Python DSA practice
Python DSA practice grouped by the patterns learners actually need.
Use this page to move from Python fundamentals into data structures and algorithms. It starts with beginner foundations, then groups interview-core practice by arrays, strings, stacks, linked lists, trees, recursion, and dynamic programming.
Best for
Learners who know Python basics and need DSA structure
Pattern groups
Arrays, strings, stacks, linked lists, trees, recursion, DP
Practice path
Foundations first, interview-core problems after
Access
Public links stay public; full lessons route through curriculum
Beginner foundation
Start with Python foundations before DSA patterns.
DSA practice goes better when loops, lists, strings, and functions are already familiar. These links give a crawl-safe warmup path before the harder full-curriculum exercises.
Iteration
Print List Items
Use a loop to visit each item before solving array-style prompts.
Array totals
Sum List Numbers
Practice accumulation, one of the most common DSA building blocks.
List foundations
Python Lists Practice
Review list scanning, filtering, and transforming before harder arrays.
String foundations
Python Strings Practice
Prepare for character counting, traversal, and exact-output prompts.
Interview-core groups
Choose a DSA group to practice next.
Each group is organized around a common pattern. Full-curriculum items point to the public curriculum overview until individual public teaser pages exist.
Practice group
Arrays and lists
Start with scanning, counting, and moving values. These patterns show up before most advanced data structures.
Accumulation
Sum List Numbers
Return one result after scanning each list value.
Array scanning
Find Maximum Value
Track the best value seen so far while reading a list.
Two pointers
Move Zeros to the End While Preserving Order
Practice stable in-place style movement without losing order.
Practice group
Strings
String DSA problems test traversal, normalization, counting, and exact edge-case handling.
Foundation
Python Strings Practice
Review traversal and formatting before interview-style string prompts.
Character counting
Count Vowels in a String
Normalize text and count selected characters with a loop.
Compression pattern
Implement Run-Length Encoding
Group adjacent characters and return a compact string representation.
Practice group
Stacks
Stack questions usually ask you to remember the most recent unmatched item and resolve it later.
Practice group
Linked lists
Linked list practice is about pointer movement, preserving references, and handling empty or single-node cases.
Pointer rewiring
Reverse a Linked List
Track previous, current, and next nodes without losing the chain.
Fast and slow pointers
Detect a Linked List Cycle
Use two speeds to find whether a cycle exists.
Tree and list bridge
Convert a BST to a Sorted Doubly Linked List
Use inorder traversal while rewiring node pointers.
Practice group
Trees and recursion
Tree practice combines recursion, traversal order, base cases, and careful return values.
Tree traversal
Implement Preorder Traversal
Visit root, left, then right with a clear recursive pattern.
Recursive return values
Compute Tree Height
Return height by combining child results.
Recursive constraints
Validate a BST
Carry min and max boundaries through the tree.
Practice group
Dynamic programming
Dynamic programming practice should start with repeated subproblems and caching before moving into larger tables.
Memoization
Compute Fibonacci With Memoization
Cache repeated recursive calls to avoid recomputing work.
State transition
Climbing Stairs
Build a recurrence from the last one or two states.
Table DP
Coin Change
Use a table to track the best answer for each amount.
Practice routine
A practical DSA routine
- 1. Restate the input, output, and edge cases before coding.
- 2. Solve the direct loop or recursive version before optimizing.
- 3. Name the pattern only after the simple version is clear.
- 4. Run visible tests, then add your own empty and single-item cases.
Related practice paths
Continue with a related Python practice path.
Python interview questions practice
Use interview-style groupings without skipping fundamentals.
Python lists practice
Build the list and array habits needed for DSA problems.
Python strings practice
Practice traversal, exact output, and character-level logic.
Python loops practice
Review iteration, counters, totals, and search loops.
Python practice hub
Start from the broader Python practice overview.