# Distilled • LeetCode

## Intro

- Distilled set of LeetCode problems for learning data structures and algorithms solved using Python 3.
- Refer Python Tips and Tricks for an review of data structure concepts and their implementations with Python 3.
- Note that recursive (top-down) implementations store call-stacks (and hence are not \(O(1)\) space complexity). For \(O(1)\) space complexity, the computations must be performed iteratively (bottom-up) without using call-stacks.
- Here’s a list of the full problem set on LeetCode.

## General Tips

- These tips are from Sean Prasad’s LeetCode Patterns Github repo.

```
If input array is sorted, then
- Binary search
If input array is not necessarily sorted, then
- Sliding window
- Two pointers
If asked for all permutations/combinations/subsets, then
- Backtracking
If given a tree/graph/grid, then
- DFS
- BFS
If given a linked list then
- Two pointers
If recursion is banned then
- Stack
If must solve in-place then
- Swap corresponding values
- Store one or more different values in the same pointer
If asked for maximum/minimum subarray/subset/options then
- Dynamic programming
If asked for top/least K items then
- Heap
If asked for common strings then
- Map
- Trie
Else
- Map/Set for O(1) time & O(n) space
- Sort input for O(nlogn) time and O(1) space
- A subarray or substring will always be contiguous, but a subsequence need not be contiguous, i.e., subsequences are not required to occupy consecutive positions within the original sequences.
```

- Check out LeetCode patterns sorted by companies/difficulty level/patterns here.

## Patterns

- Sorting/Searching
- Two Pointers
- Sliding Window
- Binary Search
- Hash Table
- Heap
- DFS
- BFS
- DP
- Graphs
- Grid
- Stack
- Trie
- Topological Sort
- Misc

## Concepts

## Further Reading

- Python for Interviewing: An Overview of the Core Data Structures
- NeetCode 150/Blind 75
- Blind 50
- Blind 75; mirror
- Grind 75
- LeetCode Solutions
- Sean Prasad: Leetcode Patterns