https://github.com/umitkacar/awesome-interview
Coding Interview Prep: LeetCode, system design, algorithms, data structures, FAANG questions, and technical interview resources.
https://github.com/umitkacar/awesome-interview
List: awesome-interview
algorithms arrays binary-search career-development coding-interview competitive-programming data-structures dynamic-programming faang graph-algorithms interview-prep interview-questions leetcode problem-solving software-engineering sorting strings system-design technical-interview trees
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Coding Interview Prep: LeetCode, system design, algorithms, data structures, FAANG questions, and technical interview resources.
- Host: GitHub
- URL: https://github.com/umitkacar/awesome-interview
- Owner: umitkacar
- License: mit
- Created: 2022-08-19T08:53:15.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2025-11-10T09:45:52.000Z (2 months ago)
- Last Synced: 2025-11-30T17:45:32.020Z (about 1 month ago)
- Topics: algorithms, arrays, binary-search, career-development, coding-interview, competitive-programming, data-structures, dynamic-programming, faang, graph-algorithms, interview-prep, interview-questions, leetcode, problem-solving, software-engineering, sorting, strings, system-design, technical-interview, trees
- Language: Python
- Size: 109 KB
- Stars: 13
- Watchers: 4
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
Awesome Lists containing this project
- ultimate-awesome - awesome-interview - FAANG INTERVIEW PREPARATION. (Other Lists / TeX Lists)
README
# 🚀 Awesome FAANG Interview Resources
### *Your Ultimate Guide to Landing Your Dream Tech Job in 2025* 🎯
[](https://github.com/umitkacar/awesome-faang-interview/stargazers)
[](https://github.com/umitkacar/awesome-faang-interview)
[](https://github.com/umitkacar/awesome-faang-interview/pulls)
[](LICENSE)
---
## 📊 Repository Stats
| 📚 Resources | 🎥 YouTube Channels | 📖 Books | 🌐 Platforms | 🤖 AI/ML Section |
|:---:|:---:|:---:|:---:|:---:|
| **150+** | **15+** | **20+** | **25+** | **✅ NEW** |
---
## 📑 Table of Contents
- [🎯 FAANG Interview Essentials](#-faang-interview-essentials)
- [📺 Top YouTube Channels 2025](#-top-youtube-channels-2025)
- [💾 Data Structures & Algorithms](#-data-structures--algorithms)
- [🎓 Object Oriented Programming](#-object-oriented-programming)
- [📚 Must-Read Books 2024-2025](#-must-read-books-2024-2025)
- [💻 Online Coding Platforms](#-online-coding-platforms)
- [🤖 AI & Machine Learning Interviews](#-ai--machine-learning-interviews)
- [🏗️ System Design Resources](#%EF%B8%8F-system-design-resources)
- [🎁 Additional Resources](#-additional-resources)
---
## 🎯 FAANG Interview Essentials
*Start your journey with these battle-tested resources* ⚡
### 🔥 Essential Interview Prep Paths
| Resource | Description | Difficulty | 🌟 Rating |
|----------|-------------|------------|-----------|
| [**NeetCode 150**](https://neetcode.io/) | 🏆 Most popular for 2024-2025! Curated list with video explanations | ⭐⭐⭐ | ⭐⭐⭐⭐⭐ |
| [**LeetCode Grind 75**](https://www.techinterviewhandbook.org/grind75) | Structured study plan, time-optimized | ⭐⭐⭐ | ⭐⭐⭐⭐⭐ |
| [**Blind 75**](https://www.teamblind.com/post/New-Year-Gift---Curated-List-of-Top-75-LeetCode-Questions-to-Save-Your-Time-OaM1orEU) | Classic must-do problems | ⭐⭐⭐ | ⭐⭐⭐⭐⭐ |
| [**Tech Interview Handbook**](https://www.techinterviewhandbook.org/) | Complete interview guide | ⭐⭐ | ⭐⭐⭐⭐⭐ |
| [**System Design Primer**](https://github.com/donnemartin/system-design-primer) | 200K+ stars on GitHub! | ⭐⭐⭐⭐ | ⭐⭐⭐⭐⭐ |
### 🎬 Top Video Courses (2024-2025)
```
🎓 NeetCode 150 Course on freeCodeCamp [38+ hours]
└─ All 150 problems explained with optimal solutions
📚 Data Structures and Algorithms in Python [12+ hours]
└─ Complete beginner to advanced coverage
🚀 Google Engineer's Full Tutorial [10+ hours]
└─ Real-world problems from a Googler
```
- 🎥 [**NeetCode 150 Course on freeCodeCamp**](https://www.youtube.com/watch?v=KLlXCFG5TnA) - 38+ hours masterclass
- 📘 [**Data Structures and Algorithms in Python**](https://www.youtube.com/watch?v=pkYVOmU3MgA) - Full course for beginners
- 🎯 [**Google Engineer's Tutorial**](https://www.youtube.com/watch?v=RBSGKlAvoiM) - Easy to advanced course
---
## 📺 Top YouTube Channels 2025
*Learn from the best! These channels have helped thousands land FAANG offers* 🎓
### 💻 Coding Interview Channels
NeetCode
👤 360K+ subs
🏢 Google Engineer
⭐ Best LeetCode explanations
Clement Mihailescu
👤 500K+ subs
🏢 Ex-Google/Facebook
⭐ AlgoExpert Founder
Back To Back SWE
👤 250K+ subs
💡 Clear explanations
⭐ Complex topics simplified
TakeUForward
👤 600K+ subs
📚 Striver's A2Z DSA
⭐ Complete roadmap
#### 🎯 More Awesome Channels
- 📺 [**Nick White**](https://www.youtube.com/@NickWhite) - Live coding sessions and tutorials
- 🎓 [**William Fiset**](https://www.youtube.com/@WilliamFiset-videos) - In-depth algorithms and data structures
- 💙 [**freeCodeCamp.org**](https://www.youtube.com/@freecodecamp) - Full courses and tutorials (1M+ hours of content!)
### 🏗️ System Design & Career Channels
| Channel | Focus Area | Subscribers | Must Watch |
|---------|-----------|-------------|------------|
| [**ByteByteGo**](https://www.youtube.com/@ByteByteGo) | System Design | 500K+ | Alex Xu's channel 🔥 |
| [**tryExponent**](https://www.youtube.com/@tryexponent) | Mock Interviews | 300K+ | Real interview practice |
| [**System Design Interview**](https://www.youtube.com/@SystemDesignInterview) | Architecture | 200K+ | Design patterns |
| [**TechLead**](https://www.youtube.com/@TechLead) | Career Advice | 1M+ | Ex-Google/Facebook |
---
## 💾 Data Structures & Algorithms
*Master the fundamentals that 90% of interviews test* 📊
### 🎯 Essential Resources
Big O Cheat Sheet
⏱️ Time & Space complexity reference
VisuAlgo
👀 See algorithms in action!
NeetCode Roadmap
🗺️ Structured learning path
### 📚 Top DSA Courses
```diff
+ AlgoExpert → 160+ curated problems with video explanations ($99)
+ AlgoMonster → Pattern-based learning, very structured
+ Udemy Bootcamp → Complete Python DSA course
+ CodeBasics → Free Python DSA course
```
- 🎯 [**AlgoExpert**](https://www.algoexpert.io/) - 160+ curated problems with video explanations ($99)
- 🧠 [**AlgoMonster**](https://algo.monster/) - Pattern-based learning approach
- 📖 [**Udemy - DSA Bootcamp in Python**](https://www.udemy.com/course/data-structures-and-algorithms-bootcamp-in-python/)
- 🆓 [**CodeBasics - DSA in Python**](https://codebasics.io/courses/data-structures-and-algorithms-in-python)
---
## 🎓 Object Oriented Programming
*Essential for system design and coding interviews* 🏛️
| Resource | Type | Level | Link |
|----------|------|-------|------|
| 🐍 Real Python OOP | Tutorial Path | ⭐⭐ | [Visit](https://realpython.com/learning-paths/object-oriented-programming-oop-python/) |
| 📺 Corey Schafer | Video Series | ⭐⭐ | [Watch](https://www.youtube.com/playlist?list=PL-osiE80TeTsqhIuOqKhwlXsIBIdSeYtc) |
| 🎨 Design Patterns | Interactive Guide | ⭐⭐⭐ | [Learn](https://refactoring.guru/design-patterns) |
---
## 📚 Must-Read Books 2024-2025
*Invest in these proven resources* 💎
### 🆕 New Releases (2024-2025)
Beyond Cracking the Coding Interview
📝 Gayle McDowell
⭐⭐⭐⭐⭐
Get Book
Coding Interview Patterns
📝 Alex Xu & Shaun
⭐⭐⭐⭐⭐
Get Book
Generative AI System Design
📝 Alex Xu
⭐⭐⭐⭐⭐
Get Book
### 📖 Coding Interview Classics
```
📕 Cracking the Coding Interview (6th Edition) ⭐⭐⭐⭐⭐
├─ 189 programming problems
├─ Still #1 for FAANG interviews
└─ Solutions in multiple languages
📘 Elements of Programming Interviews in Python ⭐⭐⭐⭐⭐
├─ 250+ challenging problems
├─ Perfect for senior positions
└─ Deep algorithmic thinking
📙 Grokking Algorithms ⭐⭐⭐⭐
├─ Illustrated guide
├─ Great for beginners
└─ Easy to understand
```
| Title | Author | Focus | Amazon |
|-------|--------|-------|--------|
| **Cracking the Coding Interview** | Gayle Laakmann McDowell | 189 problems | [🛒 Buy](https://www.amazon.com/dp/0984782850) |
| **Elements of Programming Interviews** | Aziz, Lee, Prakash | 250+ problems | [🛒 Buy](https://www.amazon.com/dp/1537713949) |
| **Grokking Algorithms** | Aditya Bhargava | Illustrated guide | [🛒 Buy](https://www.amazon.com/dp/1617292230) |
### 🏗️ System Design Books
> **🔥 Most Recommended for 2025**
| Book | Author | Level | Rating |
|------|--------|-------|--------|
| 📕 **System Design Interview Vol. 1** | Alex Xu | ⭐⭐⭐ | ⭐⭐⭐⭐⭐ [Get it](https://www.amazon.com/dp/B08CMF2CQF) |
| 📕 **System Design Interview Vol. 2** | Alex Xu | ⭐⭐⭐⭐ | ⭐⭐⭐⭐⭐ [Get it](https://www.amazon.com/dp/1736049119) |
| 📘 **Acing the System Design Interview** | Zhiyong Tan | ⭐⭐⭐ | ⭐⭐⭐⭐ [Get it](https://www.amazon.com/dp/1633439100) |
| 📙 **Designing Data-Intensive Applications** | Martin Kleppmann | ⭐⭐⭐⭐⭐ | ⭐⭐⭐⭐⭐ [Get it](https://www.amazon.com/dp/1449373321) |
### 💼 Behavioral & Career
- 📗 [**The Tech Resume Inside Out**](https://www.amazon.com/dp/B08J2DW6BQ) - Gergely Orosz ⭐⭐⭐⭐⭐
- 🎯 [**Behavioral Interview Questions**](https://www.techinterviewhandbook.org/behavioral-interview-questions) - Free online guide
### 🤖 AI/ML Interview Books
| Book | Focus | Link |
|------|-------|------|
| 📕 **Hands-on Machine Learning** (3rd Ed) | Practical ML with Scikit-Learn & TensorFlow | [Amazon](https://www.amazon.com/dp/1492032646) |
| 📘 **Machine Learning Interviews** | Free comprehensive guide | [GitHub](https://github.com/alirezadir/Machine-Learning-Interviews) |
| 📙 **Deep Learning Interviews** | 400+ questions and answers | [Amazon](https://www.amazon.com/dp/B08W3HPNDK) |
---
## 💻 Online Coding Platforms
*Practice makes perfect* 🎯
### 🏆 Problem Solving Platforms
LeetCode
⭐ #1 Platform
📊 3000+ problems
NeetCode
🎥 Video solutions
🔥 Most popular 2025
HackerRank
🏅 Certifications
💼 Job matching
CodeForces
🏆 Competitive
⚡ Contest rated
CodeChef
🌍 Global contests
📈 Rating system
### 🎓 Interview Prep Platforms
```
💎 Premium Platforms (Worth the Investment)
```
| Platform | Price/Year | Focus | Best For | Rating |
|----------|-----------|-------|----------|--------|
| [**DesignGurus.io**](https://www.designgurus.io/) | $122 | Pattern-based learning | Visual learners | ⭐⭐⭐⭐⭐ |
| [**AlgoExpert**](https://www.algoexpert.io/) | $99 | 160+ curated problems | Structured prep | ⭐⭐⭐⭐⭐ |
| [**AlgoMonster**](https://algo.monster/) | $99 | Pattern recognition | Fast track | ⭐⭐⭐⭐⭐ |
| [**Educative.io**](https://www.educative.io/) | $199 | Interactive courses | Hands-on learning | ⭐⭐⭐⭐ |
| [**InterviewBit**](https://www.interviewbit.com/) | FREE | Complete prep | Budget option | ⭐⭐⭐⭐ |
### 🎯 Mock Interview Platforms
> **Practice with real people!**
| Platform | Type | Price | Features |
|----------|------|-------|----------|
| 🎭 [**Pramp (Exponent)**](https://www.tryexponent.com/practice) | Peer-to-peer | FREE (5/month) | AI grading, transcripts |
| 💼 [**Interviewing.io**](https://interviewing.io/) | Anonymous | Paid | Real engineers from FAANG |
| 🎪 [**TechMockInterview**](https://techmockinterview.com/) | 1-on-1 | Paid | Personalized feedback |
### 📊 Assessment Platforms
- 📝 [**TestDome**](https://www.testdome.com/) - Skills assessment & certifications
- 💻 [**DevSkiller**](https://devskiller.com/) - Technical screening for companies
- 🤖 [**Workera.ai**](https://workera.ai/) - AI skills assessment
- 📊 [**DataCamp**](https://www.datacamp.com/) - Data science focused
---
## 🤖 AI & Machine Learning Interviews
*Critical for 2025! ML roles are exploding* 🚀
### 🧠 ML Interview Resources
#### 📚 Free Resources
- 🔥 [**ML Interviews GitHub**](https://github.com/alirezadir/Machine-Learning-Interviews) - 10K+ stars!
- 📖 [**Deep Learning Questions**](https://github.com/youssefHosni/Awesome-ML-GitHub-Repos-for-Data-Science-Interviews)
- 🎯 [**InterviewQuery**](https://www.interviewquery.com/) - Data science prep
#### 💎 Premium Courses
- 🏆 [**MLExpert.io**](https://www.algoexpert.io/machine-learning/product) - By AlgoExpert team
- 📊 [**Interview Kickstart**](https://interviewkickstart.com/courses/machine-learning-interview-masterclass) - 66% salary increase avg
- 🎓 [**Techademy AI/ML**](https://www.techademy.com/ai-ml-interview-preparation-program)
### 🎯 Key Topics to Master for 2025
```python
ml_interview_topics = {
"Foundation": [
"Supervised & Unsupervised Learning",
"Model Evaluation & Metrics",
"Feature Engineering",
"Bias-Variance Tradeoff"
],
"Deep Learning": [
"Neural Networks Architecture",
"CNNs for Computer Vision",
"RNNs & LSTMs for Sequences",
"Training & Optimization"
],
"2025 Critical": [
"🔥 Transformers Architecture",
"🔥 Large Language Models (LLMs)",
"🔥 Prompt Engineering",
"🔥 RAG (Retrieval-Augmented Generation)",
"🔥 Fine-tuning & Transfer Learning"
],
"Production ML": [
"MLOps & Model Deployment",
"A/B Testing",
"Model Monitoring",
"Scalability Considerations"
]
}
```
> **⚠️ 2025 Alert:** 80% of ML interviews now include questions about LLMs and Transformers!
---
## 🏗️ System Design Resources
*The most challenging part of FAANG interviews* 💪
### 📚 Essential Resources
System Design Primer
📖 Most comprehensive
🆓 Completely free
ByteByteGo
📝 Alex Xu's platform
💰 Paid but worth it
Grokking SD
🎯 Pattern-based
💡 Visual learning
SD Interview
✍️ Practice problems
🎪 Mock interviews
### 📺 Video Resources
| Channel | Subscribers | Best For | Link |
|---------|------------|----------|------|
| 🎥 **ByteByteGo** | 500K+ | System design concepts | [Watch](https://www.youtube.com/@ByteByteGo) |
| 🎓 **Gaurav Sen** | 500K+ | In-depth explanations | [Watch](https://www.youtube.com/c/GauravSensei) |
| 🏗️ **System Design Interview** | 200K+ | Architecture patterns | [Watch](https://www.youtube.com/@SystemDesignInterview) |
| 💡 **Tech Dummies** | 300K+ | Simplified concepts | [Watch](https://www.youtube.com/@TechDummiesNarendraL) |
### 🎯 Practice Platforms
```
🎪 Where to practice system design interviews
```
- 🎓 [**Exponent System Design**](https://www.tryexponent.com/courses/system-design-interview) - Comprehensive course with mock interviews
- 💬 [**HelloInterview System Design**](https://www.hellointerview.com/learn/system-design) - Interactive learning
- 📊 [**DesignGurus.io**](https://www.designgurus.io/) - Pattern-based approach
---
## 🎁 Additional Resources
*Everything else you need to succeed* ✨
### 🐙 GitHub Repositories
| Repository | Stars | Description |
|-----------|-------|-------------|
| [**Awesome Interview Questions**](https://github.com/DopplerHQ/awesome-interview-questions) | 60K+ ⭐ | Questions for all languages |
| [**Tech Interview Handbook**](https://github.com/yangshun/tech-interview-handbook) | 100K+ ⭐ | Complete handbook |
| [**Coding Interview University**](https://github.com/jwasham/coding-interview-university) | 280K+ ⭐ | Multi-month study plan |
| [**System Design Resources**](https://github.com/ashishps1/awesome-system-design-resources) | 15K+ ⭐ | Curated SD resources |
### 💰 Salary Negotiation
Levels.fyi
📊 Real salary data
🏢 All major tech companies
TeamBlind
💬 Anonymous community
🔍 Real employee insights
Negotiation Guide
📖 Comprehensive guide
💡 Proven strategies
### 📄 Resume & LinkedIn
- 📝 [**Resumake**](https://resumake.io/) - LaTeX resume builder (ATS-friendly)
- 🎨 [**FlowCV**](https://flowcv.com/) - Modern resume templates
- 💼 [**LinkedIn Optimization**](https://www.techinterviewhandbook.org/resume/) - Get noticed by recruiters
---
## 📈 Learning Path Recommendation
```mermaid
graph TD
A[Start Here] --> B{Your Level?}
B -->|Beginner| C[NeetCode Roadmap]
B -->|Intermediate| D[LeetCode Grind 75]
B -->|Advanced| E[Blind 75 + System Design]
C --> F[Practice 50 Easy Problems]
D --> G[Practice Medium Problems]
E --> H[Mock Interviews]
F --> I[Move to Grind 75]
G --> J[System Design Study]
H --> K[Apply to FAANG!]
I --> J
J --> H
style A fill:#ff6b6b
style K fill:#51cf66
style B fill:#ffd43b
```
### 🗓️ Suggested Study Schedule
| Week | Focus Area | Resources | Hours/Day |
|------|-----------|-----------|-----------|
| **1-2** | DSA Basics | NeetCode Roadmap, VisuAlgo | 2-3h |
| **3-6** | Problem Solving | Grind 75 (Easy → Medium) | 3-4h |
| **7-10** | Advanced Problems | Blind 75, NeetCode 150 | 4-5h |
| **11-12** | System Design | ByteByteGo, System Design Primer | 2-3h |
| **13-14** | Mock Interviews | Pramp, Interviewing.io | 2-3h |
| **15-16** | Behavioral Prep | Tech Interview Handbook | 1-2h |
---
## 👨💻 For Developers - Contributing to This Project
**Want to improve this project? Here's everything you need!**
[](https://github.com/umitkacar/awesome-faang-interview/pulls)
[](https://www.python.org/)
[](https://hatch.pypa.io/)
### 🚀 Quick Start for Developers
This project uses modern Python tooling for production-grade quality. Here's how to get started:
#### 📋 Prerequisites
- **Python 3.11+** - Required for modern type hints
- **Git** - For version control
- **Hatch** - Modern Python project manager
#### ⚡ Setup in 3 Steps
```bash
# 1. Clone the repository
git clone https://github.com/umitkacar/awesome-faang-interview.git
cd awesome-faang-interview
# 2. Install Hatch (if not already installed)
pip install hatch
# 3. Install pre-commit hooks
pre-commit install
```
That's it! Hatch will automatically manage environments and dependencies.
---
### 🛠️ Development Commands
All commands use Hatch for consistency and simplicity:
| Command | Description | Time |
|---------|-------------|------|
| `hatch run test` | Run all tests | ~3s |
| `hatch run test-cov` | Run tests with coverage report | ~4s |
| `hatch run test-parallel` | Run tests in parallel (faster) | ~3s |
| `hatch run lint` | Check code quality with Ruff | ~0.05s |
| `hatch run format` | Format code with Black | ~0.2s |
| `hatch run type-check` | Type check with MyPy | ~0.8s |
| `hatch run security` | Security scan with Bandit | ~1s |
| `hatch run all` | **Run everything** ✅ | ~8s |
#### 🎯 Recommended Workflow
```bash
# Before making changes
hatch run all # Ensure everything passes
# Make your changes...
# Verify your changes
hatch run all # All checks must pass
# Commit (pre-commit hooks run automatically)
git add .
git commit -m "feat: your amazing feature"
```
---
### 🧪 Testing
We maintain **93.50% code coverage** with comprehensive tests.
#### Running Tests
```bash
# Quick test (sequential)
hatch run test
# With coverage report
hatch run test-cov
# Parallel execution (3x faster!)
hatch run test-parallel
# View coverage report
open htmlcov/index.html # macOS
xdg-open htmlcov/index.html # Linux
```
#### Test Structure
```
tests/
├── conftest.py # Shared fixtures
├── test_cli.py # CLI command tests (33 tests)
└── test_core.py # Core logic tests
```
#### Writing Tests
```python
# Example test
def test_resource_validation() -> None:
"""Test URL validation in Resource model."""
with pytest.raises(ValidationError):
Resource(
name="Invalid",
url="not-a-url", # Should fail
category="test"
)
```
---
### 📊 Quality Standards
This project maintains **zero-error** production quality:
```
✅ Tests: 33/33 PASSED (100%)
✅ Coverage: 93.50% with branch coverage
✅ MyPy: 0 errors across 9 files
✅ Ruff: All checks passed
✅ Black: Code formatted
✅ Bandit: No security issues
✅ Speed: 3x faster with parallel testing
```
#### Quality Tools
| Tool | Purpose | Configuration |
|------|---------|---------------|
| **Ruff** | Linting (10-100x faster than alternatives) | `pyproject.toml:114-156` |
| **Black** | Code formatting (100 char line) | `pyproject.toml:158-161` |
| **MyPy** | Type checking (strict mode) | `pyproject.toml:163-174` |
| **Bandit** | Security scanning | `pyproject.toml:194-198` |
| **pytest** | Testing framework | `pyproject.toml:200-210` |
---
### 🔍 Pre-commit Hooks
Pre-commit hooks run automatically on `git commit` to ensure quality:
```yaml
✅ Black - Auto-format code
✅ Ruff - Auto-fix linting issues
✅ MyPy - Check types
✅ Bandit - Security scan
✅ pytest - Run fast tests
```
#### Manual Hook Execution
```bash
# Run all hooks on all files
pre-commit run --all-files
# Run specific hook
pre-commit run black --all-files
pre-commit run mypy --all-files
# Skip hooks (emergency only!)
git commit --no-verify
```
---
### 📁 Project Structure
```
awesome-faang-interview/
├── src/
│ └── faang_interview/
│ ├── __init__.py
│ ├── cli.py # CLI commands (Typer)
│ └── core.py # Core logic (Pydantic models)
├── tests/
│ ├── conftest.py
│ ├── test_cli.py
│ └── test_core.py
├── .pre-commit-config.yaml # Pre-commit hooks
├── pyproject.toml # All configuration
├── README.md # This file
├── CHANGELOG.md # Version history
├── LESSONS_LEARNED.md # Technical documentation
└── LICENSE # MIT License
```
---
### 🎨 Code Style Guidelines
#### Type Hints
```python
# ✅ Good - Full type hints
def filter_resources(
resources: list[Resource],
category: str | None = None,
) -> list[Resource]:
"""Filter resources by category."""
...
# ❌ Bad - No type hints
def filter_resources(resources, category=None):
...
```
#### Docstrings
```python
# ✅ Good - Comprehensive docstring
def process_data(data: dict[str, Any]) -> str:
"""Process data and extract name.
Args:
data: Dictionary containing resource data
Returns:
Extracted name as string
Raises:
KeyError: If 'name' key is missing
"""
return str(data["name"])
```
#### Error Handling
```python
# ✅ Good - Descriptive error messages
if not url.startswith(("http://", "https://")):
msg = f"Invalid URL format: {url}. Must start with http:// or https://"
raise ValueError(msg)
# ❌ Bad - Generic error
if not url.startswith(("http://", "https://")):
raise ValueError("Invalid URL")
```
---
### 🐛 Debugging
#### Enable Verbose Output
```bash
# Verbose pytest output
hatch run test -vv
# Show print statements
hatch run test -s
# Run specific test
hatch run test tests/test_cli.py::test_list_command -vv
```
#### Type Checking Issues
```bash
# Check specific file
mypy src/faang_interview/cli.py
# Show error codes
mypy src/ --show-error-codes
# Ignore specific errors (use sparingly!)
mypy src/ --disable-error-code=attr-defined
```
---
### 📚 Additional Documentation
- **[LESSONS_LEARNED.md](LESSONS_LEARNED.md)** - Deep technical insights and decisions
- **[CHANGELOG.md](CHANGELOG.md)** - Detailed version history
- **[Hatch Documentation](https://hatch.pypa.io/)** - Build system guide
- **[Ruff Documentation](https://docs.astral.sh/ruff/)** - Linter reference
- **[pytest Documentation](https://docs.pytest.org/)** - Testing guide
---
### 🤝 Contributing Resources
**Found a great resource? Have suggestions?**
Simply:
1. 🍴 Fork this repository
2. ✏️ Add your resource to README.md
3. ✅ Run `hatch run all` to ensure quality
4. 📬 Submit a pull request
**For code contributions:**
1. Create a feature branch (`git checkout -b feature/amazing-feature`)
2. Make your changes
3. Ensure all tests pass (`hatch run all`)
4. Commit your changes (`git commit -m 'feat: add amazing feature'`)
5. Push to the branch (`git push origin feature/amazing-feature`)
6. Open a Pull Request
---
### 💡 Pro Tips
**Speed up development:**
```bash
# Use parallel testing by default
alias test="hatch run test-parallel"
# Quick format + lint
hatch run format && hatch run lint
# Watch mode for tests (install pytest-watch)
pip install pytest-watch
ptw -- -n auto
```
**IDE Integration:**
- **VS Code**: Install Python, Pylance, Ruff extensions
- **PyCharm**: Configure Hatch as project interpreter
- **Vim/Neovim**: Use ALE or coc-pyright
---
---
## ⭐ Show Your Support
**If this helped you, give it a star!** It helps others discover these resources 🌟
[](https://github.com/umitkacar/awesome-faang-interview/stargazers)
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---
### 📫 Connect & Stay Updated
---
**Last Updated:** January 2025 📅
**License:** MIT 📜
---
**Made with ❤️ for aspiring FAANG engineers**