---
license: mit
task_categories:
- text-generation
- table-question-answering
language:
- ru
- en
tags:
- 1с
- ones
- 1C
- 1С
- один-с
pretty_name: 1C_forums_dataset_by_arefaste
size_categories:
- 1K<n<10K
configs:
- config_name: default
  data_files:
  - split: train
    path: result_final_make_dataset.parquet
---
# 1C_forums: Dataset based parsed data from two of the most popular forums for 1c 

This dataset made of the parsed data from two forums for coders at the 1C languages:
- [Infostart](https://forum.infostart.ru/group2/?a=26694) - all threads presents as like think section for model, and marked as the best result for queestion as final answer
- [Fastcode](https://fastcode.im/Templates?TemplatesOnly=True) - Only templates

## Dataset Overview
All rows prepared as useful columns. All text prepared as markdown text, and code 1c looks as like:
```md
\`\`\`1c
 "ВЫБРАТЬ
        |    Ссылка.Контрагент,
        |    Ссылка.Магазин,
        |    СУММА(КоличествоСпрос) КАК КолвоСпрос
        |ИЗ
        |    Документ.СпросНаТовар.Товары
        |ГДЕ Ссылка.Дата МЕЖДУ ДОБАВИТЬКДАТЕ(&ДатаНачало, ГОД, -10) И &ДатаНачало
        | СГРУППИРОВАТЬ ПО Ссылка.Контрагент, СсылкаМагазин";.
\`\`\`
```

### ❗IMPORTANT❗: Escaping special characters

Values in columns `prompt`, `think_process`, and `solution` have escaped special characters like `\n`, `\t`, and `\\`!

The reason for this behavior: the Python's `csv` module that I'm using in the parser to save rows saves `\n` as an actual newline character, 
which makes reading the prepared file with Pandas impossible.

To fix it use simple lambda code:
```python
return_back_special_symbols = lambda x: x.replace("\\n", "\n").replace("\\t", "\t").replace("\\\\", "\\")
```



### Infostart
Choosen data at [Infostart](https://forum.infostart.ru/group2/?a=26694) are all forums threads with found answers in section Dev.
- `source` - for all rows for Infostart forum contains this value `forum_infostart`
- `in_source_id` - id of the thread from that web forum. To get link to this page use this format: `https://forum.infostart.ru/forum9/{in_source_id}/`
- `prompt` - it's a first question(msg) in thread.
- `think_process` - its all thread discution presented as like think process that in there each msg between others separeted `\n----\n`
- `solution` - msgs marked in thread as like solution for question
- `is_answer_a_link` - if link contains a more then 60-70% of all solution, it's contains value `True`, else `False`
- `has_link` - Counter links in solution. If solution doesn't contains any link, it value will be a `Nan`
- `tags` - predicted tags


### FastCode
All data at [Fastcode](https://fastcode.im/Templates?TemplatesOnly=True) are only templates, comments for this code made as new section `# Примечание` that what shows each comment. 
- `source` - for all rows for Fastcode forum contains this value `fastcode_Templates`
- `in_source_id` - id of the thread from that web forum. To get link to this page use this format: `https://fastcode.im/Templates/{in_source_id}/`
- `prompt` - it's title of the template.
- `think_process` - **`None` - it's dont use it at all!**
- `solution` - it's description(if it's contains there) and code with notes(it's comments, if its are there)
- `is_answer_a_link` - if link contains a more then 60-70% of all solution, it's contains value `True`, else `False`
- `has_link` - Counter links in solution. If solution doesn't contains any link, it value will be a `Nan`
- `tags` - Tags at template separated by comma

## Dataset Statistics

* **Total examples**: 19041
 - forum ***infostart***: 18299
 - ***fastcode*** Template: 742

## Parsing scripts

You can find in folder `scripts_parsing`!

## Citation

Please cite this dataset if you use it in your work:

```
@misc{arefaste2025,
  title={Arefaste: Parsed dataset for 1c from dataset},
  author={arefaste},
  year={2025},
  publisher={Hugging Face},
  howpublished={\url{https://huggingface.co/datasets/arefaste/1C_Forums}}
}
```