Datasets:
Tasks:
Text Generation
Modalities:
Text
Formats:
parquet
Languages:
English
Size:
10K - 100K
Tags:
code
License:
File size: 4,059 Bytes
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---
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). |