fa-models 1.0.23

The library describes the most common models used in trading systems. It is based on sqlmodel and offers many built-in features like serialization.

fa-models

A set of models often used for trading services. The library offers no algorithms - just models.

General

Run and compiled for Python 3.9.13.

Development

Installation as Consuming Developer

Simply run: pip install fa-models

Import in modules without the dash (e.g.): from famodels.signal import Signal

Setup as Contributor

Create the virtul environment: py -m venv .venv Start the Environment: ./.venv/Scripts/activate. Use deactivateto stop it. Update the PIP: py -m pip install --upgrade pip

All the required libraries must be listed in requirements.txt and installed by py -m pip install -r .\requirements.txt

To cleanup the environment run: pip3 freeze > to-uninstall.txt and then pip3 uninstall -y -r to-uninstall.txt

or pip3 install pip-autoremove

Build Library

Preqrequisite: make sure that you give your Operating System user the right to modify files in the python directory. The directory where pyhton is installed. Use python setup.py bdist_wheel to create the dist, build and .eggs folder.

Reference from a different project

In order to use your own version of the project - to maybe contribute to the library - simply clone the code from github into new directory. Then add the path of that new directory to the requirements.txt file of your project. Then change in fa-models whatever you recommend to improve. Don't forget the Open-Closed Principle: extend only (unless it requires a breaking change)

Releasing a new version

Install the tools build, twine and bumpver: python -m pip install build twine bumpver Upgrade the setuptools: pip install --upgrade setuptools

Delete any old files in the /dist folder.

Bump the version in pyproject.toml: bumpver update --patch

Build the project: python -m build

Check the distribution: twine check dist/*

Upload to test-pypi to validate: twine upload -r testpypi dist/*

Login with username: svabra (password should be known)

Finally, upload to pypi production: twine upload dist/*