Traditionally, there is considerable friction for developers when setting up development environments

Overview

Table of Contents

I. Overview
   A. Why you care
   B. What you will learn
II. How this training is structured
III. Requirements
IV. Overview of Development containers, GitHub Codespaces And Visual Studio Code
   A. Development Container
   B. Visual Studio Code
   C. GitHub Codespaces
V. Challenges
   A. Challenge1
   B. Challenge2
   C. Challenge3
   D. Challenge4
   E. Challenge5

Overview

Why you care

Traditionally, there is considerable friction for developers when setting up development environments. It is not uncommon for devs new to projects to spend days updating their environment before being able to start contributing to the project.

The more complex the requirements, the greater the friction. Consider the following 2 examples:

  1. Configuring a local Kubernetes development environment with the following:
  • Grafana
  • Prometheus
  • Fluentbit
  1. A Python API with:
  • The current version of Python
  • Debugging configured
  • Pytest
  • Flask

The above are 2 very real examples. The Retail Dev Crew team in CSE has been working with some of the largest Kubernetes deployments in the world. The dev environment includes everything listed above in example #1 plus much more. Despite the complex dev environment, the team prides itself upon new devs creating a PR on their first day. This is only possible because the Retail Dev Crew's use of development containers and GitHub Codespaces.

Python environments are notoriously challenging to configure. This is especially true with regard to debugging.

A large blocker to contributing to OSS projects is configuring the development environment. Imagine being able to instantiate a fully-configured development environment with the click of a button. That is the promise of development containers and GitHub Codespaces.

What you will learn

If you complete this self-directed training, you will:

  • Learn what development containers are
  • Learn what GitHub Codespaces are
  • Understand the relationship between Visual Studio Code, development containers and GitHub Codespaces
  • Learn how to build devcontainers
    • Using an existing docker image
    • Using the commands
      • onCreateCommand
      • postCreateCommand
      • postStartCommand
    • Creating a custom docker image
    • Updating the developer experience
      • Installing extensions
      • dotfiles
  • Patterns and best practices working with development containers and GitHub Codespaces

How this training is structured

This GitHub repository has a master branch and a collection of solution branches.

The master branch contains the following:

  • Readme.md - The main training file. Start here.
  • Challenges/* - The challenge files for this training. Each Challenge file will contain some learnings/background on the challenge, the challenge itself and, optionally, some helpful hints.
  • api/math_api.py - A very simple python Flask REST API
  • tests/api/test_math_api.py - Pytest unit tests
  • requirements.txt and dev_requirements.txt - Python requirements files contining the dependencies for the application and application development environment
  • math.http - A manual test file for use in Challenge 5

Each challenge has its own solution branch. Use your git client to open each Solution branch. For example:

git checkout Solution1

Each branch contains the following:

  • Solution(1-N).md - File describing the solution. This file may also contain a "From the Field" section where we list some of the learnings the CSE Retail Dev Crews team has had working with GitHub codespaces with our largest customers
  • The solution configured in the .devcontainer folder
  • Solution(1-N).mp4 - A video outlining a solution to the challenge. Open the videos from the file system, not Visual Studio Code

Requirements

You will need the following to complete the development container challenges in this training (see detailed installation instructions here):

  • Docker for Windows/Mac/Linux
  • Visual Studio Code

You will need to be enabled for GitHub Codespaces in order to complete the codespaces challenges. (see documentation here about getting access to Codespaces)

Overview of Development containers, GitHub Codespaces And Visual Studio Code

The goal of these technologies is to allow developers to define a fully-configured development environment, run it in a container and develop against it with Visual Studio Code running as a client application or running in the browser. This section will provide a high-level overview of these technologies and how they interrelate. You will find links to more information throughout this section.

Development Container

As noted above, a development container is a fully-featured development environment running in a container. The development container is a Docker container running locally or remotely that, at a high-level, contains the following:

  • All the application dependencies - Defined in a Docker image, Dockerfile or docker-compose file and potentially updated via scripts called by well-defined hooks.
  • The application code - mounted, copied or cloned into the container
  • Visual Studio Code Server - configured with the appropriate Visual Studio Code Extensions required to develop

Default Images can be used for general development. However, for a more productive development experience, you will likely want to define your own development containers. The configuration for the development container is in a devcontainer.json file which exists either at the root of the project or under a .devcontainer folder at the root. From the field: We always put the devcontainer.json file under a .devcontainer folder. We do that because we always have additional files that accompany the devcontainer.json file. These files include bash scripts and a Dockerfile. We will get into more details about these files later. During the challenges in this training you will explore and learn the common configuration patterns in a devcontainer.json file. For the time being, we will show you a very simple example of a devcontainer.json file taken from the documentation:

{
  "image": "mcr.microsoft.com/vscode/devcontainers/typescript-node:0-12",
  "forwardPorts": [3000],
  "extensions": ["dbaeumer.vscode-eslint"]
}

Again, we will explore each of the above in more detail in the challenges. For now, it is enough to understand that the devcontainer.json points to an existing typescript-node image. This is the image that will be used when starting the developer (Docker) container. The configuration further specifies that port 3000 should be forwarded from the container to the host. Lastly, it specifies that a linting extension should be installed in the VS Code Server running in the developer container.

Visual Studio Code

Visual Studio Code has a Remote-Containers Extension that enables the use of a Docker container as a fully configured development environment. This is enabled through a client-server architecture. As noted above, running development containers have a Visual Studio Code Server running in them. The Visual Studio Code Client can access a running container or can create an instance of a new development container and connect to it.

The challenges will mainly be using Visual Studio Code to create and run development containers.

GitHub Codespaces

GitHub Codespaces enables exposing a fully configured development environment for GitHub repositories. This can be used for anthing from new feature development to code reviews. Codespaces extends the use of development containers by providing a remote hosting environment for them. Developers can simply click on a button in GitHub to open a Codespace for the repo. Behind the scenes, GitHub Codespaces is:

  • Spinning up a VM
  • Shallow cloning the repo in that VM. The shallow clone pulls the devcontainer.json onto the VM
  • Spins up the development container on the VM
  • Clones the repository in the development container
  • Connects you to the remotely hosted development container - via the browser or GitHub

The Challenges - Building a Devcontainer

The challenges below are designed to provide a stepwise approach to building development containers. They start with the simplist approach, with each subsequent challenge teaching you a further aspect. Throughout the challeges, we will be providing real-world guidance that we have learned working with real customers in the field.

Owner
CSE Labs at Spark
CSE Labs at Spark
A simple and convenient build-and-run system for C and C++.

smake Smake is a simple and convenient build-and-run system for C and C++ projects. Why make another build system? CMake and GNU Make are great build

Venkataram Edavamadathil Sivaram 18 Nov 13, 2022
Tool to audit and fix Python project requirements.

Requirement Auditor Utility to revise and updated python requirement files.

Luis Carlos Berrocal 1 Nov 07, 2021
💻 Algo-Phantoms-Backend is an Application that provides pathways and quizzes along with a code editor to help you towards your DSA journey.📰🔥 This repository contains the REST APIs of the application.✨

Algo-Phantom-Backend 💻 Algo-Phantoms-Backend is an Application that provides pathways and quizzes along with a code editor to help you towards your D

Algo Phantoms 44 Nov 15, 2022
The Google Assistant on a rotary phone

Google Assistant Rotary Phone Shoutout to my dad who had this idea a year ago and I'm only now getting around to doing it. Notes This is the code used

rydercalmdown 10 Nov 04, 2022
Mute your mic while you're typing. An app for Ubuntu.

Hushboard Mute your microphone while typing, for Ubuntu. Install from kryogenix.org/code/hushboard/. Installation We recommend you install Hushboard t

Stuart Langridge 142 Jan 05, 2023
Project Interface For nextcord-ext

Project Interface For nextcord-ext

nextcord-ext 1 Nov 13, 2021
Easy to use phishing tool with 65 website templates. Author is not responsible for any misuse.

PyPhisher [+] Description : Ultimate phishing tool in python. Includes popular websites like facebook, twitter, instagram, github, reddit, gmail and m

KasRoudra 1.1k Dec 31, 2022
CoreSE - basic of social Engineering tool

Core Social Engineering basic of social Engineering tool. just for fun :) About First of all, I must say that I wrote such a project because of my int

Hamed Mohammadvand 7 Jun 10, 2022
Tool to automate the enumeration of a website (CTF)

had4ctf Tool to automate the enumeration of a website (CTF) DISCLAIMER: THE TOOL HAS BEEN DEVELOPED SOLELY FOR EDUCATIONAL PURPOSE ,I WILL NOT BE LIAB

Had 2 Oct 24, 2021
A fast python implementation of DTU MVS 2014 evaluation

DTUeval-python A python implementation of DTU MVS 2014 evaluation. It only takes 1min for each mesh evaluation. And the gap between the two implementa

82 Dec 27, 2022
Paprika is a python library that reduces boilerplate. Heavily inspired by Project Lombok.

Image courtesy of Anna Quaglia (Photographer) Paprika Paprika is a python library that reduces boilerplate. It is heavily inspired by Project Lombok.

Rayan Hatout 55 Dec 26, 2022
Keyboard Layout Change - Extension for Ulauncher

Keyboard Layout Change - Extension for Ulauncher

Marco Borchi 4 Aug 26, 2022
Modern API wrapper for Genshin Impact built on asyncio and pydantic.

genshin.py Modern API wrapper for Genshin Impact built on asyncio and pydantic.

sadru 212 Jan 06, 2023
A10 cipher - A Hill 2x2 cipher that totally gone wrong

A10_cipher This is a Hill 2x2 cipher that totally gone wrong, it encrypts with H

Caner Çetin 15 Oct 19, 2022
HatAsm - a HatSploit native powerful assembler and disassembler that provides support for all common architectures

HatAsm - a HatSploit native powerful assembler and disassembler that provides support for all common architectures.

EntySec 8 Nov 09, 2022
Small C-like language compiler for the Uxn assembly language

Pyuxncle is a single-pass compiler for a small subset of C (albeit without the std library). This compiler targets Uxntal, the assembly language of the Uxn virtual computer. The output Uxntal is not

CPunch 13 Jun 28, 2022
This directory gathers the tools developed by the Data Sourcing Working Group

BigScience Data Sourcing Code This directory gathers the tools developed by the Data Sourcing Working Group First Sourcing Sprint: October 2021 The co

BigScience Workshop 27 Nov 04, 2022
A tool converting rpk (记乎) to apkg (Anki Package)

RpkConverter This tool is used to convert rpk file to Anki apkg. 如果遇到任何问题,请发起issue,并描述情况。如果转换rpk出现问题,请将文件发到邮箱 ssqyang [AT] outlook.com,我会debug并修复问题。 下

9 Nov 01, 2021
京东自动入会获取京豆

京东入会领京豆 要求 有一定的电脑知识 or 有耐心爱折腾 需要Chrome(推荐)、Edge(Chromium)、Firefox 操作系统需是Mac(本人没在m1上测试)、Linux(在deepin上测试过)、Windows 安装方法 脚本采用Selenium遍历京东入会有礼界面,由于遍历了200

Vanke Anton 500 Dec 22, 2022
Ingest openldap data into bloodhound

Bloodhound for Linux Ingest a dumped OpenLDAP ldif into neo4j to be visualized in Bloodhound. Usage: ./ldif_to_neo4j.py ./sample.ldif | cypher-shell -

Guillaume Quéré 71 Nov 09, 2022