This README provides info about the development process.
For more info about the package itself see
package README or
docs.
$ apt update && apt install curl git python3 python3-pip python3-venv
$ python3 -m pip install pipx && pipx install poetry
$ pipx ensurepath && exec bash
$ curl -sSL https://repo.anaconda.com/miniconda/Miniconda3-py39_4.10.3-Linux-x86_64.sh -o miniconda.sh
$ bash miniconda.sh && exec bash
(base) $ git clone https://github.com/kilroybot/kilroyplot
(base) $ cd kilroyplot
(base) $ conda env create -f environment.yaml
(base) $ conda activate kilroyplot
(kilroyplot) $ cd kilroyplot
(kilroyplot) $ poetry install --syncIf you just want to try it out and don't care about polluting your environment:
$ python3 -m pip install ./kilroyplotWe are using conda for environment management
(but you can as well use any other tool, e.g. pyenv + venv). The major reason
is that conda lets you specify python version and will install that version
in the environment. This ensures consistency between different instances
(developers, CI, deployment).
The first step is of course to install conda.
To create an environment, run from project root:
conda env create -f environment.yamlAnd then activate it by:
conda activate kilroyplotCreating the environment is performed only once, but you need to activate it every time you start a new shell.
If the configuration file environment.yaml changes, you can update the
environment by:
conda env update -f environment.yamlWe are using poetry to manage our package and
its dependencies. You need to have it installed outside our environment
(I recommend to use pipx for that).
To install the package, you need to cd
into kilroyplot directory and run:
poetry install --syncThis will download and install all package dependencies (including development ones) and install the package in editable mode into the activated environment.
Editable mode means that you don't have to reinstall the package if you change something in the code. The changes are reflected automatically.
However, you need to install the package again if you change something in its configuration (e.g. add a new dependency). But more on that later.
If it's the first time installing the package, poetry will write specific
versions of all packages to poetry.lock file. This file should be committed
to the repository, so other people can have the exact same versions of all
dependencies. It will work because poetry install checks if poetry.lock
file is available and uses it if it is.
We are using pytest for tests. It's already installed
in the environment, because it's a development-time dependency. To start first
write the tests and put them in kilroyplot/tests.
To execute the tests, cd into kilroyplot and run:
poe testWe are using mkdocs
with material
for building the docs. It lets you write the docs in Markdown format and
creates a nice webpage for them.
Docs should be placed in kilroyplot/docs/docs. They
are pretty straightforward to write.
To build and serve the docs,
cd into kilroyplot and run:
poe docsIt will generate site directory with the webpage source and serve it.
If you need to add a new dependency, look into pyproject.toml file. Add it
to tool.poetry.dependencies section. If it is a development-time dependency
you need to mark it as optional and add it to the right groups
in tool.poetry.extras.
After that update the installation by running
from kilroyplot directory:
poe updateThis will install anything new in your environment and update the poetry.lock
file. Other people only need to run poetry install to adjust to the incoming
changes in the poetry.lock file.
When you push changes to remote, different GitHub Actions run to ensure project consistency. There are defined workflows for:
- deploying docs to GitHub Pages
- testing on different platforms
- drafting release notes
- uploading releases to PyPI
For more info see the files in .github/workflows directory and Actions tab
on GitHub.
Generally if you see a red mark next to your commit on GitHub or a failing
status on badges in README
it means the commit broke something (or workflows themselves are broken).
Every time you merge a pull request into main, a draft release is automatically
updated, adding the pull request to changelog. Changes can be categorized by
using labels. You can configure that in .github/release-drafter.yaml file.
Every time you publish a release the package is uploaded to PyPI
with version taken from release tag
(you should store your PyPI token in PYPI_TOKEN secret).
You can use jupyter to experiment with the code and
make some great visualizations or reports.
To launch jupyter lab environment,
cd into kilroyplot and run:
poe jupyterThe developed package is installed in the environment, so we can import it in the notebooks as any other package.