Datasets:

olegshulyakov
/

doocs-leetcode-solutions

	---
	license: cc-by-sa-4.0
	task_categories:
	- text-generation
	language:
	- en
	tags:
	- code
	pretty_name: Doocs LeetCode Solutions
	size_categories:
	- 10K<n<100K
	---

	# Doocs LeetCode Solutions

	A comprehensive dataset of LeetCode problems and solutions created from the [Doocs LeetCode](https://github.com/doocs/leetcode) repository. This dataset is designed for fine-tuning large language models to understand programming problems and generate code solutions.

	## Description

	- Repository: [Doocs LeetCode Solutions](https://github.com/doocs/leetcode)
	- Total Problems: 3500+
	- Total Solutions: 15,000+ (across multiple languages)
	- Size: ~60 MB (Parquet format)
	- Languages:
	- C
	- Cangjie
	- C++
	- C#
	- Dart
	- Go
	- Java
	- JavaScript
	- Kotlin
	- Nim
	- PHP
	- Python
	- Ruby
	- Rust
	- Scala
	- Bash
	- SQL
	- Swift
	- TypeScript

	## Structure

	### Data Fields

	\| Field \| Type \| Description \| Example \|
	\|---------------\|------------\|--------------------------------------------\|----------------------------------\|
	\| `id` \| `string` \| Problem ID \| "0001" \|
	\| `title` \| `string` \| Problem title (slugified) \| "two-sum" \|
	\| `difficulty` \| `string` \| Problem difficulty level \| "Easy", "Medium", "Hard" \|
	\| `description` \| `string` \| Problem description in Markdown \| "Given an array of integers..." \|
	\| `tags` \| `string` \| Problem category tags \| "Array; Hash Table" \|
	\| `language` \| `string` \| Programming language of solution \| "Python", "Java", "C++" \|
	\| `solution` \| `string` \| Complete solution code \| "class Solution:\n def..." \|

	### Data Splits

	The dataset contains a single comprehensive split containing all problems and solutions:

	\| Split \| Problems \| Solutions \|
	\|---------\|----------\|-----------\|
	\| `train` \| 3500+ \| 15,000+ \|

	## How to Use

	### Using Hugging Face `datasets` Library

	```python
	from datasets import load_dataset

	# Load the dataset
	dataset = load_dataset("olegshulyakov/doocs-leetcode-solutions")

	# Access a sample
	sample = dataset['train'][0]
	print(f"Problem {sample['id']}: {sample['title']}")
	print(f"Difficulty: {sample['difficulty']}")
	print(f"Tags: {sample['tags']}")
	print(f"Language: {sample['language']}")
	print(f"Solution:\n{sample['solution']}")
	```

	## Dataset Creation

	### Source Data
	- Collected from [Doocs LeetCode](https://github.com/doocs/leetcode) repository
	- Solutions cover 14+ programming languages
	- Includes problems from LeetCode's entire problem set

	### Preprocessing
	1. Repository cloned and processed using our [dataset generator tool](https://github.com/olegshulyakov/leetcode-dataset-generator).
	2. Metadata extracted from README_EN.md files.
	3. Solution files parsed and mapped to programming languages.
	4. Special characters and encoding issues resolved.

	## Intended Use

	### Primary Use
	- Fine-tuning code generation models
	- Training programming problem-solving AI
	- Educational purposes for learning algorithms

	### Possible Uses
	- Benchmarking code generation models
	- Studying programming patterns across languages
	- Analyzing problem difficulty characteristics
	- Creating programming tutorials and examples

	### Limitations
	- Solutions may not be optimal (community solutions)
	- Some edge cases might not be covered
	- Problem descriptions may contain markdown/html formatting
	- Limited to problems available in the Doocs repository

	## License
	This dataset is licensed under the CC-BY-SA-4.0 License - see [LICENSE](LICENSE) file for details.

	## Copyright
	The copyright of this project belongs to [Doocs](https://github.com/doocs) community.

	## Contact
	For questions or issues regarding the dataset, please open an issue on [GitHub](https://github.com/olegshulyakov/leetcode-dataset-generator/issues).