Python

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.

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2️⃣ OOP in Real Backend Apps

Let me break it down how I understood it:

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

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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.

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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.

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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).

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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).

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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

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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