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Code versioning and other continuous integration helpers for Gitlab CI/CD pipelines

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Continuous Integration & Code Versioning for Gitlab CI/CD pipelines

Shared repository for base images to use in gitlab CI/CD pipelines.

What does it do?

tl/dr Updates the semantic version of your code when you release it. Bumps versions for the languages golang, Node, R, Python & SBT ie Scala.

How does it do it?

On a merge to the default branch (nowadays in gitlab this is called main) it updates the semantic version of the code, creates a tag based on that version and then creates the next snapshot version and rebases back on to develop in readiness for the next release.
Note: It doesn't have to be main but can be whatever branch you want as long as you have configured your default branch correctly.

How do I use it via a CI file?

All the language subfolders contain an example of a gitlab CI file. Use one of the language based images in your ci process and then to update the version/release the code use the cictl command to release it. For example, for python you could use the image registry.gitlab.com/medicines-discovery-catapult/informatics/docker-images/ci/python:3.12 and release/version with cictl exec release python src.

How do I get a patch/minor/major semantic version change

Prefix the branch name following these rules:

  • For major version bump eg 2.1.3 to 3.0.0 prefix the branch name with breaking-change or major breaking-change/whatever-you-want major/whatever-you-want
  • For minor version bump eg 2.1.3 to 2.2.0 prefix the branch name with feature or minor feature/whatever-you-want minor/whatever-you-want
  • For patch version bump it is the default behaviour eg 2.1.3 to 2.1.4 call-the-branch anything

Gotchas

  • If using these images for your CI process, it is recommended that you always create merge commits, and never squash your commits. These are the default options in gitlab.
  • Ensure that the push rules in your Repository>Push rules settings allow unverified users to push code. This is so that the bot user can tag & rebase the branch.
  • Make sure you have created an access token called CI_TOKEN which is given maintainer access and read/write permissions.
  • Ensure your project is allowed access to the CI images repo and, if you are using or pushing any packages, to the private gitlab package registry. Look at the CI/CD>Token Access settings.
  • If you are running gitlab sast pipelines and using a private pypi repo then make sure to tell the CI stage using the PIP_INDEX_URL variable eg
dependency_scanning:
  stage: test
  allow_failure: false
  inherit:
    default: false
  variables:
    SECURE_LOG_LEVEL: "debug"
    PIP_INDEX_URL: https://gitlab-ci-token:${CI_JOB_TOKEN}@gitlab.com/api/v4/projects/${REGISTRY_HOST_PROJECT_ID}/packages/pypi/simple
  • If you want to access any of the cictl commands beyond release then you may need to ensure that the correct env vars are available by running this command for the language in question: source <(cictl config env golang).
  • The tag names for images do not always reflect the version of the language they are built on. Some, for example R, are built on whatever the latest release of the R language is. Exceptions are the sbt:jdk-14, node:lts-20 and the python: 3.x tags.

General project structure

All images:

  • Are based on debian.
  • Contain the cictl command line interface tool. This is in the /scripts folder and on the path.
  • Contain useful scripts in the /scripts folder and available on the PATH.
  • Have an example .gitlab-ci.yml file within their folder.
  • May come pre-installed with useful things. For example, the R image is based on the R runner which has BioConductor and other packages pre-installed.
  • To test the CI process you can see the instructions below but there is also a CI Test repo which has a specific branch for each language to try out the branch to develop to master merge process.

Each language has a folder with a Dockerfile to create the image, a sample CI file and a release.sh file for legacy purposes. Originally the CI processes were written in bash scripts but they are now python based. Language specific commands are in the lib folder.

├── cictl          # Main file to run CI commands. Figures out the command, language and calls the appropriate method
├── debian
│   ├── Dockerfile
│   └── release.sh
├── example.env    # Copy to .env, environment variables used by docker when running a CI container
├── golang
│   ├── Dockerfile
│   ├── gitlab-ci.example.yml
│   ├── godoc.sh # Utility script to generate godocs
│   └── release.sh
├── lib            # Language specific CI commands. Tell cictl which language to use eg cictl exec release node 
│   ├── common.py # Common CI commands shared between the language specific libs
│   ├── golang.py
│   ├── node.py
│   ├── python.py
│   └── sbt.py
├── node
│   ├── Dockerfile
│   ├── gitlab-ci.example.yml
│   └── release.sh
├── python
│   ├── Dockerfile
│   ├── gitlab-ci.example.yml
│   └── release.sh
├── sbt
│   ├── Dockerfile
│   ├── gitlab-ci.example.yml
│   └── release.sh
├── r
│   ├── Dockerfile
│   ├── gitlab-ci.example.yml
│   └── release.sh

Usage

There are lots of commands, most of them are used internally by the release process, but you have access to them all if you need them.

cictl has the following commands:

  • get: get a resource.
  • create: create a resource.
  • config: configure your environment.
  • exec: execute an action.

cictl get can get the following resources:

  • latest-tag: gets the last git tag.
  • git-log: gets a formatted and sanitized git log which is safe for interacting with gitlab.
  • increment: interprets the git log between head and a given tag and returns an appropriate version increment.
  • next-tag: increments a given tag by a given amount.
  • short-sha: gets the short-sha of the latest commit.

cictl create can create the following resources:

  • release: creates a gitlab release against a given tag.
  • attachment: creates attachments on a gitlab release, given a tag and a file glob.

cictl config can configure the following resources:

  • git: configures git to use the ci user credentials (project token) and ensures we are up to date.
  • env: returns a set of environment variables to export. It should be used like source <(cictl config env <language(optional)>).
  • goprivate: writes credentials to the ~/.netrc file so that private go modules can be pulled. Must be used after source <(cictl config env golang).
  • pip configures pip to use an internal nexus host. - DEPRECATED

cictl exec executes the following:

  • rebase: performs a rebase of $REBASE_BRANCH, develop, or dev (in order of precedence) onto the $CI_COMMIT_BRANCH. Typically, this is performed during a release when the $CI_COMMIT_BRANCH is master (i.e. we've just merged develop into master, so the pipeline is running on master), so develop is rebased onto master.
  • version: performs various language dependent actions to increment the software version. If no language is specified, an empty commit is added and tagged with the given tag. Usage cictl exec version tag <language(optional)>.
  • release: performs various language dependent actions to perform a full release. This includes configuring the environment, committing to the codebase, creating gitlab releases and attachments, and rebasing. Usage cictl exec release <language(optional)>.

Additionally, the golang image contains a script to obtain the raw html required to make godocs. This is located under /scripts as godoc.sh.

The variables used in the CI process in gitlab can be accessed via the gitlab Admin CI/CD pages. It is important that the CI_READONLY_USER & CI_READONLY_TOKEN are for an actual current user and actually work! The default is the project_bot.

Custom CI Environment Variables

You can override the following CI environment variables through gitlab settings for your repo. CI_DOMAIN. The default is noreply.gitlab.mdcatapult.io.
CI_USER_EMAIL. The default is project_project_id_bot@CI_DOMAIN. The project_id can be found on the home page of your repository underneath the title.
eg project_702_bot@noreply.gitlab.mdcatapult.io. The CI pipeline will attempt to construct the correct email address for the CI_TOKEN that you created. If it gets it wrong you can set CI_USER_EMAIL with the correct one.
This bot email/user is used to tag and rebase the release. If you look at the release pipeline you will see things like

INFO:git.cmd:git config user.name project_52267953_bot -> 0
INFO:git.cmd:git config user.email project_52267953_bot@noreply.gitlab.mdcatapult.io -> 0

CI_READONLY_USER. Used to generate the netrc file for go private repo CI_READONLY_TOKEN. Used to generate the netrc file for go private repo

cictl config pip deprecation

You can create a pip config file use cictl config pip which was mainly used when MDC had an internal NEXUS package repository. We now have use gitlab for the package registry and recommend using the index-url and/or extra-index-url settings within the CI file itself like this:

test:
  stage: test
  script:
    - pip install -r requirements.txt --index-url https://gitlab-ci-token:${CI_JOB_TOKEN}@gitlab.com/api/v4/projects/${REGISTRY_HOST_PROJECT_ID}/packages/pypi/simple

Note that here we use a CI variable called REGISTRY_HOST_PROJECT_ID to hide the actual project id. Don't forget to allow your project repo access to your package repository via the CI/CD settings.

If you do have an internal Nexus based package repo and want to create the pip config file then note the following (plus the fact that it will be removed in a future release):
Set PACKAGE_PASSWORD to true if there is a password required to access the package repository and also set the NEXUS_PASSWORD, NEXUS_USERNAME and NEXUS_HOST variables. If you want to use pypi repo then do not set these variables.

Adding and updating images

Some background on what happens in teh build process: Each language folder, sbt, python etc, has a Dockerfile that defines what goes into each image. The Dockerfile defines a TAG variable to determine what version of the upstream image should be used. For example,

ARG TAG=latest
FROM python:$TAG

Within the projects .gitlab-ci.yml file there are various stages, eg python3.11 that define the actual tagged image to be built. In this example it builds a python:3.11 image:

python3.11:
  stage: build
  script:
    - |
      /kaniko/executor --context $CI_PROJECT_DIR --dockerfile python/Dockerfile \
      --build-arg TAG=3.11 \
      --destination $CI_REGISTRY_IMAGE/python:3.11 \
      --destination $CI_REGISTRY_IMAGE/python:3.11-$CI_COMMIT_REF_NAME

Within each Dockerfile it also copies the cictl script and the lib folder. It also copies the internal MDC ssl certificates (note: it's not clear if these certificates are needed since the images are not used to run any services on the MDC kube cluster).

If you want to change an existing build then change the kaniko --build-arg that contains the TAG to something else. If you want to add a completely new image then copy an existing build stage and change the kaniko command appropriately. There is usually an accompanying -dev stage for building images for branches.

Note that the CI release process is used to release these updated images.

Development & Testing CI pipelines

Requires python3.6+, virtualenv and docker. The example.env file contains all the gitlab builtin environment variables that these scripts make use of. They have been set to values suitable for testing against the CI Test repository.

# environment:
git clone git@gitlab.com:medicines-discovery-catapult/informatics/docker-images/ci.git
cd ci
virtualenv -p python3.7 venv
source venv/bin/activate
pip install -r requirements.txt

# testing the commands directly:
# (fill out the .env file first)
cp example.env .env
set -a; source .env; set +a
source <(./cictl config env)
./cictl create release $NEXT_TAG 

# building & pushing test images:
docker build --pull -f debian/Dockerfile -t registry.gitlab.com/medicines-discovery-catapult/informatics/docker-images/ci/debian:test .
docker push registry.gitlab.com/medicines-discovery-catapult/informatics/docker-images/ci/debian:test

# testing images with a local repo:
# (fill out the .env file first)
cp example.env .env
docker build --pull -f debian/node -t ci-node-test .
docker run -it -v $LOCAL_REPO:/repo -w /repo --env-file .env ci-node-test

In the docker build phase there are 6 images possible:

  • debian/Dockerfile
  • node/Dockerfile
  • golang/Dockerfile
  • python/Dockerfile
  • sbt/Dockerfile
  • r/Dockerfile

Make sure you choose the correct Dockerfile and tag before you push anything to the repo.

Running CI commands

From within a running CI container you can then test the cictl commands against the LOCAL_REPO. Remember that this will actually run things against the repo in gitlab so be careful. For example here we are testing the Aurac release pipeline which will bump versions, create a tag and release and attach the Aurac zip to it. Have a look an actual .gitlab-ci.yml file to see the commands that a CI pipeline is running. For example, in the Aurac release stage it executes:

/scripts/release.sh -b -r develop -u 'dist/browser-plugin/web-ext-artifacts/aurac-*.zip'

This release.sh script is in this repo in the node folder and just runs cictl exec release node "$@". Look at the cictl code in this repo's root folder to see what exec does. Basically it ends up calling the release method in the lib/node.py code. The same pattern is followed for all languages. You don't have to use /script/release.sh, it is just there for legacy and you can call the commands directly as shown below.

root@969f9dea6d82:/repo# cictl exec release node -b -r develop -u 'dist/browser-plugin/web-ext-artifacts/aurac-*.zip'

It might be easier to try the commands against a dummy repo that no-one cares about. There is also the CI test repo which is designed to work against a CI image in the registry. Clone the project, create a branch eg node-dev that will be using your new pipeline. Change some code on it, change the .gitlab-ci.yml file to use your CI image branch eg node:test, commit, push and watch the pipelines.

Troubleshooting

If you have problems running the commands locally then pay close attention to the logged output and double check your .env file. We have had issues where the python interpreter treats quoted strings with env vars literally and we had to remove the quotes and write them out long hand.

"project_${CI_PROJECT_ID}_bot" became "project_550_bot" etc.

Make sure that your CI_PROJECT_ID, CI_TOKEN & CI_PROJECT_PATH are correct and actually match the project that you are testing.

Remember this is all just code, none of it is magic.

Some notes on R

If you look at the R example CI file you will see that it includes package upload to Nexus. Gitlab doesn't support R packages yet and we recommend using the remotes package.

License

This project is licensed under the terms of the Apache 2 license, which can be found in the repository as LICENSE.txt