Metadata-Version: 2.5
Name: md2gost
Version: 1.0.0
Summary: Markdown to DOCX formatted per GOST 7.32-2017 (Russian standard for reports)
Project-URL: Homepage, https://github.com/EDeev/my_converterbot
Project-URL: Issues, https://github.com/EDeev/my_converterbot/issues
Project-URL: Bot, https://t.me/my_convbot
Author-email: Egor Deev <egor@deev.space>
License-Expression: MIT
License-File: LICENSE
Keywords: converter,docx,gost,markdown,report,word
Classifier: Environment :: Console
Classifier: Natural Language :: Russian
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Office/Business :: Office Suites
Classifier: Topic :: Text Processing :: Markup :: Markdown
Requires-Python: >=3.9
Requires-Dist: python-docx>=1.1
Description-Content-Type: text/markdown

# My Converter Bot · md2gost

[Русский](https://github.com/EDeev/my_converterbot/blob/main/README.md) · **English**

[![CI](https://github.com/EDeev/my_converterbot/actions/workflows/ci.yml/badge.svg)](https://github.com/EDeev/my_converterbot/actions/workflows/ci.yml)
[![PyPI](https://img.shields.io/pypi/v/md2gost)](https://pypi.org/project/md2gost/)
[![Python](https://img.shields.io/pypi/pyversions/md2gost)](https://pypi.org/project/md2gost/)
[![License](https://img.shields.io/github/license/EDeev/my_converterbot)](https://github.com/EDeev/my_converterbot/blob/main/LICENSE)

A Markdown to DOCX converter that follows GOST 7.32-2017 (the Russian standard for research and student
reports), plus a Telegram bot for study routine: send a `.md` and get a report ready to submit, send a
project `.zip` and get a `.txt` with the folder tree and file contents. The converter is installable on its
own as the `md2gost` package on PyPI. The bot speaks Russian.

**Status:** personal project, maintained · bot [@my_convbot](https://t.me/my_convbot) ·
package [md2gost](https://pypi.org/project/md2gost/)

![Pages of a report built with md2gost](https://raw.githubusercontent.com/EDeev/my_converterbot/main/docs/demo.png)

**Stack:** Python 3.9+ · python-docx · aiogram 3 · Docker

## md2gost — Markdown → DOCX per GOST

```bash
pip install md2gost
md2gost report.md                 # writes report.docx next to it
md2gost report.md -o out.docx --no-heading-numbers
```

What it does to the document:

- margins: left 30 mm, right 15, top and bottom 20; Times New Roman 14 pt, 1.5 line spacing, 1.25 cm first-line indent, justified text
- page numbers at the bottom center, none on the title page
- section numbering `1.`, `1.1.`, `1.1.1.`; structural elements ("Введение", "Заключение", "Список
  литературы" and others) unnumbered, uppercase, centered
- a page break before every second-level section
- bulleted lists with dashes and nesting, numbered lists as `1)` with numbering restarted per list
- tables with a "Таблица N" caption on the top left, code blocks and inline code in a monospace font,
  quotes, footnotes `[^1]`, bold and italic

Command-line options: `--font`, `--size`, `--spacing`, `--no-heading-numbers`, `--no-page-numbers`,
`--number-title-page`. From Python:

```python
from md2gost import DocumentSettings, MarkdownToDocxConverter

settings = DocumentSettings()
settings.auto_numbering_headings = True
MarkdownToDocxConverter(settings).convert("report.md", "report.docx")
```

The Markdown parser is custom and line-based: nested tables and lists inside tables are not supported.

## The bot

| Send | Get |
|---|---|
| `.md` | a GOST-formatted `.docx` (the same md2gost, with heading numbers) |
| project `.zip` | a `.txt`: folder tree and contents of text files with line numbers, handy for an LLM or a report appendix |

Files up to 20 MB. Archives are checked before extraction: at most 5000 files and 200 MB unpacked. Service
folders (`.git`, `node_modules`, `__pycache__`, `build`…) and binary files are skipped. Conversion runs in
a separate thread, so the bot never freezes on big files.

```bash
git clone https://github.com/EDeev/my_converterbot.git && cd my_converterbot
cp .env.example .env      # BOT_TOKEN from @BotFather
docker compose up -d
```

Prebuilt image: `docker pull ghcr.io/edeev/my_converterbot` or `docker pull dcr.deev.su/edeev/my_converterbot`.
Without Docker: `pip install -r requirements.txt`, then `BOT_TOKEN=… python bot.py`.

`rep_to_txt.py` also works on its own: `python rep_to_txt.py path/to/project`.

## Development

```bash
pip install -r requirements-dev.txt
ruff check --select E9,F,B . && pytest
```

CI tests the package on Python 3.9, 3.12 and 3.13 and builds it. On `v*` tags the package is published to
PyPI and the bot's Docker image to GitHub Packages and `dcr.deev.su`.

## License

MIT — see [LICENSE](https://github.com/EDeev/my_converterbot/blob/main/LICENSE).

## Author

**Egor Deev** — [GitHub](https://github.com/EDeev) · [Telegram](https://t.me/DeevEgor) · [egor@deev.space](mailto:egor@deev.space)
