TransKit is a pharmacokinetic simulation library specifically tailored for transgender hormone therapy. It provides a set of low level tools that transgender people can use to understand, manage, and control their hormonal transitions. It is one component of Tilia, and is designed as an open source library that can be used by other projects supporting the transgender community. In its current state it should be considered experimental, but already contains a number of tools that can be useful (and have been useful to the author).
Currently the easiest way to access this library is through a Jupyter Notebook, documented below.
All dependencies are handled using Poetry, and are specified in the project's pyproject.toml file.
All the dependencies you need to work with these notebooks will be installed in a virtualenv specifically for this project using:
> poetry install -D
If you don't want to follow the steps manually, you can also run the ./tools/install.sh script.
To start Jupyter, run:
> poetry run jupyter lab
notebooks/TransKit.ipynb is a notebook using sample injections data demonstrating basic usage.
I keep my own hormonal data in a different repository, checked out in a parallel directory to this one. My directory structure looks like this:
hormones/
my/
Estradiol.ipynb -- personal notebook
transition.py -- my injections data
transkit/
notebooks/
TransKit.ipynb
...
tools/
lab.sh
publish.sh
...
...
transkit-pages/
<html files>
To start Jupyter so that it can access both directories, you can run the ./tools/lab.sh script.
To cut an html release of the notebooks for publishing, run the ./tools/publish.sh script.
It outputs the html files to the ../trankit-pages directory, and expects that to exist.
TransKit uses Pytest for running tests. You can run all the tests using:
> poetry run pytest
And you can generate a pretty code coverage report with:
> poetry run pytest --cov-report html --cov=transkit
We use Black for code formatting and Flake8 for linting. They're required and are set up to run in a pre-commit hook.
After installing dependencies with poetry, run:
> poetry run pre-commit install
Then, all the required checks will run before you can commit. You can also manually run them with:
> poetry run pre-commit run --all-files
We also use jupytext to allow Jupyter notebooks to be represented as plain-text markdown files.
The notebooks/*.md files represent the input text of each notebook.
The notebooks/*.ipynb notebook files are paired with them and represent the full notebook, including output.
You can open either in Jupyter Lab and the changes will be synced between them.
We commit both files to benefit from the usable diffs of markdown files, and from the accessible viewing of the ipynb files.
The pre-commit hook ensures that they are in sync.