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---
license: other
task_categories:
- text-generation
- question-answering
language:
- ru
size_categories:
- 100K<n<1M
dataset_info:
features:
- name: question_id
dtype: uint32
- name: url
dtype: string
- name: answer_count
dtype: uint32
- name: text_html
dtype: string
- name: text_markdown
dtype: string
- name: score
dtype: int32
- name: title
dtype: string
- name: tags
sequence: string
- name: views
dtype: uint64
- name: author
dtype: string
- name: timestamp
dtype: uint64
- name: comments
sequence:
- name: text
dtype: string
- name: author
dtype: string
- name: comment_id
dtype: uint32
- name: score
dtype: int32
- name: timestamp
dtype: uint64
- name: answers
sequence:
- name: answer_id
dtype: uint32
- name: is_accepted
dtype: uint8
- name: text_html
dtype: string
- name: text_markdown
dtype: string
- name: score
dtype: int32
- name: author
dtype: string
- name: timestamp
dtype: uint64
- name: comments
sequence:
- name: text
dtype: string
- name: author
dtype: string
- name: comment_id
dtype: uint32
- name: score
dtype: int32
- name: timestamp
dtype: uint64
splits:
- name: train
num_bytes: 3013377174
num_examples: 437604
download_size: 670468664
dataset_size: 3013377174
---
# Russian StackOverflow dataset
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Description](#description)
- [Usage](#usage)
- [Data Instances](#data-instances)
- [Source Data](#source-data)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Licensing Information](#licensing-information)
## Description
**Summary:** Dataset of questions, answers, and comments from [ru.stackoverflow.com](https://ru.stackoverflow.com/).
**Script:** [create_stackoverflow.py](https://github.com/IlyaGusev/rulm/blob/hf/data_processing/create_stackoverflow.py)
**Point of Contact:** [Ilya Gusev](ilya.gusev@phystech.edu)
**Languages:** The dataset is in Russian with some programming code.
## Usage
Prerequisites:
```bash
pip install datasets zstandard jsonlines pysimdjson
```
Loading:
```python
from datasets import load_dataset
dataset = load_dataset('IlyaGusev/ru_stackoverflow', split="train")
for example in dataset:
print(example["text_markdown"])
print()
```
## Data Instances
```
{
"question_id": 11235,
"answer_count": 1,
"url": "https://ru.stackoverflow.com/questions/11235",
"score": 2,
"tags": ["c++", "сериализация"],
"title": "Извлечение из файла, запись в файл",
"views": 1309,
"author": "...",
"timestamp": 1303205289,
"text_html": "...",
"text_markdown": "...",
"comments": {
"text": ["...", "...",
"author": ["...", "..."],
"comment_id": [11236, 11237],
"score": [0, 0],
"timestamp": [1303205411, 1303205678]
},
"answers": {
"answer_id": [11243, 11245],
"timestamp": [1303207791, 1303207792],
"is_accepted": [1, 0],
"text_html": ["...", "..."],
"text_markdown": ["...", "..."],
"score": [3, 0],
"author": ["...", "..."],
"comments": {
"text": ["...", "..."],
"author": ["...", "..."],
"comment_id": [11246, 11249],
"score": [0, 0],
"timestamp": [1303207961, 1303207800]
}
}
}
```
You can use this little helper to unflatten sequences:
```python
def revert_flattening(records):
fixed_records = []
for key, values in records.items():
if not fixed_records:
fixed_records = [{} for _ in range(len(values))]
for i, value in enumerate(values):
fixed_records[i][key] = value
return fixed_records
```
The original JSONL is already unflattened.
## Source Data
* The data source is the [Russian StackOverflow](https://ru.stackoverflow.com/) website.
* Original XMLs: [ru.stackoverflow.com.7z](https://ia600107.us.archive.org/27/items/stackexchange/ru.stackoverflow.com.7z).
* Processing script is [here](https://github.com/IlyaGusev/rulm/blob/hf/data_processing/create_stackoverflow.py).
## Personal and Sensitive Information
The dataset is not anonymized, so individuals' names can be found in the dataset. Information about the original authors is included in the dataset where possible.
## Licensing Information
According to the license of original data, this dataset is distributed under [CC BY-SA 2.5](https://creativecommons.org/licenses/by-sa/2.5/).