project-of-the-week/2023-01-11-github_actions-1.md at main · MekongDelta-mind/project-of-the-week · GitHub

DIY GitHub Actions (Part 1)

Goal: Learn about GitHub Actions and create examples and apply them in your future projects. At the end of the week, you should be familiar with GitHub Actions, and understand the basic concepts behind them.
Dates: from 11th to 17th January
Where: #project-of-the-week in DataTalks.Club (get in slack here: https://datatalks.club/slack.html)

For more information about the "Project of the Week" initiative at DataTalks.Club, see README.md.

If you want to receive reminders about this event, sign up here

Technologies

GitHub
Unit testing
Linting and formating libraries

Note: this is a suggested list of technologies, you can chose alternatives instead

Plan

This is a proposed plan only, you don’t have to follow it day-by-day.

Day 1 (11 January, Wednesday)

Create a GitHub repository.
Run your first workflow through Quickstart.
Study the concepts behind Github Actions.
Share your progress in Slack and on social media.

Suggested materials

🗒️ GitHub Quickstart
🗒️ Understanding Github Actions

Found good materials? Create a PR with links!

Day 2 (12 January, Thursday)

Recap or finish studying GitHub about Actions.
Study about Triggering a workflow. You can check as well the GitHub Actions Tutorial by TechWorld with Nana.
Check suggested material related to building and testing.
Commit your changes.
Share your progress in Slack and on social media.

Suggested materials

🗒️ Triggering a workflow
🗒️ Automated building and testing in python
📺 GitHub Actions Tutorial

Found good materials? Create a PR with links!

Day 3 (13 January, Friday)

Create your own project that you will use for testing (See suggestions below). You can use a Machine Learning project from previous project-of-the-week. If you want to create your own, we have a list of some datasets for you to use.
Commit your changes.
Share your progress in Slack and on social media.

Suggested materials

💻 Frontend for your ML model
💾 list of some datasets

Found good materials? Create a PR with links!

Day 4 (14 January, Saturday)

Finish your project set-up.
Create your linters and tests. (see suggestions bellow)
Commit your changes.
Share your progress in Slack and on social media.

Suggested materials

📺 Testing code with pytest
🏫 Linting and formatting: DataTalksClub MLops Course
📺 Introduction to Linting and formatting
🗒️ Testing python applications with pytest

Found good materials? Create a PR with links!

Day 5 (15 January, Sunday)

Edit your GitHub workflow according to GitHub actions guide. (make sure pushing a change triggers the workflow).
Push example changes from your code and check your linters and tests.
Commit your changes.
Share your progress in Slack and on social media.

Suggested materials

📺 GitHub Actions Tutorial
🗒️ Automated building and testing in python
📺 CI/CD youtube tutorial
📺 Testing code with pytest
🏫 Linting and formatting: DataTalksClub MLops Course

Found good materials? Create a PR with links!

Day 6 (16 January, Monday)

Make sure pushing a change triggers the workflow
Make more examples that check your linters and tests.
Commit your changes.
Share your progress in Slack and on social media.

Suggested materials

🗒️ Automated building and testing in python
📺 CI/CD youtube tutorial

Found good materials? Create a PR with links!

Day 7 (17 January, Tuesday)

Continue exploring more about this topic
Polish the documentation for your project
Push your changes to GitHub
Share your progress in Slack and on social media
Give us feedback
Add the link to your project to this project of the week github page

Other useful materials

Datasets

💾 list of some datasets for your project

Materials legend:

🏫 Course
💾 Dataset
🗒️ Article
📺 Video tutorial
💻 Code

Projects

List of projects from our participants:

Project link 1
Project link 2
...
(Create a PR)

(We will put the projects here after the event finishes)