Python & Dev Cheat Sheet Project

Overview

This project is a comprehensive reference guide for Python programming, data analysis, scripting, and project setup. It is designed to serve as a quick-access cheat sheet for developers, data scientists, and students, covering both core Python concepts and practical tools for day-to-day development.

---

Contents

1. Python Basics

• Variables, data types, and operators
• Control flow: if, for, while, break, continue
• Functions: standard, lambda, *args, **kwargs, decorators
• Object-Oriented Programming (OOP): classes, objects, inheritance, special methods

2. Data Analysis

• Pandas: DataFrames, selection, filtering, aggregation
• NumPy: arrays, mathematical operations, broadcasting
• Datetime: parsing, formatting, timedelta operations
• String & Regex: pattern matching, search, replace

3. Visualization

• Basic plotting with matplotlib and seaborn
• Plot customization: labels, titles, colors, styles

4. File & Data Handling

• File I/O: reading/writing text, CSV, JSON
• JSON parsing and API response handling
• Flattening nested JSON into DataFrames

5. Project Setup & Development Tools

• Typical project structure (src/, tests/, notebooks/, data/)
• Virtual environments (venv) and dependencies (requirements.txt)
• Git workflow: init, add, commit, push, branching
• Docker basics: Dockerfile, build, run

6. Shell & Automation

• PowerShell commands: navigation, file ops, process management, scripting
• Networking commands and simple API calls

7. Advanced Python & Tips

• List, set, dictionary, and generator comprehensions
• Error handling: try/except/finally
• Logging with logging module
• Performance profiling: timeit, cProfile
• Useful standard library modules: math, random, itertools, functools, os, sys, json

---

How to Use

1. Clone the repository:

git clone <repo_url>
cd my_project
Create a virtual environment:

bash
Copy code
python -m venv .venv
.venv\Scripts\activate  # Windows
source .venv/bin/activate  # Linux/Mac
Install dependencies:

bash
Copy code
pip install -r requirements.txt
Open the Jupyter notebook:

bash
Copy code
jupyter notebook
Explore sections interactively and run examples.