Performance

You think Python runs things in parallel. Most of the time, it doesn’t. Today, you understand how Python handles concurrency, why it behaves the way it does, and how async actually works. Today’s Goal By the end of today, you will: Understand concurrency vs parallelism Learn about threads and the GIL Understand async/await internals Know when to use threading vs async vs multiprocessing The Illusion import threading def task(): print("running") threading.Thread(target=task).start() You think: ...

You think Python processes everything immediately. It doesn’t. Python can be lazy. Today, you understand how iteration really works under the hood. Today’s Goal By the end of today, you will: Understand iterator protocol Learn how generators work internally See how lazy execution saves memory Avoid unnecessary allocations The Illusion for i in [1,2,3]: print(i) You think: Python loops over the list directly Reality: Python asks for an iterator and pulls values one by one ...

You think import just brings code into your file. It does much more than that. Today, you understand how Python loads, initializes, and caches modules. Today’s Goal By the end of today, you will: Understand how Python resolves imports Learn module execution model Understand import caching Avoid common import pitfalls The Illusion import math You think: Python just loads math Reality: Python searches, loads, compiles (if needed), executes, and caches the module ...

You think calling a function is cheap. It isn’t. Every function call has a cost. Today, you understand what actually happens when Python executes functions. Today’s Goal By the end of today, you will: Understand how function calls work internally Learn what a call stack is Visualize execution flow Understand performance impact of function calls The Illusion def add(a, b): return a + b add(2, 3) You think: Python just jumps into the function Reality: ...

You think dictionary lookup is always O(1). That’s only half the story. Today, you understand how dictionaries actually work. Today’s Goal By the end of today, you will: Understand how dictionaries store data Learn how hashing works Understand collisions and their impact Know when O(1) breaks down The Illusion user = { "name": "John", "age": 30 } You think: This is just key-value storage Reality: This is a highly optimized hash table Dictionary Internal Model key -> hash(key) -> index -> slot -> value Dictionary does NOT scan all keys. It jumps directly using hash. ...

You think a list is just a collection of items. It is not. It is a memory-managed structure with real trade-offs. Today, you stop using data structures blindly. Today’s Goal By the end of today, you will: Understand how lists, tuples, and sets work internally Learn time and space complexity Choose the right structure based on behavior and cost The Illusion data = [1, 2, 3] You think this stores values. Reality: [ ptr | ptr | ptr ] -> references to objects A list stores references, not values. ...

Python Is Not Running Your Code (Execution Model Deep Dive) You write Python. But Python is not executing your code the way you think. Today, you stop treating Python as magic. Today’s Goal By the end of today, you will: Understand how Python executes your code Learn what happens between .py to execution Build a mental model of the Python interpreter The Illusion You write: x = 10 y = x + 5 print(y) You assume: ...