Gitlab Ci Run Python Script

To run a Python script, just type python and then the script's file name. You must be in the same directory as the script, otherwise you must give python the relative path to the script. This means that in order to run python scripts in the lt-maker directory, you should run python from within the lt-maker directory. Python Command Not Found. The.python:build job template provides an end-to-end distribution build configuration, effectively running the following command to build a project: python -m build -sdist -wheel. The outputs are uploaded as job artifacts. The following variables can be used to configure the build. This page contains links to a variety of examples that can help you understand how to implement GitLab CI/CD for your specific use case. Examples are available in several forms. As a collection of:.gitlab-ci.yml template files maintained in GitLab, for many common frameworks and programming languages. Repositories with example projects for. To run these tests automatically when you push code to your repository, add the following job to your.gitlab-ci.yml. Test:pytest: image: python:3.6 script: - pip install pytest -quiet - pytest. Pytest will automatically discover all test files in your project (all files named test.py.

Gitlab Ci/cd Run Python Script
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How does GitLab integrate with Maven?

Create the simple Maven dependency

Log in to your GitLab account.
Create a new project by selecting Import project from ➔ Repo by URL.
Click Create project.

How do I run a Python script from GitLab?

Automating python scripts to run by GitLab CI (Runner) needs to configure with “….In order to schedule a pipeline:

Navigate to your project’s CI / CD > Schedules and click the New Schedule button.
Fill in the form.
Hit Save pipeline schedule for the changes to take effect.

How do I deploy a GitLab project?

Using GitLab to deploy project pages

Step 1: Create a repository for your project pages.
Step 2: Add content to the repository.
Step 3: Add continuous integration through .
Step 4: Deploy and test your new project pages.

How do you write CI CD in GitLab?

Get started. CI/CD concepts Migrate from CircleCI Migrate from Jenkins Enable or disable CI/CD.
Pipelines.
Choose when jobs run Access a terminal for a running job Format scripts and job logs Git submodules.
Variables.
Environments and deployments.
Runners.
Cache and artifacts.
.gitlab-ci.yml.

How do you continuously deploy?

Moving from continuous delivery to continuous deployment

Emphasize a culture of continuous integration.
Make sure you have good test coverage (and good tests too!)
Adopt real-time monitoring.
Review your post-deployment tests.
Get your QA team to work upstream.
Drop the traditional release notes.

Is continuous delivery is different from continuous deployment?

The key difference is that with Continuous Deployment, your application is run through an automated pipeline workflow. Whereas with Continuous Delivery, your application is ready to be deployed whenever your team decides it’s time to do so.

This blog specifies how to automate python scripts to run by GitLab CI. Inthe following, I will talk about each element of the configuration with“.gitlab-ci.yml”, manage environments with anaconda and “environment.yml”, andsettings on GitLab.

Requirements

Before all, I would like to specify my working environment.

OS: Debian 8
GitLab Community Edition 10.8.0 (GitLab Installation)
GitLab Runner (GitLab Runner Installation)
Python 3.6.4

Project structure

Using GitLab CI to configure your jobs

.gitlab-ci.yml is used by GitLab CI to manage your project’s jobs. It isplaced in the root of your repository and contains definitions of how yourproject should be built. On any push to your repository, GitLab will look forthe .gitlab-ci.yml file and start jobs on CI according to the contents ofthe file, for that commit.

Following is one example:

In this example, there are several parts: stages, image, stage, script,only, tags. I’ll introduce them one by one.

`stages`

stages is used to define stages that can be used by jobs and is definedglobally.

The specification of stages allows for having flexible multi stage pipelines.The ordering of elements in stages defines the ordering of jobs’ execution:

Jobs of the same stage are run in parallel.
Jobs of the next stage are run after the jobs from the previous stage completesuccessfully.

In the example, we have 2 stages ‘test’ and ‘report’. The jobs of stage ‘test’will run before running the jobs of stage ‘report’.

`image`

This allows to specify a custom Docker image that can be used for time of thejob. In our case, we need to use connect Teradata which officially supports onlyCentOS and RHEL Linux distributions, so we built upon Jeremy Marshall’sdocker-teradata-client container and moble’s miniconda-centoscontainer.

If the configuration interests you, more information here.

`stage`

Gitlab Ci/cd Run Python Script

stage is defined per-job and relies on stages which is defined globally. Itallows to group jobs into different stages, and jobs of the same stage areexecuted in parallel.

In the example, the job in ‘tests’ corresponds the stage ‘test’, the job in‘weekly_job’ corresponds the stage ‘report’.

`script`

script is the only required keyword that a job needs. It’s a shell scriptwhich is executed by the CI.

The scripts in ‘tests’ update pip, install packages in requirements.txt with pip,and discover unit tests that ends with ‘_test.py’.

We created a conda environment quietly from file jobs/environment.yml (I’ll talkabout this file in the next part), then switching to the new environment whichis defined by the file, and run python script jobs/weekly_job.py by python.

`only`

only defines the names of branches and tags for which the job will run.

There are a few rules that apply to the usage of job policy:

only is inclusive. If only is defined in a job specification, the ref isfiltered by only.
only allows the use of regular expressions.
only allows to specify a repository path to filter jobs for forks.

In addition, only allows the use of special keywords. For example, variableskeyword is used to define variables expressions, in other words you can usepredefined variables / project / group or environment-scoped variables to definean expression GitLab is going to evaluate in order to decide whether a jobshould be created or not; using refs to specify that a branch is pushed andscheduled pipelines.

In the example, the job only runs when it satisfies the following conditions:

value of variable $weekly_job is “yes”(use %variable% in windows batch and $env:variable in PowerShell)
following the scheduled pipelines
script is on the master branch

`tags`

tags is used to select specific Runners from the list of all Runners that areallowed to run this project.

Managing environments

With conda, you can create, export, list, remove and update environments thathave different versions of Python and/or packages installed in them. Switchingor moving between environments is called activating the environment. You canalso share an environment file.

Creating an environment from an environment.yml file

You can create an environment file manually to share with others.

An environment.yml file should specify environment’s name with name, anddependable packages with dependencies.