semvec/pypi-packages huggingface dataset:
hfst-altlab 0.1.2
A python wrapper for accessing Helsinki Finite State Transducers used at ALTLab
Requires Python: >=3.9

hfst-altlab
===========

A wrapper on the [hfst][] python package, currently working as a replacement for [hfst-optimized-lookup][], built originally for [itwêwina][].

This module helps to use both analyser and generator FSTs for multiple linguistic uses and language tools.

[itwêwina]: https://itwewina.altlab.app
[hfst-optimized-lookup]: https://github.com/UAlbertaALTLab/hfst-optimized-lookup
[hfst]: https://pypi.org/project/hfst/

Languages currently supported:
  - Python

[hfst] is a great toolkit with all sorts of functionality, and is
indispensable for building FSTs, but for various applications that only
want to do unweighted hfstol lookups, this package may be easier to use.

[hfst]: https://github.com/hfst/hfst

[morphodict]: https://github.com/UAlbertaALTLab/morphodict
django-sphinx-hosting 1.7.1
Reusable Django app for hosting Sphinx documentation privately.
Requires Python: >=3.11
Keywords: documentation, sphinx, django

# django-sphinx-hosting

**Documentation**: [django-sphinx-hosting.readthedocs.org](https://django-sphinx-hosting.readthedocs.org)

This reusable Django application provides models, views, permissions, REST API
endpoints and management commands for making a private Sphinx documentation
hosting platform.

This is useful for when you want Sphinx documentation for your internal software
projects, but that is too sensitive to be shared with a third party.

## Features

* Users must be authenticated to view docs
* Multiple levels of privileges within the system based on Django authentication
* Manage multiple versions of your docs per project
* Automatically build and display navigation for each version of your documentaion
* Renders all documentation published within with a consistent theme
* Tag projects with classifiers to refine searching and filtering
* Search across all projects
* Use REST API to programmatically interact with the system.  Useful for
  integrating into a CI/CD system

## Installation and Configuration

See the [documentation](https://django-sphinx-hosting.readthedocs.org) for how
to install and configure `django-sphinx-hosting` in your Django project.
arch-mcp 0.1.0
MCP server for Python API architecture controls
Requires Python: >=3.11

# arch-mcp

[![CI](https://github.com/slahiri/arch.mcp/actions/workflows/ci.yml/badge.svg)](https://github.com/slahiri/arch.mcp/actions/workflows/ci.yml)
[![PyPI](https://img.shields.io/pypi/v/arch-mcp.svg)](https://pypi.org/project/arch-mcp/)
[![Python 3.11+](https://img.shields.io/badge/python-3.11+-blue.svg)](https://www.python.org/downloads/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

MCP server for Python API architecture controls. Validates code against architecture rules and best practices.

## Quick Start

### Option 1: Hosted (Recommended)

No install needed. Just add to your config:

**Claude Code:**
```bash
claude mcp add arch-controls --url https://arch-mcp.sid.sh/sse
```

**Cursor** (`.cursor/mcp.json`):
```json
{
  "mcpServers": {
    "arch-controls": {
      "url": "https://arch-mcp.sid.sh/sse"
    }
  }
}
```

### Option 2: Local via uvx

Run locally without installing:

**Claude Code:**
```bash
claude mcp add arch-controls -- uvx arch-mcp
```

**Cursor** (`.cursor/mcp.json`):
```json
{
  "mcpServers": {
    "arch-controls": {
      "command": "uvx",
      "args": ["arch-mcp"]
    }
  }
}
```

### Option 3: Local Install

```bash
pip install arch-mcp
```

**Claude Code:**
```bash
claude mcp add arch-controls -- arch-mcp
```

**Cursor** (`.cursor/mcp.json`):
```json
{
  "mcpServers": {
    "arch-controls": {
      "command": "arch-mcp"
    }
  }
}
```

## Tools

| Tool | Description |
|------|-------------|
| `tool_list_rules` | List architecture rules (filter by category/severity) |
| `tool_get_rule` | Get rule details with code examples |
| `tool_validate_code` | Validate code against architecture rules |
| `tool_get_project_structure` | Get recommended folder structure |
| `tool_get_best_practices` | Get best practices by category |
| `tool_check_architecture` | Check codebase for layer violations |
| `tool_get_architecture_guide` | Complete architecture guide |

## Rule Categories

- **security** - Secrets management, SQL injection prevention, input validation
- **data-access** - Repository pattern, async database operations
- **error-handling** - Custom exceptions, specific exception catches
- **api-design** - Pydantic schemas, dependency injection
- **logging** - Structured logging, no print statements
- **configuration** - Pydantic settings, environment variables
- **testing** - Pytest patterns, fixtures

## Architecture Patterns

- **clean-architecture** - Domain-driven with clear layer separation
- **feature-based** - Organized by feature/module
- **simple** - Minimal structure for small projects

## Example Usage

Once connected, ask your AI assistant:

- "List all security rules"
- "Validate this code against architecture rules"
- "Show me the recommended project structure"
- "Check if my imports follow clean architecture"

## Development

```bash
git clone https://github.com/slahiri/arch.mcp.git
cd arch.mcp
pip install -e ".[dev]"

# Run tests
PYTHONPATH=src pytest tests/ -v

# Lint
ruff check src/
```

## License

MIT