Trace runs Python code line-by-line in your browser (via Pyodide / WebAssembly) and visualizes every variable mutation: heaps as trees, linked lists as chains, grids as cells, sets/dicts/queues as native shapes. Perfect for understanding LeetCode solutions, teaching algorithms, or debugging tricky logic.
Supported Input Formats
nums = [1,2,3], target = 9 standard LeetCode format
Paste directly from LeetCode, Input: prefix handled automatically
Auto-Save & Persistence
Your code and test input are saved to your browser's local storage automatically as you type. Reload the page anytime, your work is preserved. Use Save Snippet to keep a named copy of any solution you want to revisit.
Sharing
Click Share to generate a URL that encodes your code + input. Anyone with the link can open the same scenario in their browser, no account required.
Tips
The bar at the very top shows your playback progress through all snapshots.
Variables that changed since the last step are highlighted in green.
Heap visualizations show raw stored values. For negated max-heaps, you'll see negative numbers.
For OOP problems, instance attributes (self.x) are auto-captured and shown.
If execution hangs, the runtime caps at 1000 steps to protect against infinite loops.
Tr
Welcome to TRACE
Your Python algorithm visualizer
Write or pick your code
Paste any Python algorithm in the left panel, or pick a ready-made example from the Algorithm dropdown in the header.
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Use the Array · Binary Search dropdown in the header to load built-in examples instantly.
class Solution: def twoSum(self, nums, target): seen = {} for num in nums:
Add your test input
Type your test case in the TEST INPUT box at the bottom-left. LeetCode format works directly, just paste it in.
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Example: nums = [2,7,11,15], target = 9. Your input auto-saves every time.
02 TEST INPUT
nums = [2,7,11,15], target = 9
✓ PARSED
Hit RUN, watch it come alive
Click RUN (or press ⌘/Ctrl + Enter). Your code executes line-by-line inside your browser. No server, no install.
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The right panel fills with your variables, arrays, trees, and graphs, all live.
▶ RUN
nums[2, 7, 11, 15]
target9
seen{2: 0}
Step through every line
Use the ← → arrows (or keyboard arrow keys) to move one step at a time. Watch exactly which variable changes at each line.
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Green highlights = something just changed. Press Space to auto-play.
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Step 4 / 12
Visualize any data structure
Arrays, linked lists, binary trees, heaps, grids, graphs: all rendered as visual shapes. Recursion auto-builds a call-tree.
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Try "Binary Tree · Max Depth" or "Heap · K Closest Points" from the dropdown!
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Analyze time & space complexity
After running, click the O(n) button in the bottom bar. Every line gets a complexity badge with a plain-English reason why.
↓Perfect for interview prep. Understand why your algorithm is O(n) or O(n²).
O(n)two pointers converge, each element once
O(1)array access, constant time
O(1)in-place swap, no auxiliary array
TOTAL → TIME O(n) | SPACE O(1)
💾 Save Snippet
Give this snippet a memorable name. It will be saved in your browser only.
Tip: existing snippet with the same name will be overwritten.
Find the Pattern
Paste any DSA problem statement — LeetCode, an interview question, anything. Runs entirely in your browser (no API key, no network call) and walks the same thought process every time: restate it, find the brute force, spot the waste, read the constraints, name the pattern, and check the traps.
🔗 Share This Trace
Copy this URL. Anyone who opens it will see exactly your code & test input.
The URL contains your code (encoded). It works without any backend or account.
Report a Problem
Something not working, or a wrong visualization? Tell us what happened. Your current code & test input are attached automatically so we can reproduce it.
We attach: your code, test input, current step, theme, and browser info. No personal data.