semvec/pypi-packages huggingface dataset:
asciidoc-dita-toolkit 2.1.5
AsciiDoc DITA Toolkit - unified package for technical documentation workflows
Requires Python: >=3.8
Keywords: asciidoc, dita, documentation, technical-writing, content-validation

# AsciiDoc DITA Tool

**👉 Complete documentation and tutorials:** https://rolfedh.github.io/asciidoc-dita-toolkit/
## 📋 Prerequisites

### Option 1: Python Package
- **Python 3.8+** - Required for the package installation (we recommend upgrading to Python 3.8+)
- **pip** - Python package manager
- *Note: If you're using Python 3.7, please use the container option below*

### Option 2: Container
- **Docker** or **Podman** - Container runtime
- **curl** - For downloading the wrapper script
- *Recommended for users on Python 3.7 or those who prefer containerized tools*

## 🚀 Quick Start

[![PyPI version](https://img.shields.io/pypi/v/asciidoc-dita-toolkit.svg)](https://pypi.org/project/asciidoc-dita-toolkit/)
[![Container](https://img.shields.io/badge/container-ghcr.io-blue?logo=docker)](https://github.com/rolfedh/asciidoc-dita-toolkit/pkgs/container/asciidoc-dita-toolkit-prod)
[![Python 3.8+](https://img.shields.io/badge/python-3.8+-blue.svg)](https://www.python.org/downloads/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

A command-line toolkit for technical writers to review and fix AsciiDoc content for DITA-based publishing workflows.

##  What is this?

The AsciiDoc DITA Toolkit helps you:

- **Find and fix** common issues in `.adoc` files before publishing
- **Apply automated checks** and transformations using a plugin system
- **Ensure consistency** across large documentation projects
- **Integrate** with your existing documentation workflow

## � Documentation

**👉 Complete documentation and tutorials:** https://rolfedh.github.io/asciidoc-dita-toolkit/

## 🚀 Quick Start

### Option 1: Python Package (Recommended)

```sh
# Install
pip install asciidoc-dita-toolkit

# Use
adt --help
adt --list-plugins
```

### Option 2: Container

```sh
# One-time setup: Download and install adt wrapper
curl -sSL https://raw.githubusercontent.com/rolfedh/asciidoc-dita-toolkit/main/scripts/adt-docker -o /usr/local/bin/adt && chmod +x /usr/local/bin/adt

# Use
adt --help
adt --list-plugins
```

## � Basic Usage

```sh
# Fix HTML entity references
adt EntityReference -r

# Add content type labels
adt ContentType -r
```

## 🛠️ Troubleshooting

If you encounter issues like "Failed to load module" or "No module named 'modules'" errors, see our [Troubleshooting Guide](docs/TROUBLESHOOTING.md) for solutions.

Common fixes:
- Remove conflicting packages: `pip uninstall adt-core`
- Clear package cache: `pip cache purge`
- Reinstall: `pip install --upgrade asciidoc-dita-toolkit`

## 🤝 Contributing

- **Documentation**: https://rolfedh.github.io/asciidoc-dita-toolkit/
- **Issues**: https://github.com/rolfedh/asciidoc-dita-toolkit/issues
- **Contributing Guide**: [docs/CONTRIBUTING.md](docs/CONTRIBUTING.md)
- **Troubleshooting**: [docs/TROUBLESHOOTING.md](docs/TROUBLESHOOTING.md)

## 📄 License

MIT License - see [LICENSE](LICENSE) file for details.
mcp-logger 0.1.23
Python SDK for tool usage logging and monitoring
Requires Python: >=3.8

# Observe Python SDK

A Python SDK for MCP tool and prompt usage logging and monitoring.

## Installation

```bash
pip install observee
```

## Usage

You can set the MCP server name either globally or per decorator:

### Global Configuration

```python
from observee import ObserveeConfig, observee_usage_logger

# Set the MCP server name globally
ObserveeConfig.set_mcp_server_name("your-mcp-server-name")

# Auto-detection based on function name
@observee_usage_logger
async def your_tool_function():
    # Your tool code here
    pass

@observee_usage_logger
async def generate_prompt():
    # Your prompt code here - auto-detected as prompt
    pass
```

### API Key Configuration (Developers and Enterprise Customers)

```python
from observee import ObserveeConfig

# Set your API key
ObserveeConfig.set_api_key("your-api-key")
```

### Unified Usage Logging

```python
from observee import ObserveeConfig, observee_usage_logger

# Auto-detection based on function name (recommended)
@observee_usage_logger()
async def your_tool_function():
    # Your tool code here
    pass

@observee_usage_logger()
async def generate_prompt():
    # Your prompt code here
    pass

```

## Features

- **Unified decorator** for both tool and prompt usage logging with async support
- **Auto-detection** of usage type based on function names (or explicit specification)
- Automatic logging of:
  - Tool/prompt name
  - Input parameters
  - Response data
  - Execution duration (for tools only)
  - Error information (if any)
- Configurable logging endpoint (defaults to Observe API)
- Error handling and reporting
- Performance tracking (for tools only)
- Flexible MCP server name configuration
- API key support for enhanced features
- Privacy protection: Input/response data only logged when API key is provided


## Logging Details

### Unified Usage Logging

The SDK uses a single `@observee_usage_logger()` decorator that can automatically detect whether you're logging a tool or prompt based on the function name, or you can specify explicitly:

**Auto-detection**: Functions containing keywords like 'prompt', 'template', or 'message' in their name are detected as prompts. All others are treated as tools.

**Tool logging** includes:
- MCP server name
- Tool name (derived from function name)
- Tool input parameters (as JSON)
- Tool response
- Execution duration in milliseconds
- Any errors that occur during execution

**Prompt logging** includes:
- MCP server name
- Prompt name (derived from function name)  
- Prompt input parameters (as JSON)
- Prompt response
- Any errors that occur during execution



### Privacy Protection

For privacy protection, detailed input and response data is only logged when an API key is configured. Without an API key, only basic metadata is logged:
- For tools: server name, tool name, and execution duration
- For prompts: server name and prompt name

Logs are sent asynchronously to avoid impacting tool/prompt performance.

## Requirements

- Python 3.8 or higher
- Dependencies:
  - httpx
  - pydantic

## License

GPL v3 - see [LICENSE](LICENSE) file for details
pluginspy 0.2.20
Plugins Framework
Requires Python: >=3.0

# README

* 最初的目的是管理多个Python脚本，省得脚本放在不同的地方不好找，也是软件名称由来
* 第一次进化：可以在命令行选择脚本运行，参数在脚本中硬编码
* 第二次进化：使用PyQt5增加UI界面，不仅可以选择脚本运行，也可以修改参数
* 第三次进化：增加直接数据可视化解析、可视化、模版生成
* 第四次进化：matplotlib绘图和PyQt5绘图进程分离，配置可保存

# docs

NO.  |文件名称|摘要
:---:|:--|:--
0003 | [PyQt5_UI选择插件运行](docs/0003_PyQt5_UI选择插件运行.md) | UI运行插件
0002 | [cmd插件管理功能](docs/0002_cmd插件管理功能.md) | 以Plugin的形式集成命令行脚本，便于脚本的集中管理
0001 | [PyPi发布版本](docs/0001_PyPi发布版本.md) | 发布软件
burger 1.5.1
Burger Becky's shared python library.
Requires Python: !=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,>=2.7
Keywords: burger, perforce, burgerlib, development, python, windows

=================
Burger for Python
=================

|PyPi| |License| |GithubActions| |Docs| |Versions|

The ``burger`` module is a set of simple subroutines used by the ``Burgerlib``
build system.

* Documentation is found at https://pyburger.readthedocs.io

* Doxygen generated documentation is found at https://pyburger.readthedocs.io/en/latest/doxygen

* Python Packing Index (PyPI): https://pypi.python.org/pypi/burger

* Source code and issue tracker: https://github.com/burgerbecky/pyburger

Compatibility
-------------

* Python 2.7.1 or higher
* Python 3.4 or higher

Installation
------------

Type in ``pip install -U burger``. Some platforms may require the ``sudo``
prefix.

Bugs
----

If you find a bug, issue or have a feature request, please submit a bug report
by emailing becky@burgerbecky.com and mention python version, integer
size (32 bit or 64 bit) and what platform was used (Windows / Mac OSX / Linux).

.. |PyPi| image:: https://img.shields.io/pypi/v/burger.svg
    :target: https://pypi.org/project/burger/
    :alt: Pypi Version
.. |License| image:: https://img.shields.io/pypi/l/burger.svg
    :target: https://github.com/burgerbecky/pyburger/blob/master/LICENSE.txt
    :alt: License
.. |GithubActions| image:: https://github.com/burgerbecky/pyburger/actions/workflows/python-build.yml/badge.svg
    :target: https://github.com/burgerbecky/pyburger/actions
    :alt: Github Actions Status
.. |Docs| image:: https://img.shields.io/readthedocs/pyburger.svg
    :target: http://pyburger.readthedocs.io
    :alt: Documentation Status
.. |Versions| image:: https://img.shields.io/pypi/pyversions/burger.svg
    :alt: Supported Python versions