semvec/pypi-packages huggingface dataset:
mtlearn 0.1.8
Morphological tree learning utilities built on top of mmcfilters
Requires Python: >=3.9

# MTLearn

Projeto C++/Python que reutiliza o núcleo `mmcfilters::core` para experimentos
de aprendizado em árvores morfológicas.

## Organização

- `cmake/` — utilitários e módulos adicionais.
- `external/` — dependências de código fonte (submódulos ou vendorizadas).
- `src/` — código-fonte C++ da aplicação/biblioteca.
- `bindings/` — módulo pybind11 com integração PyTorch específica do projeto.
- `python/mtlearn/` — pacote Python puro.
- `tests/` — testes C++ (compilados apenas se habilitados via CMake).

## Dependência principal

Adicionar `MorphologicalAttributeFilters` como submódulo:

```bash
git submodule add https://github.com/wonderalexandre/MorphologicalAttributeFilters external/MorphologicalAttributeFilters
```

## Build C++

Build mínimo apenas com C++:

```bash
cmake -S . -B build
cmake --build build
```

- `MTLEARN_BUILD_TESTS` recompila a suíte C++/Python (padrão `OFF`).
- `MTLEARN_ENABLE_EMBED` liga os testes com interpretador embutido (exige um
  PyTorch funcional instalado no Python em uso).
- `MTLEARN_ENABLE_ASSERTS` mantém asserts do núcleo C++ ativos mesmo em build
  Release (padrão `OFF`).
- `MTLEARN_WITH_TORCH` liga o suporte ao LibTorch C++ (padrão `ON` para builds
  locais; o `pyproject.toml` força `OFF` para que `pip install mtlearn` não
  precise baixar o toolkit do PyTorch).

Para rodar o teste com interpretador embutido:

```bash
#cmake -S . -B build -DMTLEARN_BUILD_TESTS=ON -DMTLEARN_ENABLE_EMBED=ON \
#      -DPYTHON_EXECUTABLE=$(python3 -c "import sys; print(sys.executable)") \
#      -DPYTHON_LIBRARY_DIR=$(python3 -c "import sysconfig; print(sysconfig.get_config_var('LIBDIR'))")
cmake -S . -B build -DCMAKE_INSTALL_PREFIX=$(python -c "import site; print(site.getsitepackages()[0])")
cmake --build build
ctest --test-dir build -R mtl_interpreter_test --output-on-failure
```

> Antes de habilitar `MTLEARN_ENABLE_EMBED`, verifique se o ambiente consegue
> importar o PyTorch desejado (`python -c 'import torch'`). Caso contrário o
> teste será ignorado (ou o próprio PyTorch precisará ser reinstalado com um
> build compatível com o seu hardware).

## Build Python (wheel)

```bash
pip install scikit-build-core pybind11 torch
python -m build
pip install -e .
```

Para uma instalação limpa via `pyproject.toml` não são necessários argumentos
extras: os valores padrão já deixam asserts, testes e interpretador embutido
desativados.
toon-parser-async 0.1.4
Async wrapper for toon-parser - High-performance TOON format parser
Requires Python: >=3.8
Keywords: toon, async, asyncio, parser, serialization

# toon-parser-async

Async wrapper for [toon-parser](https://pypi.org/project/toon-parser/) - High-performance TOON format parser with asyncio support.

## Installation

```bash
pip install toon-parser-async
```

This will automatically install `toon-parser` as a dependency.

## Quick Start

```python
import asyncio
from toon_parser_async import encode, decode, encode_batch, decode_batch

async def main():
    # Encode data
    data = {"name": "Alice", "age": 30}
    toon_str = await encode(data)
    print(toon_str)
    
    # Decode data
    decoded = await decode(toon_str)
    print(decoded)
    
    # Batch operations
    items = [{"id": i} for i in range(10)]
    encoded_items = await encode_batch(items)
    decoded_items = await decode_batch(encoded_items)

asyncio.run(main())
```

## API

All functions are async and use `asyncio.to_thread()` to run the sync `toon-parser` functions in the thread pool:

- `async encode(data, delimiter=None, strict=None)` - Encode Python data to TOON format
- `async decode(toon_str, delimiter=None, strict=None)` - Decode TOON format to Python data
- `async dumps(data, **kwargs)` - Alias for encode
- `async loads(toon_str, **kwargs)` - Alias for decode
- `async encode_batch(data_list, **kwargs)` - Encode multiple items concurrently
- `async decode_batch(toon_strs, **kwargs)` - Decode multiple strings concurrently

## Performance

`toon-parser-async` uses the high-performance `toon-parser` Rust library under the hood, which is **5.82x faster** than other TOON implementations on average. The async wrapper adds minimal overhead while enabling concurrent I/O operations.

## Credits

- Built on [toon-parser](https://pypi.org/project/toon-parser/) by magi8101
- TOON format parser [toon-rs](https://github.com/jimmystridh/toon-rs) by Jimmy Stridh

## License

MIT License
makeapp 2.1.0
Simplifies routine Python application development processes.
Requires Python: >=3.10
Keywords: development, scaffolding

# makeapp

https://github.com/idlesign/makeapp

[![PyPI - Version](https://img.shields.io/pypi/v/makeapp)](https://pypi.python.org/pypi/makeapp)
[![License](https://img.shields.io/pypi/l/makeapp)](https://pypi.python.org/pypi/makeapp)
[![Coverage](https://img.shields.io/coverallsCoverage/github/idlesign/makeapp)](https://coveralls.io/r/idlesign/makeapp)
[![Docs](https://img.shields.io/readthedocs/makeapp)](https://makeapp.readthedocs.io/)

## Description

*Simplifies routine Python application development processes.*

* Make a skeleton for your new application with one console command.
* Automatically create a VCS repository for your application.
* Automatically check whether the chosen application name is not already in use.
* Customize new application layouts with skeleton templates.
* Put some skeleton default settings into a configuration file not to mess with command line switches anymore.
* Easily add entries to your changelog.
* Publish your application to remotes (VCS, PyPI) with a single command.
* Easily bootstrap your development environment.
* Build and local serve the docs.
* Run code styling/linting.

## Application scaffolding

Scaffold a new application:

``` bash
ma new shiny_app /home/librarian/shiny/ --description "My app." --author "I am"
```

!!! note
    `ma` is a convenient alias for `makeapp` command.

This will create a decent application skeleton using the default skeleton template (``pyproject.toml``, docs, tests, etc.)
and initialize Git repository.

`makeapp` also bundles templates for commonly used application types:

* `click` powered app
* `pytest` plugin
* `Django` app
* `webscaff` project [here](https://github.com/idlesign/webscaff)
* etc.

Multiple templates can be used together. Complete list of featured templates can be found in the documentation.
User-made templates are also supported.


## Adding changes

When you're ready to add another entry to your changelog use `change` command:

``` bash
ma change "+ New 'change' command implemented"
```

This will also stage and commit all changed files.

## Application publishing

When you're ready to publish issue the following command:

``` bash
ma release
; Bump version number part manually: major, minor, patch
ma release --increment major
```

This will automatically:

* bump up application version number
* tag version in VCS
* push sources to remote repository
* upload application package to PyPI


## Dev environment bootstrap

Or you just want to participate in the development of some other app.

Use `tools` and `up` commands to initialize tools and the environment to develop the application. 

``` bash
ma tools
ma up
```

## Code style

Apply code style with `style` command:

``` bash
ma style
```


## Build/serve docs

Use `docs` command:

``` bash
ma docs
```

## Documentation

https://makeapp.readthedocs.io/
zsxq-mcp 0.2.4
MCP server for publishing content to Zhishixingqiu (知识星球)
Requires Python: >=3.10

# ZSXQ MCP Server

知识星球 MCP 服务器 - 通过 Model Context Protocol 自动发布内容到知识星球。

## 🔥 核心功能

- ✅ 发布文字主题
- ✅ 上传并发布带图片的主题
- ✅ 从本地文件读取内容发布
- ✅ 灵活的环境变量配置
- ✅ Cookie 身份验证
- ✅ 定时发布主题
- ✅ 定时任务管理

## 📦 安装与配置

### 1. 安装 uv 工具（首次使用）

```bash
curl -LsSf https://astral.sh/uv/install.sh | sh
```

### 2. Claude Desktop 配置

直接在配置文件中使用 uvx 运行：

```json
{
  "mcpServers": {
    "zsxq": {
      "command": "uvx",
      "args": ["zsxq-mcp", "server"],
      "env": {
        "ZSXQ_COOKIE": "your_cookie_here",
        "ZSXQ_GROUP_ID": "your_group_id_here"
      }
    }
  }
}
```

重启 Claude Desktop 即可使用。

### 配置说明

| 参数 | 说明 | 必填 |
|------|------|------|
| `ZSXQ_COOKIE` | 知识星球浏览器 Cookie | ✅ |
| `ZSXQ_GROUP_ID` | 星球 ID（URL 中获取） | 🔹 |

> Cookie 获取方法：浏览器登录知识星球 → F12 开发者工具 → Network → 任意 API 请求 → 请求头 `Cookie` 字段

## 🚀 使用示例

### 在 Claude 中使用

```
帮我发布一条动态到知识星球："今天学习了 MCP 的使用方法！"
```

```
把这个文件的内容发布到知识星球：/path/to/article.txt
```

```
帮我发布一条带图片的动态，内容是"分享今天的成果"，图片路径：/path/to/screenshot.png
```

```
帮我定时发布一条动态，5分钟后发布，内容是"定时测试"
```

```
帮我查看所有定时发布的任务
```

### MCP 工具列表

| 工具 | 功能 |
|------|------|
| `publish_topic` | 发布文字主题 |
| `publish_topic_from_file` | 从文件发布内容 |
| `publish_topic_with_images` | 发布带图片的主题 |
| `upload_image` | 单独上传图片 |
| `get_group_info` | 获取星球信息 |
| `schedule_topic` | 定时发布主题 |
| `get_scheduled_jobs` | 获取定时任务列表 |

## 📌 注意事项

- 🔒 Cookie 包含登录凭证，请勿泄露
- ⏰ Cookie 可能过期，需定期更新
- 💡 未指定 `ZSXQ_GROUP_ID` 时，每次调用需手动指定

## 📁 开发相关

### 本地开发

```bash
git clone https://github.com/your-repo/zsxq-mcp.git
cd zsxq-mcp
pip install -e .
```

### 调试工具

```bash
# 使用 MCP Inspector 调试（uvx 方式）
npx @modelcontextprotocol/inspector uvx zsxq-mcp server

# 或本地开发调试
uvx zsxq-mcp server
```

## 📄 许可证

MIT License
tg-file-exporter 1.1.17
Download all files from Telegram chat
Requires Python: <3.12,>=3.9.0

# TG File Exporter

Программа для экспорта файлов из Telegram чатов.

## Установка

1. Установите uv (если у вас его ещё нет)
  
  Выберите один из способов
  
  macOS, Linux: `curl -LsSf https://astral.sh/uv/install.sh | sh`
  
  Windows: `powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"`
  
  PyPI: `pip install uv` or `pipx install uv`

2. Установите зависимости: `uv sync`
3. Склонируйте репозиторий: `git clone https://github.com/alekssamos/tg-file-exporter/`
4. Получите api_id и api_hash от [Telegram API](https://my.telegram.org/auth)
5. Замените плейсхолдеры в `tg_file_exporter/__init__.py` на реальные значения.

## Запуск

Из исходников: `uvw run -m tg_file_exporter`

Или автоматически установить из PyPI последнюю версию и запустить: `uvx tg-file-exporter`

## Использование

Программа проведет вас через пошаговый мастер:
1. Вход в аккаунт
2. Выбор чата
3. Выбор темы (если есть)
4. Выбор пути сохранения
5. Выбор типов файлов b периода
6. Непосредственно экспорт файлов

## Todo

Доделать поиск, сейчас он не работает. Пользуйтесь первой буквой в списке.


Copyright 2025 @alekssamos