File size: 2,164 Bytes
7a4607a 76ac470 7a4607a 76ac470 7a4607a 76ac470 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 |
---
language:
- en
license: cc-by-sa-4.0
tags:
- python
- stackoverflow
- question-answering
- instruct
size_categories:
- 1K<n<10K
---
# StackOverflow Python QA Dataset
[](https://github.com/meeAtif)
[](https://creativecommons.org/licenses/by-sa/4.0/)
## Description
This dataset contains high-quality Python questions and answers scraped from StackOverflow. It is designed for instruct-tuning Large Language Models (LLMs) or for question-answering tasks.
- **Source**: StackOverflow
- **Selection Criteria**:
- Tag: `python`
- Score: > 10
- Must have an **accepted answer**
- **Content**: Pairs of instructions (Question) and outputs (Accepted Answer).
## Dataset Structure
The dataset consists of the following fields:
- `question_id`: The unique identifier for the question on StackOverflow.
- `score`: The vote score of the question.
- `tags`: A list of tags associated with the question.
- `creation_date`: The timestamp of when the question was asked.
- `instruction`: The full question title and body, cleaned of HTML.
- `output`: The full body of the accepted answer, cleaned of HTML.
## Sample Entry
```json
{
"question_id": 12345,
"score": 50,
"tags": ["python", "list-comprehension"],
"instruction": "How do I create a list... \n\n I have a loop that...",
"output": "You can use a list comprehension:\n\n [x for x in iterable]"
}
```
## Usage
```python
from datasets import load_dataset
dataset = load_dataset("meeAtif/stackoverflow-python-qa")
print(dataset['train'][0])
```
## Author
[](https://github.com/meeAtif)
[](https://linkedin.com/in/meAtif)
[](mailto:iatif@proton.me)
---
*Created by [Atif](https://github.com/meeAtif)*
|