Make your slow code run faster

@itchallenges

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Why it worked

The post provides actionable, concise tips for a common pain point among developers (slow code), making it highly shareable and saveable content. The clear visual examples and structured format enhance understanding and retention.

Summary

This post provides five tips for optimizing code performance. It covers moving database queries out of loops, eliminating nested loops, using appropriate data structures, cutting unnecessary logging, and preferring built-in functions.

Structure

1Hook: Make your slow code run faster
2Tip 1: Move database queries out of loops
3Tip 2: Get rid of nested loops
4Tip 3: Use the right data structure
5Tip 4: Cut unnecessary logging and I/O
6Tip 5: Always prefer built-in functions
7Call to action: Save this post

Product placement

The video demonstrates code optimization techniques, implying the use of a programming tool or IDE, but no specific product is named or promoted.

Original caption

#code #coding #algorithm #programming

More from @itchallenges

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Call to action

Save this post for the next time your code runs slow!

On-screen text

Make your slow code run faster SWIPE 0) Move database queries out of loops query = "SELECT * FROM users WHERE id = ?" for user_id in user_ids: user = db.query(query, user_id) process(user) query = "SELECT * FROM users WHERE id IN (?)" users = db.query(query, user_ids) for user in users: process(user) 1) Get rid of your nested loops def find_common(a, b): # O(n^2) common = [] for x in a: for y in b: if x == y: common.append(x) return common def find_common(a, b): # O(n) set_b = set(b) return [x for x in a if x in set_b] 2) Use the right data structure # Using a list participants = ["dave", "eva", "frank"] # Linear search through the list if "eva" in participants: print("Match found") # Using a set participants = {"dave", "eva", "frank"} # Constant-time check via hash table if "eva" in participants: print("Match found") 3) Cut unnecessary logging and I/O for item in items: with open("log.txt", "a") as f: f.write(f"{item}\n") buffer = [f"{item}\n" for item in items] with open("log.txt", "a") as f: f.writelines(buffer) 4) Always prefer built-in functions total = 0 for x in numbers: total += x # Faster, C-optimized total = sum(numbers) Save this post for the next time your code runs slow!