Hash Table from Scratch in Python: Chaining, Resizing and Interview Questions
Build a hash table in Python from scratch with chaining and open addressing, then see collisions, resizing, bad hashes and the tombstone bug that catches most candidates.
Master coding interview patterns
Clear, step-by-step guides to data structures, algorithms and LeetCode problems, with Python solutions and complexity analysis.
two_sum.py
def two_sum(nums, target):
seen = {}
for i, n in enumerate(nums):
need = target - n
if need in seen:
return [seen[need], i]
seen[n] = i
# One pass, O(n) time, O(n) space- 26in-depth guides
- 10topics
- Pythoncode in every guide
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Every guide belongs to one topic, so you can study in order.
- Arrays & Strings6 articlesHash maps, two pointers and sliding window: the patterns behind most beginner and medium problems.
- Backtracking & Recursion1 articleBacktracking interview problems in Python: subsets, permutations, combination sum, parentheses and grid search, with a reusable template and tested code.
- Binary Search1 articleSearch templates, boundaries and searching on the answer.
- Dynamic Programming2 articlesFrom recursion to memoization to tabulation, with classic problems.
- Greedy and Intervals2 articles
- Heaps & Priority Queues1 articleHeap and priority queue interview problems in Python: top K, merge K sorted lists and running medians, with tested code and complexity analysis.
- Interview Tips5 articlesStudy plans, habits and strategy for coding interviews.
- Linked Lists & Stacks2 articlesPointer manipulation, fast and slow pointers, dummy nodes and stack-based problems.
- System Design1 articleHow to approach design interviews: requirements, estimates, components and trade-offs.
- Trees & Graphs5 articlesDFS, BFS, traversals and grid problems explained step by step.
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Build a trie in Python with prefix search, autocomplete and wildcard matching, then see when a sorted list with bisect…
A four week study plan
Full roadmap →Foundations
Arrays, strings and hash maps. Learn to spot when a lookup table removes a nested loop. Start here.
Core patterns
Two pointers, sliding window and binary search cover a huge share of easy and medium problems. Binary search.
Trees and graphs
Recursion, DFS, BFS and backtracking. Practise drawing the call stack before you code. Trees and graphs.
Dynamic programming
Move from recursion to memoization to tabulation, then do timed mock interviews. Dynamic programming.
How we write our guides
Interview preparation is mostly about understanding, not memorising answers. Each article explains the idea in plain language first, then shows the code.
- Problem statement and a simple worked example before any code.
- Brute force first, then the improvement, so you see why it works.
- Python solutions with time and space complexity stated.
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- Found a mistake? Tell us through the contact page and we will correct it.
Built and edited by Nilesh Kumar
I am a second-year BTech student and the person behind LeetPrep. I choose every topic, review and edit each guide before it goes live, and read every message that comes through the contact page. Code examples are tested before they are published.
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