I thought I was a Python wizard when I mastered lists and dicts. I wasn’t. Python hides some powerful data structures in plain sight, and knowing them will make you look like you’ve been coding since Guido first wrote print("Hello World").
Here are 9 data structures that every serious Python developer should know. Trust me, these aren’t your everyday list comprehensions.
1. deque (Because Lists Get Slow When You’re in a Hurry)
You’ve probably used lists as queues, right? Append at the end, pop from the front. But here’s the kicker: lists are terrible at this. Removing from the front is O(n).
Enter collections.deque: lightning-fast for appending and popping from both ends.
from collections import dequeq = deque()
q.append('task1')
q.append('task2')
print(q.popleft()) # task1
Pro Tip: When you need real-time log buffers or job queues, deque is your secret weapon.
2. defaultdict (No More “KeyError” Headaches)
Ever wrote this?
if key not in d:
d[key] = []
d[key].append(value)
