This page documents how to get the GeniePy boilerplate up and running for a new project.
Purchase the boilerplate from Lemon Squeezy.
After the purchase, you'll be able to download an
app-vXX.YY.ZZ.zip file to your
machine. This is the base for setting up a new application.
Note that the
XX.YY.ZZ in the file name will be different depending on the
version you end up purchasing. Once you've made a purchase, all future versions
will be made available to you at no additional cost.
zip file in the directory where you want to initialize the project.
Assuming that you store your work projects under
$HOME/projects and the name
of your new SaaS is
Example, the following commands should set everything up.
# create the project directory $ mkdir -p ~/projects/example $ cd ~/projects/example # move and extract the downloaded file into the target directory $ mv /path/to/app-v1.2.3.zip . $ unzip app-v1.2.3.zip # cleanup $ rm app-v1.2.3.zip
This should extract the application source code into the current working directory.
In line with the 12-factor methodology, GeniePy uses environment variables for application configuration.
In local development, this means using a
.env file for the application to
read. Make a copy of the
sample.env file included in the codebase:
$ cp sample.env .env
... and edit the contents of this new file based on what your project needs.
The next time you start the application on your machine, this file will be used to load all the settings.
Please note that you'll need to have a working installation of Python available for this section to work. For more details please refer to the Python pre-requisite.
Prepare a virtualenv in the current directory. The recent versions of Python
make this easy using the in-built
$ python -m venv venv $ source venv/bin/activate
If you'd like to set up the virtual environment a different way, pyenv is a good option to consider, especially if you're working a lot with Python codebases.
Run the following three commands:
poetry install: this will install all the Python dependencies needed to run the application.
poetry run task migrate: this will run all the database migrations to set up the database tables. The default database engine is set to SQLite but can easily be changed using application settings.
poetry run reflex init: this is a one-time command to initialize your project to work with Reflex.
poetry run task server in the terminal!
You should now be able to visit the application in the browser at
poetry run task lint in the project directory.
ruff is used to ensure quality checks on Python codebases. It can point out
issues related to style (eg. if some code is not conformant to PEP-8) or for
discovering errors that would otherwise only be discovered at runtime (eg.
NameError). It's also much faster than the other Python tools for the same
black is a code formatter for Python. If you've worked in a team of software developers, you've most likely ran into formatting issues at one time or another. black puts an end to such discussions by choosing a formatting style for you.
isort is responsible for sorting imports in Python code. This keeps the upper-most section of the file clean and consistent across the entire codebase.
These three tools have also been installed as pre-commit hooks. If you set up
pre-commit as described in the previous section, all these linters will run
sequentially whenever you run
git commit. Any violations will prevent you from
poetry run task test in the project directory.
This will run all the database migrations on the test database and then run the
entire test suite using
pytest is an excellent framework for writing
better tests in Python. It is widely used in the Python community and has a rich
plugin system which application developers can benefit from.
At this point you should have a basic but functioning application running on your machine.
Check the post-installation steps for what you can do next!