The dataset viewer is not available for this dataset.
The dataset tries to import a module that is not installed.
Error code:   DatasetModuleNotInstalledError
Exception:    ImportError
Message:      To be able to use IlyaGusev/ru_stackoverflow, you need to install the following dependency: jsonlines.
Please install it using 'pip install jsonlines' for instance.
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 72, in compute_config_names_response
                  config_names = get_dataset_config_names(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 347, in get_dataset_config_names
                  dataset_module = dataset_module_factory(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1910, in dataset_module_factory
                  raise e1 from None
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1876, in dataset_module_factory
                  return HubDatasetModuleFactoryWithScript(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1498, in get_module
                  local_imports = _download_additional_modules(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 353, in _download_additional_modules
                  raise ImportError(
              ImportError: To be able to use IlyaGusev/ru_stackoverflow, you need to install the following dependency: jsonlines.
              Please install it using 'pip install jsonlines' for instance.

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Russian StackOverflow dataset

Description

Summary: Dataset of questions, answers, and comments from ru.stackoverflow.com.

Script: create_stackoverflow.py

Point of Contact: Ilya Gusev

Languages: The dataset is in Russian with some programming code.

Usage

Prerequisites:

pip install datasets zstandard jsonlines pysimdjson

Loading:

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:

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

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.

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Models trained or fine-tuned on IlyaGusev/ru_stackoverflow