This repository provides a dataset of LeetCode problems in JSON format. Each problem is saved as a separate .json
file within the problems/
directory, and all problems are also combined in a single merged_problems.json
file for easy access.
problems/
: Contains individual LeetCode problems as separate.json
files. Each file is named with the problem's ID and a slug (e.g.,0001-two-sum.json
).merged_problems.json
: A single file containing all problems merged into a list.
Each problem JSON file contains the following fields:
title
: The name of the problem (e.g., "Container With Most Water").problem_id
: The internal problem ID (string).frontend_id
: The LeetCode frontend ID (string).difficulty
: The difficulty level (Easy
,Medium
, orHard
).problem_slug
: The URL-friendly name (e.g.,container-with-most-water
).topics
: Array of topic tags (e.g.,Array
,Two Pointers
).description
: The full problem statement, usually in Markdown format.examples
: Array of example objects, each with:example_num
: Example numberexample_text
: Input/output and explanationimages
: Array of image URLs (if available)
constraints
: Array of constraints or limits for the problem.follow_ups
: Array of follow-up questions (if any).hints
: Array of hints for solving the problem.code_snippets
: Object containing starter code for various languages (e.g.,python
,cpp
,java
, etc.)solutions
: HTML string containing editorial content for some problems.
{
"title": "Container With Most Water",
"problem_id": "11",
"frontend_id": "11",
"difficulty": "Medium",
"problem_slug": "container-with-most-water",
"topics": [
"Array",
"Two Pointers",
"Greedy"
],
"description": "You are given an integer array height of length n...",
"examples": [
{
"example_num": 1,
"example_text": "Input: height = [1,8,6,2,5,4,8,3,7]\\nOutput: 49\\nExplanation: ...",
"images": ["https://s3-lc-upload.s3.amazonaws.com/uploads/2018/07/17/question_11.jpg"]
},
{
"example_num": 2,
"example_text": "Input: height = [1,1]\\nOutput: 1",
"images": ["https://s3-lc-upload.s3.amazonaws.com/uploads/2018/07/17/question_11.jpg"]
}
],
"constraints": [
"n == height.length",
"2 <= n <= 105",
"0 <= height[i] <= 104"
],
"follow_ups": [],
"hints": [
"If you simulate the problem, it will be O(n^2) which is not efficient.",
"Try to use two-pointers...",
"How can you calculate the amount of water at each step?"
],
"code_snippets": {
"cpp": "class Solution {\npublic:\n int maxArea(vector<int>& height) {\n \n }\n};",
"java": "class Solution {\n public int maxArea(int[] height) {\n \n }\n}",
"python": "class Solution(object):\n def maxArea(self, height):\n \"\"\"\n :type height: List[int]\n :rtype: int\n \"\"\"\n ",
"python3": "class Solution:\n def maxArea(self, height: List[int]) -> int:\n ",
"c": "int maxArea(int* height, int heightSize) {\n \n}",
"csharp": "public class Solution {\n public int MaxArea(int[] height) {\n \n }\n}",
"javascript": "/**\n * @param {number[]} height\n * @return {number}\n */\nvar maxArea = function(height) {\n \n};",
"typescript": "function maxArea(height: number[]): number {\n \n};",
"php": "class Solution {\n\n /**\n * @param Integer[] $height\n * @return Integer\n */\n function maxArea($height) {\n \n }\n}",
"swift": "class Solution {\n func maxArea(_ height: [Int]) -> Int {\n \n }\n}",
"kotlin": "class Solution {\n fun maxArea(height: IntArray): Int {\n \n }\n}",
"dart": "class Solution {\n int maxArea(List<int> height) {\n \n }\n}",
"golang": "func maxArea(height []int) int {\n \n}",
"ruby": "# @param {Integer[]} height\n# @return {Integer}\ndef max_area(height)\n \nend",
"scala": "object Solution {\n def maxArea(height: Array[Int]): Int = {\n \n }\n}",
"rust": "impl Solution {\n pub fn max_area(height: Vec<i32>) -> i32 {\n \n }\n}",
"racket": "(define/contract (max-area height)\n (-> (listof exact-integer?) exact-integer?)\n )",
"erlang": "-spec max_area(Height :: [integer()]) -> integer().\nmax_area(Height) ->\n .",
"elixir": "defmodule Solution do\n @spec max_area(height :: [integer]) :: integer\n def max_area(height) do\n \n end\nend"
}
}
- Some fields (like
solutions
,images
,follow_ups
) may be missing for certain problems.
You can use this dataset for:
- Building practice tools
- Analyzing problem trends
- Interview preparation
- Educational projects
Feel free to contribute or suggest improvements!