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Gitlab Ci Python Docker

Describe your question in as much detail as possible:
In my AWS SAM build-and-package step, the docker container fails to pull an image of python3.9. This issue suddenly started happening, and was note occurring in previous builds. Not sure if it’s an issue w/ docker containers, or not?

Python-gitlab is a Python package providing access to the GitLab server API. It supports the v4 API of GitLab, and provides a CLI tool (gitlab).Installation. Dockerized Gitlab CI runner for Python testing. Contribute to cardoe/docker-gitlab-ci-runner-python development by creating an account on GitHub. Oct 28, 2020 How to improve docker build time by leveraging different caching strategies while using Docker in Docker. Illustrated using GitLab CI and Kubernetes. Or compile the dependencies into a Python.

  • What are you seeing, and how does that differ from what you expect to see?
    I’m expecting the build to be successful, like below:

  • Consider including screenshots, error messages, and/or other helpful visuals
    Below is what I’m currently seeing:

  • What version are you on? Are you using self-managed or GitLab.com?

    • GitLab (Hint: /help): Yes, on Gitlab.com
    • Runner (Hint: /admin/runners): Shared runners for this project is enabled

  • Add the CI configuration from .gitlab-ci.yml and other configuration if relevant (e.g. docker-compose.yml)
    https://gitlab.com/qzeng96/vibes/-/blob/main/.gitlab-ci.yml

  • What troubleshooting steps have you already taken? Can you link to any docs or other resources so we know where you have been?
    • Attempted changing image to python:3.9, rather than the current value.

Gitlab Ci Python Docker Examples

Thanks for taking the time to be thorough in your request, it really helps!

In the previous post I described how to run own GitLab server with CI runner.In this one, I’m going to walk through my experience of configuring GitLab-CI for one of my projects.I faced few problems during this process, which I will highlight in this post.

Some words about the project:

  • Python/Flask backend with PostgreSQL as a database, with the bunch of unittests.
  • React/Reflux in frontend with Webpack for bundling. No JS tests.
  • Frontend and backend are bundled in a single docker container and deployed to Kubernetes

Building the first container

First thing after importing repository into gitlab we need to create .gitlab-ci.yml.Gitlab itself has a lot of useful information about CI configuration,for example this andthis.

Previously I used to do following steps to test/compile/deploy manually:

  • npm run build - to build all js/css
  • build.sh - to build docker container
  • docker-compose -f docker-compose-test.yml run –rm api-test nosetests
  • deploy.sh - to deploy it
Python

Everything is pretty common for most of the web projects.So, I started with a simple .gitlab-ci.yml file, trying to build my python code:

Gitlab
  • $CI_BUILD_TOKEN - is a password for my docker registry, saved in projects variables in GitLab project settings

And it actually worked fine. I got my docker container built and pushed to the registry.Next step was to be able to run tests. This is where things became not so obvious.For testing, we need to add another stage to our gitlab-ci file.

Gitlab Ci Python Docker Code

Testing. First try

After reading posts like thisI thought that it will be as easy as declaring service and adding test stage:

Tutorial

But it didn’t work. As far as I understood it, it’s because of docker-in-docker runner.Basically, we have 2 containers - docker:latest and postgresql:9.5, and they are linked perfectly fine.But then we’re bootstrapping our own container, inside this docker container.And this container can’t use docker links to access postgres, because its outside of its scope.

Testing. Second try

Then I tried to use my container as and image for the test stage and service declared in test stage itself, like this:

But it also didn’t work because of authentication.

My docker registry needs authentication which I do in before_script stage. But before_script is being called after the services.I assume that this method should work for public images.

Testing. Third try. Kinda working solution

So I decided to try to use docker-compose in tests as I was doing manually since.Docker-compose should be able to run and link everything together.And since this page in documentation says:

GitLab CI allows you to use Docker Engine to build and test docker-based projects.

This also allows to you to use docker-compose and other docker-enabled tools.

I was very confused when I was not able to use docker-compose, since docker:latest image has no docker-compose installed.I spent some time googling and trying to install compose inside the container,and ended up using image jonaskello/docker-and-compose instead of the recommended one.

So my test stage changed to this:

This actually worked, but from time to time I was seeing weird race conditions during database provisioning.It’s not a big problem, and could be fixed easily. But I decided to try one more approach.

Testing. Final version

This time I decided to run postgres container during the test stage and link it to my test container.This requires to provide additional configuration to postgres container, but still this way is the closest to the original services approach.

Now, when we have our python container built and tested we need to add one more thing.We need to compile our javascript and css and put it into release container.This stage is actually going before the build.To be able to use files between stages we need to use some cache.In my case we need to cache only one directory.The one where webpack produces compiled files - src/static/dist.

Cache is described in more details in official docs

Gitlab Ci Python Docker Online

As for release stage I’m simply going to tag container with build number and push it back to the registry.

Gitlab Ci Docker Build

Now we have a working CI pipeline which can build a container, run tests against this container and then push it to the registry.So far so good. The only problem is that all of this takes very long time. For my project, it takes about 20 minutes to finish all these stages.Most of the time is spent on building docker layers, downloading python and npm packages and installing it.Next post will probably be about reducing this time by using some local caching services.