1️⃣ Core Python Concepts I Use Daily

📦 Data Types (These map directly to JSON data!)

List → Think of it as an array of values coming from an API: [1, 'Flask', True]
Tuple → Unchangeable config values like ('DEBUG', False)
Set → For filtering out duplicate user IDs
Dict → Backend gold: Every JSON object becomes a dictionary in Python{ "user": "rishabh", "age": 23}

🧠 Control Flow

if/else → Classic auth checks
for/while → Iterating over DB rows or JSON keys

🔁 Comprehensions & Generators

One-liners for filtering lists or serializing DB records.
Generator = lightweight API paginators, async-ready!

🧯 Exception Handling

Use try/except while handling requests, DB connections, or auth logic. It’s cleaner and more Pythonic than checking every condition.

2️⃣ OOP in Real Backend Apps

Let me break it down how I understood it:

Concept	How I Actually Use It
Class	Blueprint for models (like `Task`, `User`)
Object	Actual DB row, or user session
Constructor	Set up initial data like `__init__(self)` in Flask views
Inheritance	Extend base classes in Flask/JWT/Auth
Encapsulation	Keep internal logic hidden (e.g., password hashing)
Polymorphism	Think of different serializers/validators responding to same method call

Also, __str__ is super useful when debugging models in logs.

3️⃣ Writing Pythonic Code

Python is beautiful when written right.

enumerate() → Index + value in loops (great for CLI apps)
zip() → Combine two lists, useful in data processing
any() / all() → Quick validation checks
Use comprehensions instead of for loops where possible.
Follow EAFP (Easier to Ask Forgiveness than Permission) instead of checking every if.

4️⃣ File Handling & Data Interchange

You’ll often deal with:

Config files (.env, .json)
User data (JSON from frontend)
Exporting reports (CSV or PDF)

My go-to approach:

pythonCopyEditwith open('config.json') as f:
    config = json.load(f)

Safe, clean, and closes the file automatically.

5️⃣ Decorators & Closures

I use decorators in:

Flask for @app.route and @jwt_required
Custom middlewares for logging, permissions, API key validation

Closures are handy when I want to retain some data inside a nested function (used once to build a rate limiter without external libs).

6️⃣ Iterators, Generators, and Async

When building data-heavy features or working with async frameworks like FastAPI:

Generator: Stream DB rows without loading all at once
Iterator: Custom __iter__ objects for pagination
Asyncio: Used for background jobs, emailing, etc.

For API calls, I often use httpx (async) or requests (sync).

7️⃣ Concurrency Basics for Backend

threading → Great for logging or sending emails in background
multiprocessing → Batch jobs and heavy calculations
asyncio → My favorite when building event-driven APIs in FastAPI

8️⃣ Data Structures & Algorithms (Still important!)

Even though frameworks handle a lot, knowing Big O helped me write faster code and optimize DB queries.

I practiced:

Searching/sorting logic with lists and dicts
Use collections.Counter, deque, defaultdict when needed

Python

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