README.md

---
license: apache-2.0
dataset_info:
  features:
  - name: id
    dtype: int64
  - name: repo_name
    dtype: string
  - name: repo_owner
    dtype: string
  - name: file_link
    dtype: string
  - name: line_link
    dtype: string
  - name: path
    dtype: string
  - name: content_sha
    dtype: string
  - name: content
    dtype: string
  splits:
  - name: test
    num_bytes: 32708409
    num_examples: 50
  - name: train
    num_bytes: 8081954107
    num_examples: 10000
  download_size: 5914651135
  dataset_size: 8114662516
configs:
- config_name: default
  data_files:
  - split: test
    path: data/test-*
  - split: train
    path: data/train-*
tags:
- jupyter notebook
size_categories:
- 1K<n<10K
---

# Dataset Summary
 The presented dataset contains `10000` Jupyter notebooks, 
 each of which contains at least one error. In addition to the notebook content, 
 the dataset also provides information about the repository where the notebook is stored. 
 This information can help restore the environment if needed.
 
# Getting Started
This dataset is organized such that it can be naively loaded via the Hugging Face datasets library. We recommend using streaming due to the large size of the files.

```Python
import nbformat
from datasets import load_dataset

dataset = load_dataset(
    "JetBrains-Research/jupyter-errors-dataset", split="test", streaming=True
)
row = next(iter(dataset))
notebook = nbformat.reads(row["content"], as_version=nbformat.NO_CONVERT)
```

# Citation
```
@misc{JupyterErrorsDataset,
  title = {Dataset of Errors in Jupyter Notebooks},
  author = {Konstantin Grotov and Sergey Titov and Yaroslav Zharov and Timofey Bryksin},
  year = {2023},
  publisher = {HuggingFace},
  journal = {HuggingFace repository},
  howpublished = {\url{https://huggingface.co/datasets/JetBrains-Research/jupyter-errors-dataset}},
}
```