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LEARN OPEN SOURCE CONTRIBUTION

Open Source is the foundation of the modern internet. From the Linux kernel running on servers to the React components on your screen, nearly every piece of software depends on code written by a distributed community of strangers.

Learn Contribute to Open Source: From Zero to Open Source Contributor

Goal: Deeply understand the mechanics, culture, and social dynamics of open source software. You will go from being a passive user to an active contributor who understands how to navigate large codebases, communicate effectively with maintainers, and ship code that powers the world’s infrastructure.

Why Open Source Matters

Open Source is the foundation of the modern internet. From the Linux kernel running on servers to the React components on your screen, nearly every piece of software depends on code written by a distributed community of strangers.

Contributing to open source is not just about “fixing bugs”—it is the ultimate masterclass in software engineering.

  • You learn to read code written by world-class engineers.
  • You learn to communicate asynchronously and persuasively.
  • You build a reputation that transcends your current employer.
  • You understand the supply chain of the software you use daily.

It remains relevant because no single company can out-innovate the collective intelligence of the entire world.

Core Concept Analysis

To contribute effectively, you must understand the invisible machinery that keeps open source projects alive. It is 20% coding and 80% communication/process.

1. The Ecosystem of Actors

Open source is a social system first, technical second.

      ┌───────────────┐
      │  The Project  │
      └──────┬────────┘
             │
   ┌─────────┴─────────┐
   │                   │
   ▼                   ▼
┌──────────────┐    ┌──────────────┐
│  Maintainers │    │ Contributors │
│ (The Keepers)│    │ (The Givers) │
└──────┬───────┘    └──────┬───────┘
       │                   │
       │    ┌──────────────┴─┐
       └───►│ The Community  │◄──┐
            └──────┬─────────┘   │
                   │             │
            ┌──────▼──────┐      │
            │    Users    │──────┘
            │(The Consumers)
            └─────────────┘
  • Maintainers: They have the keys. Their scarcest resource is attention, not code. Your job is to save them time.
  • Contributors: People like you who propose changes.
  • Users: People who report bugs but don’t fix them.

2. The Contribution Flow (The “Happy Path”)

Understanding the mechanical flow of code is crucial. Most beginners get stuck on “Git” when the real problem is “Workflow”.

   [ Upstream Repo ] <──────────┐
  (Original Project)            │ 7. Merge
         │                      │
         │ 1. Fork              │
         ▼                      │
   [ Your Fork ] ───────────────┤
  (Your Copy on GitHub)         │ 6. Pull Request (PR)
         │                      │
         │ 2. Clone             │
         ▼                      │
   [ Local Repo ]               │
   (On your Machine)            │
         │                      │
         │ 3. Create Branch     │
         │ 4. Code & Commit     │
         │ 5. Push Branch       │
         └──────────────────────┘

3. The “Review Loop” (Where Dreams Die)

The Pull Request (PR) is not the end; it is the beginning of a conversation.

      You                       Maintainer
       │                            │
       ├─── [ PR Opened ] ─────────►│
       │                            │
       │◄── [ Request Changes ] ────┤ (1-3 weeks later)
       │                            │
       ├─── [ Push Fixes ] ────────►│
       │                            │
       │◄── [ "LGTM!" ] ────────────┤
       │                            │
       │◄── [ Merge ] ──────────────┤
       ▼                            ▼
   Celebration                  New Release

4. Semantic Versioning (SemVer)

You must understand when your change breaks things.

   v1.2.3
    │ │ └─ Patch: Bug fixes only (Safe to upgrade)
    │ └─── Minor: New features, backward compatible (Safe-ish)
    └───── Major: Breaking changes (Dangerous)
  • Breaking Change: Changing a function signature or removing a file.
  • Feature: Adding a new function.
  • Fix: Correcting internal logic without changing behavior.

5. Licenses (The Rules of Engagement)

Code without a license is not open source—it’s just code you can look at but can’t touch.

License Can Commercialize? Must Share Changes? Viral?
MIT Yes No No
Apache Yes No No
GPL Yes Yes Yes

Concept Summary Table

Concept Cluster What You Need to Internalize
The Forking Workflow You never write to the main repo directly. You copy it (fork), download it (clone), change it (branch), and offer it back (PR).
Async Communication No one is waiting for you. Responses take days. You must be clear, concise, and provide context (screenshots, logs) upfront.
Code Style & Linting Every project has a “voice”. If the project uses tabs, you use tabs. If they use semi-colons, you use semi-colons. Consistency > Personal Preference.
The “Diff” Mindset Maintainers review diffs, not whole files. Make your diffs clean. Don’t reformat the whole file if you only changed one line.
CI/CD Pipelines Robots check your code before humans do. If the build fails (red X), the maintainer won’t even look at it.

Deep Dive Reading by Concept

This section maps each concept from above to specific book chapters for deeper understanding.

Open Source Culture & History

Concept Book & Chapter
The Philosophy The Cathedral and the Bazaar by Eric S. Raymond — Ch. 2: “The Mail Must Get Through”
Social Dynamics Producing Open Source Software by Karl Fogel — Ch. 2: “Getting Started”

Technical Mechanics

Concept Book & Chapter
Git & Workflows Pro Git by Scott Chacon — Ch. 5: “Distributed Git”
Maintenance The Art of Readable Code by Boswell & Foucher — Ch. 1: “Code Should Be Easy to Understand”

Essential Reading Order

  1. Foundation: Pro Git (Ch. 1-3) - You must master the tool.
  2. Culture: Producing Open Source Software (Ch. 2) - Understand the human side.
  3. Practice: Start with Project 1 below.

Project List

We will not just “contribute” blindly. We will build tools to help contributors and simulate the contribution environment to master the mechanics safely.

Project 1: The Local “Fork” Simulator

  • File: LEARN_OPEN_SOURCE_CONTRIBUTION.md
  • Main Programming Language: Bash (Shell Scripting)
  • Alternative Programming Languages: Python, Go
  • Coolness Level: Level 2: Practical but Forgettable
  • Business Potential: 1. The “Resume Gold” (Git mastery is essential)
  • Difficulty: Level 1: Beginner
  • Knowledge Area: Version Control / Git Internals
  • Software or Tool: Git
  • Main Book: “Pro Git” by Scott Chacon

What you’ll build: A shell script that creates two local directories, upstream_repo and my_fork, initializes them as git repositories, and simulates the entire contribution lifecycle (fork, clone, branch, push, merge-conflict resolution) entirely on your local machine without needing GitHub.

Why it teaches Open Source: Beginners are terrified of “messing up” the main repo. This project proves that origin is just another folder. You’ll learn that “Pull Requests” are just a request to merge branch A into branch B, and you’ll practice handling the dreaded “Merge Conflict” safely.

Core challenges you’ll face:

  • Simulating Remote: Treating a local folder as a “remote” server.
  • The Upstream Drift: Simulating the main repo moving forward while you are working on your feature.
  • Rebasing: Learning to git rebase your changes on top of the new upstream work.

Key Concepts:

  • Remotes: Pro Git Ch. 2.5 “Working with Remotes”
  • Branching: Pro Git Ch. 3.2 “Basic Branching and Merging”

Difficulty: Beginner Time estimate: Weekend Prerequisites: Basic Terminal usage

Real World Outcome

You’ll have a script simulate_contribution.sh that, when run, creates a sandbox environment.

Example Output:

$ ./simulate_contribution.sh
[+] Creating 'upstream' repo (The Maintainer's code)...
[+] Creating 'my_fork' (Your copy)...
[+] Simulating Maintainer commit: "Added README"
[+] You are creating feature branch 'fix-typo'...
[!] ALERT: Maintainer pushed new code while you were working!
[+] Syncing your fork...
[+] Rebasing your changes...
[SUCCESS] Your history is clean and ready for a PR!

The Core Question You’re Answering

“What actually happens when I ‘Fork’ and ‘Clone’?”

Before you write code, sit with this: There is no magic cloud. A “remote” is just another git repository that happens to be on someone else’s computer.

Concepts You Must Understand First

  1. Git Remotes
    • What is origin vs upstream?
    • Book Reference: “Pro Git” Ch. 2.5
  2. The Graph
    • How does a commit point to its parent?
    • Book Reference: “Pro Git” Ch. 1.3

Questions to Guide Your Design

  1. How do I link two local repos?
    • Can git remote add take a file path instead of a URL? (Yes!)
  2. How do I simulate a conflict?
    • I need to write to file.txt in repo A, and write to the same line in file.txt in repo B.

Thinking Exercise

Draw the DAG (Directed Acyclic Graph)

Draw circles for commits.

  1. Draw the state where upstream and fork are identical.
  2. Draw upstream adding a commit (moving forward).
  3. Draw fork adding a different commit (diverging).
  4. Draw what a merge looks like vs a rebase.

The Interview Questions They’ll Ask

  1. “What is the difference between git merge and git rebase?”
  2. “How do you handle a merge conflict in a file you didn’t touch?”
  3. “What is a ‘fast-forward’ merge?”

Hints in Layers

Hint 1: Setup Create two folders: mkdir upstream fork. Run git init --bare in upstream? Or just git init? (Hint: A remote you push to usually needs to be --bare or configured to accept pushes).

Hint 2: Linking Inside fork: git remote add upstream ../upstream.

Hint 3: Causing Trouble To create a conflict, edit line 1 of readme.md in upstream, commit. Then edit line 1 of readme.md in fork, commit. Try to merge.

Hint 4: Resolution Use git rebase upstream/main to replay your work on top of theirs.

Project 2: The “Bug Reproduction” Script

  • File: LEARN_OPEN_SOURCE_CONTRIBUTION.md
  • Main Programming Language: JavaScript (Node.js) or Python
  • Alternative Programming Languages: Any language with a package manager
  • Coolness Level: Level 3: Genuinely Clever
  • Business Potential: 3. Service & Support (This is 50% of senior debugging)
  • Difficulty: Level 2: Intermediate
  • Knowledge Area: Debugging / Testing / Docker
  • Software or Tool: Docker (optional but recommended)
  • Main Book: “The Art of Debugging” by Norman Matloff

What you’ll build: A standalone script that installs a specific version of a library (e.g., express or requests), sets up a minimal usage scenario, triggers a “bug” (you will intentionally pick a known historical bug from a library), and fails with a clear error message.

Why it teaches Open Source: Maintainers ignore issues that say “It doesn’t work”. They prioritize issues that say “Run this script to see it crash”. Creating a Minimal, Reproducible Example (MRE) is the most valuable skill for a contributor.

Core challenges you’ll face:

  • Isolating the variable: Removing your app’s code to prove the bug is in the library.
  • Versioning: Ensuring you are running exactly the version that has the bug.
  • Automation: Making the script setup its own environment (installing dependencies) so the maintainer just runs node repro.js.

Key Concepts:

  • Minimal Reproducible Example (MRE): StackOverflow Help Pages
  • Dependency Management: package.json vs package-lock.json

Difficulty: Intermediate Time estimate: 1 week Prerequisites: Basic coding in the chosen language

Real World Outcome

You will have a file reproduce_issue_1024.js.

Example Output:

$ node reproduce_issue_1024.js
[info] Installing express@4.17.1...
[info] Setting up test server...
[test] Sending malformed request...
[FAIL] Expected server to handle error, but it crashed with "TypeError: Cannot read property 'header' of undefined"
[SUCCESS] Bug reproduced!

The Core Question You’re Answering

“How can I prove this is their bug, not my code?”

Before you write code, ask: “What is the absolute minimum amount of code required to crash this?”

Concepts You Must Understand First

  1. Test Cases
    • How to write an assertion?
    • Book Reference: “Test Driven Development: By Example” by Kent Beck

Questions to Guide Your Design

  1. How do I install a package inside a script?
    • You might need to use child_process.execSync('npm install ...') inside your script.
  2. How do I cleanup?
    • The script should probably run in a /tmp folder or clean up node_modules after it’s done.

Thinking Exercise

Find a resolved issue on GitHub for a popular library (e.g., “axios”). Look at the “How to reproduce” section.

  • Did they provide code?
  • Did the maintainer ask for more info?
  • Imagine you have to write the code to reproduce that specific bug.

The Interview Questions They’ll Ask

  1. “Walk me through how you debug a crash in a third-party library.”
  2. “What information should be included in a bug report?”
  3. “How do you ensure your reproduction script works on other machines?” (Answer: Containers/Docker)

Hints in Layers

Hint 1: Find a Target Don’t invent a bug. Go to the react or express repo, filter issues by label:bug and status:closed. Find one that looks interesting.

Hint 2: The Wrapper Write a shell script or main wrapper that creates a temporary directory.

Hint 3: The Setup In that directory, programmatically write a package.json with the exact version mentioned in the old issue.

Hint 4: The Trigger Write the code that calls the library function in the way that caused the crash. Assert that the process exit code is non-zero.

Project 3: The “Good First Issue” Finder

  • File: LEARN_OPEN_SOURCE_CONTRIBUTION.md
  • Main Programming Language: Python
  • Alternative Programming Languages: TypeScript, Go
  • Coolness Level: Level 2: Practical
  • Business Potential: 2. Micro-SaaS (Help devs find work)
  • Difficulty: Level 2: Intermediate
  • Knowledge Area: APIs / JSON / Filtering
  • Software or Tool: GitHub API
  • Main Book: “Designing Data-Intensive Applications” (Chapter on Data Models - slightly overkill but good for thinking about structure)

What you’ll build: A CLI tool that queries the GitHub API to find repositories written in your favorite language, that have issues labeled good-first-issue or help-wanted, but excludes repos with 0 stars or issues that haven’t been touched in years.

Why it teaches Open Source: Finding where to contribute is the hardest part. By building this, you learn to navigate the GitHub metadata, understand how maintainers label work, and you build a tool you will actually use to find your first real contribution.

Core challenges you’ll face:

  • Rate Limiting: GitHub’s API has strict limits. You need to handle pagination and backoff.
  • Signal vs Noise: There are millions of “test” repos. You need to filter for “real” projects (Stars > 100, Recent Activity).
  • Authentication: Learning to use Personal Access Tokens (PAT).

Key Concepts:

  • REST APIs: Understanding GET parameters and Headers.
  • Authentication: Bearer Tokens.

Difficulty: Intermediate Time estimate: Weekend Prerequisites: HTTP requests, JSON parsing

Real World Outcome

Example Output:

$ ./find_issues --lang python --stars 500
Searching GitHub for Python projects > 500 stars...

[django/django]
  - Issue #1234: "Fix typo in tutorial" (Updated 2 days ago)
  - Issue #1235: "Add documentation for X" (Updated 1 week ago)

[pandas-dev/pandas]
  - Issue #9999: "Deprecate function Y" (Updated 3 hours ago)

Found 5 potential opportunities!

The Core Question You’re Answering

“Where is my help actually needed?”

Most “Good First Issues” are already taken or are on dead projects. You are solving the discovery problem.

Concepts You Must Understand First

  1. HTTP Headers
    • How to pass Authorization: token ...?
  2. JSON Parsing
    • How to extract nested fields from the API response?

Questions to Guide Your Design

  1. How do I sort by “freshness”?
    • GitHub API search query syntax (updated:>2023-01-01).
  2. How do I verify the issue is truly open?
    • Check state: open and maybe check if it has a linked PR (often issues are “open” but a PR is already pending).

Thinking Exercise

Manually search GitHub.

  • Go to issues tab on a random repo.
  • Filter by label:"good first issue".
  • Notice how many are actually 3 years old.
  • Write down the logic you use as a human to decide if an issue is worth clicking. (e.g., “Is the last comment from 2021? Skip.”)

The Interview Questions They’ll Ask

  1. “How do you handle API pagination?”
  2. “How would you cache the results to avoid hitting rate limits?”
  3. “Explain how OAuth tokens work.”

Hints in Layers

Hint 1: API Access Get a GitHub Personal Access Token (classic).

Hint 2: The Query Use the /search/issues endpoint. Query: label:"good first issue" language:python state:open.

Hint 3: Filtering The search endpoint returns many results. Loop through them and request the repository details for each to check star count (or include stars:>100 in the search query).

Hint 4: Formatting Print the URL clearly so you can cmd+click it from the terminal.

  • File: LEARN_OPEN_SOURCE_CONTRIBUTION.md
  • Main Programming Language: Python or Go
  • Alternative Programming Languages: Rust
  • Coolness Level: Level 2: Practical
  • Business Potential: 3. Service & Support (Docs are the product)
  • Difficulty: Level 1: Beginner/Intermediate
  • Knowledge Area: Parsing / HTTP / CI/CD
  • Software or Tool: GitHub Actions
  • Main Book: “Docs for Developers” by Jared Bhatti et al.

What you’ll build: A tool (that runs locally or in CI) that recursively scans a directory for Markdown (.md) files, extracts all hyperlinks ([text](url)), and attempts to visit each one. If any link returns a 404, the script exits with an error code.

Why it teaches Open Source: Broken documentation is the #1 complaint of users. Fixing a broken link is often the “First PR” for many. By building the tool that finds them, you understand the structure of documentation and how to automate quality assurance.

Core challenges you’ll face:

  • Regex vs Parsing: Do you use a regex to find links (fragile) or a proper Markdown parser (robust)?
  • Rate Limiting: Checking 1000 links to github.com will get you banned. You need concurrency control and retry logic.
  • Relative Links: Handling [About](../about.md) vs [Google](https://google.com).

Key Concepts:

  • AST (Abstract Syntax Tree): Reading code/text as a tree structure.
  • HTTP Status Codes: 200 vs 404 vs 301 (Redirects).

Difficulty: Beginner Time estimate: Weekend Prerequisites: Basic HTTP knowledge

Real World Outcome

Example Output:

$ ./doc_guardian ./docs

[SCANNING] found 15 markdown files.
[CHECK] docs/intro.md
  OK: https://google.com (200)
  OK: ../images/logo.png (Found locally)
[CHECK] docs/install.md
  ERROR: https://example.com/old-package (404 Not Found)

[SUMMARY] Checked 54 links. 1 Broken.
[FAIL] Exiting with code 1.

The Core Question You’re Answering

“Can I trust these instructions?”

Nothing destroys trust like a 404 on the “Getting Started” page.

Concepts You Must Understand First

  1. Markdown Syntax
    • How are links structured? [label](target).
  2. Relative Paths
    • How to resolve ./../foo from /home/user/project/docs/bar?

Questions to Guide Your Design

  1. How do I parse Markdown?
    • Don’t write your own parser. Use mistune (Python) or goldmark (Go).
  2. How do I verify a local file exists?
    • os.path.exists().
  3. Should I check localhost links?
    • Probably not, or warn that they are skipped.

Thinking Exercise

Manually check a README.md.

  • Find a link. Click it.
  • Find a relative link [Code](./src). Navigate to it in your file explorer.
  • Imagine automating this loop.

The Interview Questions They’ll Ask

  1. “How do you handle flaky network requests when checking links?”
  2. “How would you optimize this to check 10,000 links?” (Async/Concurrency)
  3. “How do you distinguish between a temporary 500 error and a permanent 404?”

Hints in Layers

Hint 1: Finding Links Use a regex like \[.*?\]\((.*?)\) for a quick dirty version, or a library for the clean version.

Hint 2: Checking URLs Use HEAD requests instead of GET to save bandwidth. You only need the status code, not the body.

Hint 3: Concurrency If using Python, use aiohttp or ThreadPoolExecutor. Don’t do it serially.

Hint 4: Ignoring Anchors Ignore links starting with # (internal page anchors) for now, or check if the anchor exists in the content.

Project 5: The License Compliance Auditor

  • File: LEARN_OPEN_SOURCE_CONTRIBUTION.md
  • Main Programming Language: JavaScript (Node.js)
  • Alternative Programming Languages: Ruby, Python
  • Coolness Level: Level 1: Corporate Snoozefest (But VERY valuable)
  • Business Potential: 3. Service & Support (Enterprises pay huge money for this)
  • Difficulty: Level 2: Intermediate
  • Knowledge Area: Legal / Package Managers / Recursion
  • Software or Tool: npm / pip
  • Main Book: “Open Source for Business” by Heather Meeker

What you’ll build: A tool that reads a package.json, traverses the node_modules folder (or queries the registry) to find the license of every dependency (and their dependencies), and checks them against a policy.json (e.g., “Allow: MIT, Apache. Deny: GPL”).

Why it teaches Open Source: “Can we use this?” is the first question a boss asks. Understanding the difference between Permissive (MIT) and Copyleft (GPL) is crucial for any professional contributor. You will learn how dependency trees works and why “transitive dependencies” are a legal minefield.

Core challenges you’ll face:

  • The Tree: A depends on B which depends on C. You must walk the whole graph.
  • Missing Metadata: Some packages don’t define a license in package.json; they just have a LICENSE file. You might need to read that file.
  • Dual Licensing: Some packages say (MIT OR GPL-3.0). How do you handle that?

Key Concepts:

  • Transitive Dependencies: Dependencies of dependencies.
  • SPDX Identifiers: Standard names for licenses (e.g., Apache-2.0).

Difficulty: Intermediate Time estimate: 1 week Prerequisites: Recursion, JSON

Real World Outcome

Example Output:

$ ./audit_licenses
[INFO] Reading package.json...
[INFO] Found 12 direct dependencies.
[INFO] Scanning 432 total packages in node_modules...

[WARNING] 'stupid-logger' v1.2 is licensed under 'GPL-3.0'.
          Path: my-app -> awesome-ui -> stupid-logger
          Policy Violation: GPL-3.0 is in the DENY list.

[SUCCESS] Audit complete. 1 violation found.

The Core Question You’re Answering

“Will this code get my company sued?”

Concepts You Must Understand First

  1. Permissive vs Copyleft
    • MIT/BSD/Apache = Do whatever.
    • GPL/AGPL = If you distribute, you must share your source.
  2. Dependency Resolution
    • How npm or pip flattens trees.

Questions to Guide Your Design

  1. Where is the license info?
    • Usually in package.json under license field. Sometimes in a LICENSE file.
  2. How deep do I go?
    • All the way down.

Thinking Exercise

Look at your current project’s node_modules.

  • Pick a random folder. Look at its package.json.
  • Does it have a license?
  • Does its dependency have a license?

The Interview Questions They’ll Ask

  1. “What is the difference between MIT and GPL?”
  2. “Explain the concept of a ‘viral’ license.”
  3. “How would you handle a package that has no license declared?”

Hints in Layers

Hint 1: The Data Source Use npm list --all --json to get the full tree as a JSON object instead of scanning folders manually. This saves you from writing the recursion logic yourself.

Hint 2: The Policy Create a simple JSON file: {"allow": ["MIT", "ISC", "Apache-2.0"], "deny": ["GPL", "AGPL"]}.

Hint 3: Checking Traverse the JSON from npm list, check the license field against your policy.

Project 6: The “Stale Issue” Bot (Triage Assistant)

  • File: LEARN_OPEN_SOURCE_CONTRIBUTION.md
  • Main Programming Language: TypeScript (running on Node.js)
  • Alternative Programming Languages: Go
  • Coolness Level: Level 2: Practical
  • Business Potential: 2. Pro Tool (GitHub App)
  • Difficulty: Level 2: Intermediate
  • Knowledge Area: Automation / GitHub Actions
  • Software or Tool: GitHub Actions
  • Main Book: “GitHub Actions in Action” by Michael Kaufmann

What you’ll build: A script meant to run as a cron job (via GitHub Actions). It searches a repo for issues that have had no activity (comments/events) for > 30 days. It posts a polite comment (“Is this still relevant?”) and applies a label stale. If it remains inactive for another 7 days, it closes the issue.

Why it teaches Open Source: Maintainer burnout is real. Abandoned issues clutter the workspace. This introduces you to the concept of Automated Triage and interaction via “Bots”. You will learn to write code that acts like a user.

Core challenges you’ll face:

  • Idempotency: Don’t comment twice on the same issue. Check if you already commented.
  • Politeness: Writing text that doesn’t sound rude.
  • Safety: Ensuring you don’t accidentally close important bugs (e.g., exclude issues with pinned or security labels).

Key Concepts:

  • Cron: Scheduling tasks (0 0 * * *).
  • State Management: Using labels (stale) to store the state of the workflow.

Difficulty: Intermediate Time estimate: Weekend Prerequisites: GitHub API

Real World Outcome

Example Output:

$ node stale_bot.js
[INFO] Checking repo: douglas/my-project
[INFO] Found 3 issues inactive for > 30 days.

[Issue #42] "Fix the flux capacitor"
  - Last update: 45 days ago.
  - Action: Posting comment & Adding 'stale' label.

[Issue #15] "Add support for Mars"
  - Already labeled 'stale'. Last update: 10 days ago.
  - Action: Closing issue as "not planned".

The Core Question You’re Answering

“How do we keep the noise down so we can focus on the signal?”

Concepts You Must Understand First

  1. Bot Accounts
    • Bots are just users with a token.
  2. Search Queries
    • is:issue is:open updated:<2023-11-01.

Questions to Guide Your Design

  1. How do I avoid spamming?
    • Check the timeline of the issue. If the last comment is from the bot, don’t comment again.
  2. How do I run this every day?
    • GitHub Actions on: schedule: - cron: '0 0 * * *'.

Thinking Exercise

Go to a big repo like kubernetes/kubernetes. Look for closed issues.

  • Find one closed by k8s-ci-robot.
  • Read the message. How does it make you feel? (Annoyed? Relieved?)
  • How would you improve the message?

The Interview Questions They’ll Ask

  1. “How do you implement a ‘dry run’ mode for this bot?” (Crucial for safety).
  2. “How do you handle API rate limits if the repo has 10,000 issues?”
  3. “What are the ethical implications of auto-closing bug reports?”

Hints in Layers

Hint 1: The Search Use the GitHub Search API to find candidates: repo:owner/name is:open updated:<DATE.

Hint 2: The Loop Iterate through the results.

Hint 3: The Logic

  • If has label stale AND updated < 7 days ago -> Close.
  • If no label stale AND updated < 30 days ago -> Comment & Label.

Hint 4: The Action Create a .github/workflows/stale.yml to run it automatically.

Project 7: The Changelog Generator

  • File: LEARN_OPEN_SOURCE_CONTRIBUTION.md
  • Main Programming Language: Rust or Go (Good for CLI tools)
  • Alternative Programming Languages: Python
  • Coolness Level: Level 2: Practical
  • Business Potential: 2. Micro-SaaS
  • Difficulty: Level 2: Intermediate
  • Knowledge Area: Git Internals / Regex / String Parsing
  • Software or Tool: Conventional Commits
  • Main Book: “Regular Expressions Cookbook” by Jan Goyvaerts

What you’ll build: A CLI tool that reads the git log of the current repository, parses messages that follow the Conventional Commits specification (e.g., feat: allow login, fix: crash on exit), and generates a beautifully formatted markdown file grouping them by category.

Why it teaches Open Source: In a team of 100, you can’t read every commit. You need a summary. This project teaches you why maintainers scream about “bad commit messages”. You will learn that the commit log is a database, and structured data allows for automation.

Core challenges you’ll face:

  • Parsing: Distinguishing feat: ... from Merge branch 'main'... from “random stuff”.
  • SemVer Calculation: If a commit body contains BREAKING CHANGE:, the next release must be Major. Your tool should detect this.
  • Git Interaction: Running git log and capturing stdout.

Key Concepts:

  • Conventional Commits: A specification for commit messages.
  • Stdio: Piping output from one command to another.

Difficulty: Intermediate Time estimate: Weekend Prerequisites: Regex basics

Real World Outcome

Example Output:

$ ./generate_changelog --since v1.0.0

# Changelog v1.1.0

## 🚀 Features
- **auth**: Allow login via Google (@douglas)
- **ui**: Add dark mode toggle (@alice)

## 🐛 Bug Fixes
- **api**: Fix crash when user ID is null (@bob)

## ⚠️ Breaking Changes
- **api**: Removed `/v1/getUser` endpoint (migrated to `/v2`)

[SUCCESS] CHANGELOG.md generated.

The Core Question You’re Answering

“What changed since the last time I looked?”

Concepts You Must Understand First

  1. Git Log Formats
    • git log --pretty=format:"%s"
  2. Regex Groups
    • ^(feat|fix|docs)(\(.*\))?: (.*)$

Questions to Guide Your Design

  1. How do I get commits only since the last tag?
    • git log tag..HEAD
  2. How do I handle multi-line commits?
    • You need the body to check for “BREAKING CHANGE”.

Thinking Exercise

Look at the commit history of angular/angular.

  • Notice the strict format.
  • Look at a project with no format.
  • Which one is easier to generate release notes for?

The Interview Questions They’ll Ask

  1. “Why do we care about commit message formats?”
  2. “Write a regex to capture the ‘type’, ‘scope’, and ‘description’ from a conventional commit.”
  3. “How would you handle a commit that reverts another commit?”

Hints in Layers

Hint 1: Extracting Data Use git log --format="%H|%s|%b" to get Hash, Subject, Body separated by pipes.

Hint 2: The Loop Read line by line.

Hint 3: The Regex ^(?<type>\w+)(?:\((?<scope>[^)]+)\))?: (?<desc>.*)$

Hint 4: Grouping Store matches in a dictionary: changes = {'feat': [], 'fix': []}.

Project 8: The Maintainer Simulator (The Code Review)

  • File: LEARN_OPEN_SOURCE_CONTRIBUTION.md
  • Main Programming Language: English (Communication) & Markdown
  • Alternative Programming Languages: N/A
  • Coolness Level: Level 3: Genuinely Clever (Soft skills are rare)
  • Business Potential: 1. Resume Gold (Senior Engineers are hired for this)
  • Difficulty: Level 3: Advanced (Requires deep empathy + technical knowledge)
  • Knowledge Area: Soft Skills / Code Quality
  • Software or Tool: GitHub PR Interface
  • Main Book: “Nonviolent Communication” by Marshall Rosenberg

What you’ll build: This is a role-playing project. You will create a repo, push a “bad” PR (with security flaws, bad formatting, and no tests) from a “sockpuppet” account. Then, you will switch roles and write a Code Review that is rigorous on quality but extremely kind to the human.

Why it teaches Open Source: 90% of open source friction comes from bad communication. “This code sucks” kills projects. “Have you considered X?” builds communities. You cannot become a senior contributor without mastering the art of the review.

Core challenges you’ll face:

  • Identifying Issues: Finding the SQL injection, the memory leak, and the variable named x.
  • Tone Management: Correcting the error without making the contributor feel stupid.
  • Prioritization: Deciding what is a “blocker” (must fix) vs “nitpick” (nice to have).

Key Concepts:

  • Nitpicks: Small style issues.
  • Blockers: Security/Architecture issues.
  • Bikeshedding: Arguing over trivial details (avoid this!).

Difficulty: Advanced (Socially) Time estimate: Weekend Prerequisites: Ability to read bad code

Real World Outcome

Deliverable: A file REVIEW_GUIDE.md containing the “Bad Code” and your “Response”.

Example Output (Your Review):

Hi @new-contributor! Thanks so much for this PR. I love that you're tackling the login feature. 🎉

I reviewed the code and have a few thoughts:

1. **Security**: In `db.js`, it looks like we're concatenating strings to build the SQL query.
   - *Risk*: This leaves us open to SQL Injection.
   - *Suggestion*: Could we use parameterized queries instead? (Link to doc)

2. **Style**: I noticed a mix of tabs and spaces.
   - *Suggestion*: Running `npm run lint` should fix this automatically!

3. **Logic**: The loop on line 45 seems to run O(n^2).
   - *Question*: Since the list is sorted, could we use a binary search here?

Let me know if you need help with the SQL part!

The Core Question You’re Answering

“How do I tell someone they are wrong without them hating me?”

Concepts You Must Understand First

  1. SQL Injection / XSS
    • You need to know what to catch before you can review it.
  2. The “Sandwich” Method
    • Praise, Correction, Encouragement.

Questions to Guide Your Design

  1. Did I check the tests?
    • If there are no tests, the review should stop there.
  2. Am I being clear?
    • “Fix this” is bad. “This causes a crash because X” is good.

Thinking Exercise

Find a PR on a major repo (e.g., microsoft/vscode) where a maintainer requested changes.

  • Read the comments.
  • Note the tone.
  • Note how they ask questions (“What do you think about…”) instead of giving orders.

The Interview Questions They’ll Ask

  1. “How do you handle a disagreement in a code review?”
  2. “What do you do if a junior developer keeps making the same mistake?”
  3. “Simulate a code review for this function.” (They will show you code).

Hints in Layers

Hint 1: The Setup Write a function that takes user input and saves it to a global array without checking size. (Memory leak + Global state).

Hint 2: The Persona Pretend the contributor is an enthusiastic student who is trying their best.

Hint 3: The Review Write your draft. Then re-read it. Delete every instance of “You”. Replace “You broke X” with “This code might break X”.

Project 9: The Dependency Updater (Mini-Dependabot)

  • File: LEARN_OPEN_SOURCE_CONTRIBUTION.md
  • Main Programming Language: Python or JavaScript
  • Alternative Programming Languages: Go
  • Coolness Level: Level 3: Genuinely Clever
  • Business Potential: 4. Open Core (Dependabot was a startup sold to GitHub)
  • Difficulty: Level 3: Advanced
  • Knowledge Area: Automation / Git Operations
  • Software or Tool: GitHub API
  • Main Book: “Automate the Boring Stuff with Python” by Al Sweigart

What you’ll build: A script that parses a requirements.txt (Python) or package.json (Node), queries the central registry (PyPI or NPM) for the latest version, checks if the local version is older, and if so, creates a new git branch bump-deps, updates the file, and prints the git commands to push it.

Why it teaches Open Source: Security vulnerabilities often come from old dependencies. The ecosystem moves fast. Maintainers love tools that automate the “chores”. This project combines parsing, network requests, and git automation.

Core challenges you’ll face:

  • SemVer logic: Is 1.2.10 greater than 1.2.2? (String comparison says No, SemVer says Yes).
  • Registry APIs: Learning the JSON structure of PyPI/NPM.
  • Safety: Don’t update major versions automatically (breaking changes).

Key Concepts:

  • Semantic Versioning Parsing: major.minor.patch.
  • Registry APIs: Fetching metadata.

Difficulty: Advanced Time estimate: 1 week Prerequisites: HTTP, File I/O

Real World Outcome

Example Output:

$ ./updater ./my-project/package.json

[CHECK] 'lodash': Local=4.17.15, Latest=4.17.21. => UPDATE NEEDED
[CHECK] 'react': Local=16.8.0, Latest=18.2.0. => MAJOR UPDATE (Skipping)

[ACTION] Creating branch 'bump-lodash'...
[ACTION] Updating package.json...
[DONE] Run 'git push origin bump-lodash' to finish.

The Core Question You’re Answering

“Are we secure?”

Concepts You Must Understand First

  1. Registry APIs
    • https://registry.npmjs.org/<package>
    • https://pypi.org/pypi/<package>/json

Questions to Guide Your Design

  1. How do I parse versions?
    • Use the semver package (Node) or packaging (Python). Don’t write your own regex for sorting versions.
  2. How do I edit JSON safely?
    • Read -> Parse -> Modify Object -> Serialize with indentation.

Thinking Exercise

Manually check your project’s dependencies.

  • npm outdated.
  • Why didn’t you update them yesterday? (Fear of breaking? Laziness?)
  • How would a bot solve the “Laziness” part?

The Interview Questions They’ll Ask

  1. “How would you design a system to update dependencies for 1,000 repositories?”
  2. “How do you ensure the update doesn’t break the build?” (Trigger CI).
  3. “Compare Semantic Versioning vs Calendar Versioning.”

Hints in Layers

Hint 1: Fetching For NPM: GET https://registry.npmjs.org/react/latest.

Hint 2: Comparison Split the version string by . and cast to integers. [1, 2, 10] vs [1, 2, 2]. Compare index by index.

Hint 3: Git Ops You don’t need to push yet. Just editing the file locally is a huge win.

Project Comparison Table

Project Difficulty Time Depth of Understanding Fun Factor
1. Fork Simulator Beginner Weekend High (Foundational) 2/5
2. Issue Reproducer Intermediate 1 Week Very High (Practical) 4/5
3. Issue Finder Intermediate Weekend High (Discovery) 3/5
4. Doc Guardian Beginner Weekend Medium 3/5
5. License Auditor Intermediate 1 Week Medium (Corporate) 1/5
6. Stale Bot Intermediate Weekend Medium (Ops) 3/5
7. Changelog Gen Intermediate Weekend Medium (Process) 2/5
8. Code Reviewer Advanced Weekend Very High (Social) 4/5
9. Dependency Updater Advanced 1 Week High (Security) 5/5
10. The Library Expert 2 Weeks Master (Holistic) 5/5

Recommendation

Where to start?

  1. If you are terrified of Git: Start with Project 1 (Fork Simulator). It is a safe sandbox. You cannot break anything.
  2. If you want to contribute NOW: Do Project 3 (Issue Finder) to find a target, then Project 2 (Issue Reproducer) to solve it.
  3. If you want a job: Master Project 8 (Code Reviewer) and Project 9 (Dependency Updater). These show you understand enterprise-scale software problems.

Final Overall Project: The “Perfect” Micro-Library

  • File: LEARN_OPEN_SOURCE_CONTRIBUTION.md
  • Main Programming Language: Your strongest language
  • Difficulty: Level 5: Master (The First-Principles Wizard)
  • Time estimate: 2-4 Weeks

What you’ll build: You will not just write code; you will birth an open source project. You will build a tiny library (e.g., is-odd, color-converter, string-slugify)—the functionality doesn’t matter. The goal is to build the perfect infrastructure around it.

The Requirements:

  1. The Code: Clean, tested, modular.
  2. The CI/CD: GitHub Actions that run tests on every Push.
  3. The Docs: A README that explains why and how.
  4. The Governance: A CONTRIBUTING.md, CODE_OF_CONDUCT.md, and LICENSE.
  5. The Automation: Semantic Release (auto-publishing to NPM/PyPI on merge).
  6. The Templates: Issue templates for Bug Reports and Feature Requests.

Why it teaches [Topic]: To understand the Maintainer, you must become the Maintainer. When you set up the rules for others, you understand why those rules exist in the projects you contribute to. You will realize why “Check the CI” is the first thing a maintainer says.

Real World Outcome: A package published on NPM/PyPI/Crates.io with a green “Passing” badge, 100% test coverage, and a structure that invites others to contribute.

Core Challenges:

  • Pipeline Configuration: YAML hell. Getting tests to pass on Windows, Linux, and Mac.
  • Publishing: Managing secrets (API tokens) securely in CI.
  • Documentation: Writing for an audience that doesn’t know what you know.

Summary

This learning path covers Open Source Contribution through 10 hands-on projects.

# Project Name Main Language Difficulty Time Estimate
1 The Local “Fork” Simulator Bash Beginner Weekend
2 The “Bug Reproduction” Script JS/Python Intermediate 1 Week
3 The “Good First Issue” Finder Python Intermediate Weekend
4 The Documentation Guardian Python/Go Beginner Weekend
5 The License Compliance Auditor Node.js Intermediate 1 Week
6 The “Stale Issue” Bot TypeScript Intermediate Weekend
7 The Changelog Generator Rust/Go Intermediate Weekend
8 The Maintainer Simulator Markdown Advanced Weekend
9 The Dependency Updater Python/JS Advanced 1 Week
10 The “Perfect” Micro-Library Any Master 2-4 Weeks

For beginners: Start with #1 to lose the fear of git. Then #3 to find where to look. For intermediate: Build #2 to learn debugging, then #6 to understand automation. For advanced: Go straight to #9 and #10.

Expected Outcomes

After completing these projects, you will:

  • Fear no codebase: You know how to isolate bugs (Project 2).
  • Speak the language: You know what “rebase”, “squash”, and “semver” mean (Project 1, 7).
  • Automate the boring stuff: You can build bots to help you (Project 6, 9).
  • Be a “Good Citizen”: You understand the legal and social rules (Project 5, 8).

You will not just be a coder; you will be an Open Source Citizen.