datastreamcorelib
Core helpers and Abstract Base Classes for making use of ZMQ nice, easy and DRY.
You should probably look at https://gitlab.com/advian-oss/python-datastreamservicelib and https://gitlab.com/advian-oss/python-datastreamserviceapp_template unless you’re working on an adapter for yet unsupported eventloop.
Docker
For more controlled deployments and to get rid of “works on my computer” -syndrome, we always make sure our software works under docker.
It’s also a quick way to get started with a standard development environment.
SSH agent forwarding
We need buildkit:
export DOCKER_BUILDKIT=1
And also the exact way for forwarding agent to running instance is different on OSX:
export DOCKER_SSHAGENT="-v /run/host-services/ssh-auth.sock:/run/host-services/ssh-auth.sock -e SSH_AUTH_SOCK=/run/host-services/ssh-auth.sock"
and Linux:
export DOCKER_SSHAGENT="-v $SSH_AUTH_SOCK:$SSH_AUTH_SOCK -e SSH_AUTH_SOCK"
Creating a development container
Build image, create container and start it:
docker build --ssh default --target devel_shell -t datastreamcorelib:devel_shell . docker create --name datastreamcorelib_devel -v `pwd`":/app" -it -v /tmp:/tmp `echo $DOCKER_SSHAGENT` datastreamcorelib:devel_shell docker start -i datastreamcorelib_devel
pre-commit considerations
If working in Docker instead of native env you need to run the pre-commit checks in docker too:
docker exec -i datastreamcorelib_devel /bin/bash -c "pre-commit install --install-hooks" docker exec -i datastreamcorelib_devel /bin/bash -c "pre-commit run --all-files"
You need to have the container running, see above. Or alternatively use the docker run syntax but using the running container is faster:
docker run -it --rm -v `pwd`":/app" datastreamcorelib:devel_shell -c "pre-commit run --all-files"
Test suite
You can use the devel shell to run py.test when doing development, for CI use the “tox” target in the Dockerfile:
docker build --ssh default --target tox -t datastreamcorelib:tox . docker run -it --rm -v `pwd`":/app" `echo $DOCKER_SSHAGENT` datastreamcorelib:tox
Production docker
There’s a “production” target since it’s our standard pattern, however this library does not yet expose any CLI tools so the production target is kinda useless.
Local Development
TLDR:
Create and activate a Python 3.9 virtualenv (assuming virtualenvwrapper):
mkvirtualenv -p `which python3.9` my_virtualenv
change to a branch:
git checkout -b my_branch
install Poetry: https://python-poetry.org/docs/#installation
Install project deps and pre-commit hooks:
poetry install pre-commit install --install-hooks pre-commit run --all-files
Ready to go.
Use Python 3.9 for development since it’s the lowest supported version so you don’t accidentally use features only available in higher versions and then have to re-do everything when CI tests fail on 3.9.
Remember to activate your virtualenv whenever working on the repo, this is needed because pylint and mypy pre-commit hooks use the “system” python for now (because reasons).
Running “pre-commit run –all-files” and “py.test -v” regularly during development and especially before committing will save you some headache.
Metadata
Release files for datastreamcorelib 1.7.1
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
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Total release size: 30.3 kB
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