workon-poetry

Bash and Python scripts to make switching and starting projects more efficient and less error-prone by automating some of the boring stuff and incorporating some opinions about best practices.

Dependencies

• poetry
• virtualenv

Setup your Python environment

Launch a terminal on Linux (or git-bash on Windows) then:

1. Update your pip and virtualenv packages
2. Clone the workon-poetry project
3. Create a virtualenv within the workon-poetry dir
4. Activate your new Python virtual environment
5. Install this Python package in "--editable" mode

Any Python version greater than 3.7 should work. As of 2023 most Linux systems use Python 3.9 or higher:

pip install --upgrade virtualenv poetry
git clone git@gitlab.com:tangibleai/community/workon-poetry
cd workon-poetry
python -m virtualenv --python 3.9 .venv
ls -hal

You should see a new .venv/ directory. It will contain your python interpreter and a few site-packages like pip and distutils.

Now activate your new virtual environment by sourcing .venv/bin/activate (on Linux) or .venv/scripts/activate (on Windows).

# bin/activate on Linux OR `Scripts/activate` in git-bash on Windows
source .venv/bin/activate || source .venv/Scripts/activate

Developer install

Once you have a shiny new virtual environment activated you can install workon-poetry in --editable mode. This way, when you edit the files and have the package change immediately.

Make sure you are already within your cloned workon-poetry project directory. And makes sure your virtual environment is activated. You should see the name of your virtual environment in parentheses within your command line prompt, like (.venv) $. Then when you install workon-poetry it will be available for import within any other Python application in that virtual environment.

pip install --editable .

User install

If you don't want to contribute, and you just want to USE workon-poetry the MathText modules, you can install it from a binary wheel on PyPi:

pip install workon-poetry