You can bring up this drop-down menu with Ctrl+Space (Palette: Trigger suggest) or see similar import suggestions in the lightbulb menu. This “just works” for most symbols, but you may still need to manually import some things.

Move code to other files#

Place your cursor in any symbol, click the lightbulb or press Ctrl+., then select Move symbol to ... to move it to another file.

Rename symbols#

Place your cursor in any symbol and click the lightbulb or press F2 to rename it. You can do this wherever a symbol is defined or used and Pylance will rename it everywhere.

Extract code into its own function#

As you write code, you may find that certain blocks of code deal only with a few short-lived variables that are not used later on. This block may be a candidate for extraction into its own function. Try highlighting these lines (press Ctrl+L repeatedly to select entire lines at a time), click the lightbulb, then click Extract method... and name it do_related_things.

Extract constants#

You may find yourself hard-coding a “magic number”, e.g. 65535. It may have some special meaning to you, but the intent is not clear to others. Try renaming 65535. Highlight it, click the lightbulb, click Extract variable..., and name it MAX_16_BIT_INTEGER. You may now move this to the top of the file (you’ll have to manually cut/paste from here).

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First-time setup#

Some basics need installing on a new computer, also useful if you’re new to Python and contributing altogether!

If you’re on Windows, paste the script detailed in the first-time setup script for Windows into a local Windows PowerShell terminal (right-click and select Run as administrator). Once Windows Terminal (wt) is installed, you may also want to open it from the start menu, click the drop-down arrow, select Settings, select PowerShell (not Windows PowerShell) as your default profile, and consider setting the “default terminal application” to Windows Terminal.

Workflow

Installing Python#

If no system Python matches Python 3.11 needed for contributing, the necessary Python version will be sourced. However, if you don’t have any version of Python installed, or would prefer to source Python 3.11 yourself, you may install Python as follows.

Windows or MacOS#

If you’re on Windows or MacOS, consider installing Python 3.11 from https://www.python.org/downloads/ rather than from the Windows Store or Homebrew! These are built by the CPython team, and they know best when it comes to setting the right compiler flags when building for your operating system. Select the latest version of Python 3.11 in the “Looking for a specific release?” section, then select the appropriate installer in the “Files” section of the resulting page.

Linux, Ubuntu, or other UNIX-like systems#

If you’re on Linux, Ubuntu, or another UNIX-like systems, you could compile and install Python from source at https://www.python.org/downloads/, but consider installing Python from deadsnakes instead. This allows you to install Python with necessary extras, e.g. sudo apt install python3.11 python3.11-dev python3.11-venv python3.11-distutils python3.11-tk. Make sure you at least install python#.##-venv for your chosen Python.

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Create a GitHub account and configure git#

Modify the following terminal commands with your GitHub username/email to populate .gitconfig in your user folder (e.g. %USERPROFILE%/.gitconfig on Windows, ~/.gitconfig otherwise), so that you can commit changes in VSCode using your GitHub identity.

git config --global user.name 'yourGitHubUsername'
git config --global user.email 'yourGitHubAssociatedEmail@email.com'

If done correctly, VSCode will prompt you to log in to your GitHub account before pushing changes (a later step in the overall process above).

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Fork and clone#

These steps outline the process for cloning your fork locally and opening it in VSCode. In the web UI of your fork, click the green button labelled “Code”, select “Local” and “HTTPS”. and click the copy icon to copy the resulting URL. Use it to clone your fork locally by clicking Clone Repository in a new VSCode window (Palette: View: Show Source Control) or (Palette: Git: Clone)or at the command line. For example:

git clone '<URL you copied>' '<destination>'

If done via the VSCode UI, click Open when prompted to open your newly-created Gist in VSCode, or navigate to it in your file explorer and open it in VSCode.

Workflow

Set your Python interpreter#

If you missed your chance on initial setup, you can still set the Python interpreter at any point. This will select the virtual environment for the workspace folder, and allow your Python scripts to leverage the packages we have installed from requirements.txt.

Open the main script in your Gist, e.g. example.py
Check for venv in the bottom-right corner of VSCode, e.g. 3.11.# 64-bit (.venv: venv)
If you don’t see venv, click the version number to select the option with .venv in it

Workflow

Appendix#

Conditions in which VSCode automatic tasks run#

If you have trusted this folder in VSCode or have security.workspace.trust.enabled set to false in your User settings.json and have task.allowAutomaticTasks set to on in your User settings.json, the VSCode Task setup: Sync contributor environment automatically runs on folder open and invokes scripts/Sync-Py.ps1.

Disable automatic tasks in VSCode#

You may disable this behavior by pressingCtrl+Shift+P typing to find the command Tasks: Manage Automatic Tasks, selecting it, and selecting Disallow Automatic Tasks.

"task.allowAutomaticTasks": "on"

It should only trigger if you have allowed VSCode Tasks to run automatically and have marked your forked clone of this repository as trusted. If you prefer to contribute with further.

Cross-platform PowerShell#

PowerShell, once a Windows-only system shell, is now supported on Windows, MacOS, and Linux alike. This repository features tooling that sets up the environment with scripts/Sync-Py.ps1, to be run on cross-platform PowerShell, which, among other things, sources the appropriate Python version. Install PowerShell like this.

The contents of scripts/Initialize-Shell.ps1 represents a sort of “profile” for your PowerShell terminal sessions. But you are not required to add it to your user shell profile. Instead, it is explicitly invoked whenever needed, including in other shell scripts, local pre-commit hooks and in VSCode Tasks.

However, if you do want to add it to your user shell profile, you may do so by running code $PROFILE in pwsh after you have installed it, which will open your pwsh user profile in VSCode. You may then copy the contents of scripts/Initialize-Shell.ps1 into a conditional statement that checks whether you are in this project’s directory (e.g. c-therm-tci), like so:

if ((Get-Item '.' | Select-Object -ExpandProperty 'Name') -eq 'c-therm-tci') {
  # Paste the contents of `scripts/Initialize-Shell.ps1` here
}

Contributing

Contribute from a Dev Container or Codespace#

This project also supports contributions from a dev container (Palette: Dev Containers: Open Folder in Container) or as a Codespace.

Installing recommended extensions in VSCode#

To install workspace-recommended extensions in VSCode, restart (Palette: Developer: Reload Window) and click Yes when prompted to install recommended extensions when prompted. Otherwise, navigate to Extensions (Palette: View: Show Extensions), search for @recommended, and click the cloud icon next to Workspace Recommendations to install them.

Making changes#

See this video segment for making changes in VSCode, as well as a brief outline and more detail.

Workflow

Pinning dependencies#

If c_therm_tci depends on pandas (for example), it helps if I write down the specific version of pandas that this package works with. If I pip install pandas, then a specific version of Pandas will be installed, for instance version 2.2.1 at the time of writing. When import pandas runs in this package, it uses pandas version 2.2.1. But like any package, pandas changes over time, and pandas version 2.2.1 installed at the time of writing behaves differently from the version of pandas released a year ago or to be released a year from now. I can only guarantee that this package works with the version of pandas I’m running right now, so I keep track of that by writing pandas==2.2.1 in lock.json. This is called dependency pinning, which can be done for every dependency of this project, including transitive dependencies, for different operating systems and different versions of Python! These exact version pins above are good for recreating the exact environment needed by you, a potential contributor to this project!

However, these exact version pins are overly restrictive to those who just want to use c_therm_tci in their own code. Python environments cannot have multiple versions of pandas installed at once. If I install c_therm_tci using pip install c_therm_tci with no other qualifiers, it is retrieved from PyPI and the the version metadata defined in pyproject.toml is used to decide which packages to install alongside it. If c_therm_tci depends on pandas==2.2.1 as specified in pyproject.toml, and I try to install something else alongside it that doesn’t support pandas version 2.2.1, Python will refuse to install it! I want c_therm_tci to coexist to the greatest degree possible with other projects, so I list pandas>=2.2.1 in pyproject.toml instead.

Specifying >= may be seen as a promise that this version of c_therm_tci will work with any new release of pandas, which I couldn’t possibly know for sure. But it’s a better alternative to specifying pandas>=2.2.1,<3, because the <3 upper-bound will not allow this package to coexist in any Python environment with another package in that requires pandas>=3.0.0 in the future. Upper-bound restrictions like <3 would make c_therm_tci eventually hostile to usage alongside other packages. This is because a project that depends on this package inherits pandas>=2.2.1,<3 as a transitive dependency specification, and there is no recourse for overriding it. If a new version of pandas must be restricted in the course of development of this package, it should be specified like pandas>=2.2.1,!=3.0.0 at the time of breakage, and changes should be made to allow removing the !=3.0.0 restriction as soon as possible.

In short, in Python dependency specifications, <3 doesn’t have the same heart-shaped connotation it might have as an emoji! I pin exact dependencies to ensure working environments for potential contributors across operating systems, but specify only lower bounds with short-lived != exclusions in the distribution of this package to PyPI.

Workflow

Source for different system Python versions#

This project looks for Python 3.11 on your system to generate the virtual environment used for development. See how to install Python if you don’t have Python installed at all. If your system has any version of Python pre-installed other than Python 3.11 used for development, a temporary virtual environment with zstandard is installed and scripts/install.py used to source the necessary Python version from indygreg/python-build-standalone. This approach is derived from the one used by the uv team to source Python binaries for their tooling!

looks for any system Python on your machine, and uses it directly to create a development virtual environment if it’s the correct version, or sources the expected version of Python (in a project-local bin)

Workflow

System Python environment#

Depending on my OS, I use “system Python environment” or just “system Python” to refer to the version of Python already installed on my machine and the set of packages installed and usable by that Python installation. I also use “system Python” to refer to versions of Python manually installed, for instance from https://www.python.org/. This differentiates Python environments installed and expected to be used across the entire machine from virtual environments to be used for specific projects.

Workflow

Contribution environment sync#

This repository features tooling that bootstraps the entire development environment with scripts/Sync-Py.ps1, to be run on cross-platform PowerShell, and the contribution workflow is tested on Windows, Ubuntu, and MacOS 13. If on Windows, you may need to complete Task 1 in this guide to allow scripts to run. scripts/Sync-Py.ps1 (Task: setup: Sync contributor environment). The scripts/Sync-Py.ps1 script essentially does the following:

Sets some environment variables and error handling.
Installs uv.
Creates a virtual environment from your system Python if it’s the correct version for development or else sources the appropriate Python version and bases the virtual environment on that.
Syncs submodules.
Syncs a Python virtual environment to platform-specific dependencies in lock.json.
Installs pre-commit hooks.
Conditionally runs setup specific to CI or Dev Containers.

Workflow

Run a VSCode task#

This project defines VSCode Tasks (Palette: Tasks: Run task) defined in .vscode/tasks.json that run some common actions:

setup: Sync contributor environment: Run the contribution environment sync script.
pre-commit: Trigger pre-commit on your staged changes.
git: Rebase back to fork: Trigger an interactive rebase of commits made to a feature branch
task: Run pytest with coverage: Generates a local coverage report for review with coverage report or for local gutter highlights with the Coverage Gutters VSCode extension.
task: sphinx-autobuild docs (preview): Build and serve the documentation locally for previewing. Ctrl+click on the displayed IP http://127.0.0.1:8000 (points to localhost) in the terminal to preview documentation live as you make changes.
task: profile this file: Profile the currently open Python file with cProfile.
task: view profile results with snakeviz: View the results of the latest profiling run.

You may choose to bind Tasks: Run task command to a keyboard shortcut of your choice (Palette: Preferences: Open Keyboard Shortcuts) or modify keybindings.json directly with the similar (JSON)-suffixed command. For example, consider the following entries in keybindings.json:

{
  // ...
  // Bind `Ctrl+Shift+Z` to `Tasks: Run task`
  {
    "key": "ctrl+shift+z",
    "command": "workbench.action.tasks.runTask"
  },
  // Unbind conflicting key for "redo" (it's already on Ctrl+Y)
  {
    "key": "ctrl+shift+z",
    "command": "-redo"
  },
  // ...
}

Some less-common tasks#

The following tasks are less-commonly needed, used mostly by maintainers, or can otherwise be disruptive by triggering lots of changes across the project:

pre-commit: all: Trigger pre-commit on all tracked files. Run this if making rule changes in tooling or when tool behavior changes (e.g. ruff, markdownlint-cli2).
task: Run ruff: Check and format all files with ruff. Run this whenever an update to ruff or its rules causes a behavior change.
setup: Sync with template: Sync the project with its template, generally only used by maintainers and when bumping versions.
setup: Perform first-time setup: Usually only run after the very first commits of a project.
setup: Remove *.rej: Clean up .rej files sometimes left behind by template sync.

Transitive dependency#

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Virtual environment#

In the context of Python development, a virtual environment represents an isolated installation of Python, usually in a .venv folder in the working directory.

Say you have installed pandas with some variation of pip install pandas. pandas It is important to use a virtual environment because if you use a Python package (e.g. import pandas) that you have installed (e.g. ), your code implicitly depends on the version of pandas

It is important to create and use a virtual environment for each of your Python projects

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VSCode command palette#

A searchable list of commands in VSCode, by default accessible by pressing Ctrl+Shift+P and beginning to type the desired command. Command search is case-insensitive and fairly forgiving.

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Inspiration for this contributing guide#

I’ve gradually built up the tooling and documentation for this project and others in the blakeNaccarato/copier-python project template. In a push to finish up this guide, I’ve also reviewed other contributing guides to integrate some more best practices. If you’re looking for a modern, slim, effective contribution guide, it’s a safe bet that Hynek’s latest project represents the latest best practices! Since the goals of this project’s contributor experience is to bundle lots of helpful resources to accelerate learning, this guide is somewhat more verbose. Also, this project’s templates are inspired by those over at obsidian-tasks-group/obsidian-tasks.

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First-time setup script for Windows#

This script invokes Windows package manager (winget) from your system’s built-in PowerShell to install cross-platform PowerShell and other tools needed for contribution to this project. Run your system’s built-in PowerShell (not ISE) as administrator by searching for it in Start, right-clicking and selecting Run as administrator. Copy-paste the following script into the terminal window and run it. This script runs a series of winget commands and ensures Windows Terminal is installed.

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<#.SYNOPSIS
One-time setup for Python dev tools on Windows. Installs Python, VSCode, Windows Terminal, PowerShell, and Git.
#>

# Install Python
winget install --id 'Python.Python.3.11' --override '/quiet PrependPath=0'
# Install VSCode
winget install --id 'Microsoft.VisualStudioCode'
# Install Windows Terminal
winget install --id 'Microsoft.WindowsTerminal'

# Install cross-platform PowerShell
$PowerShellOverrides = @(
  '/quiet'
  'ADD_EXPLORER_CONTEXT_MENU_OPENPOWERSHELL=1'
  'ADD_FILE_CONTEXT_MENU_RUNPOWERSHELL=1'
  'ADD_PATH=1'
  'ENABLE_MU=1'
  'ENABLE_PSREMOTING=1'
  'REGISTER_MANIFEST=1'
  'USE_MU=1'
)
winget install --id 'Microsoft.PowerShell' --override $PowerShellOverrides

# Install git
@'
[Setup]
Lang=default
Dir=C:/Program Files/Git
Group=Git
NoIcons=0
SetupType=default
Components=ext,ext\shellhere,ext\guihere,gitlfs,assoc,assoc_sh,autoupdate,windowsterminal,scalar
Tasks=
EditorOption=VisualStudioCode
CustomEditorPath=
DefaultBranchOption=main
PathOption=Cmd
SSHOption=OpenSSH
TortoiseOption=false
CURLOption=OpenSSL
CRLFOption=CRLFAlways
BashTerminalOption=MinTTY
GitPullBehaviorOption=Merge
UseCredentialManager=Enabled
PerformanceTweaksFSCache=Enabled
EnableSymlinks=Disabled
EnablePseudoConsoleSupport=Disabled
EnableFSMonitor=Enabled
'@ | Out-File ($inf = New-TemporaryFile)
winget install --id 'Git.Git' --override "/SILENT /LOADINF=$inf"

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Contributing

Contents

Contributing#

Overview#

We’re always learning#

Workflow#

Checks#

Code#

Tests#

Documentation#

Contributor tools guide#

Learn gradually from immediate feedback#

Sourcery#

Check dependencies with fawltydeps#

Keep track of expected data types#

Check and format Markdown documentation#

Automate tedium every time you save the file#

Debug your code with VSCode debug configurations#

Reduce friction and typos with refactoring#

Import symbols automatically when you need them#

Move code to other files#

Rename symbols#

Extract code into its own function#

Extract constants#

First-time setup#

Installing Python#

Windows or MacOS#

Linux, Ubuntu, or other UNIX-like systems#

Create a GitHub account and configure git#

Fork and clone#

Set your Python interpreter#

Appendix#

Conditions in which VSCode automatic tasks run#

Disable automatic tasks in VSCode#

Cross-platform PowerShell#

Contribute from a Dev Container or Codespace#

Installing recommended extensions in VSCode#

Making changes#

Pinning dependencies#

Source for different system Python versions#

System Python environment#

Contribution environment sync#

Run a VSCode task#

Some less-common tasks#

Transitive dependency#

Virtual environment#

VSCode command palette#

Inspiration for this contributing guide#

First-time setup script for Windows#

Check dependencies with `fawltydeps`#