semvec/pypi-packages huggingface dataset:
zy-log 0.1.3
An advanced, asynchronous logging system for algorithmic projects.
Requires Python: >=3.8

# zy_log: 一个为算法项目定制的、专业的、异步的日志系统

[![PyPI Version](https://badge.fury.io/py/zy_log.svg)](https://badge.fury.io/py/zy_log) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

一个功能强大的 Python 日志包，专为计算密集型和算法项目设计。它通过异步 I/O 确保日志记录不会阻塞您的主计算线程，并使用 `rich` 提供美观的控制台输出和异常堆栈。

## 核心功能

* **异步非阻塞**: 所有日志 I/O (文件/控制台) 都在一个单独的后台线程中处理。
* **Rich 集成**: 自动的控制台颜色、美观的格式化和清晰的异常堆栈追踪。
* **动态配置**: 可通过参数或环境变量 (`LOG_LEVEL`) 轻松覆盖配置。
* **致命错误处理**: 提供 `logger.error_and_raise()` 方法，在记录致命错误后立即抛出异常，实现“快速失败”(Fail-Fast)。

## 安装

```bash
pip install zy_log
```

## 快速使用

您只需要在您算法的**主入口文件** (`main.py`) 中初始化一次，然后在任何子模块中调用 `get_logger` 即可。

### 1. 初始化 (在 `main.py` 中)

这是最关键的一步。

```python
# main.py
import zy_log
import os
import time
from your_project import run_my_core_algo

# --- 日志系统初始化 (仅一次) ---
# 推荐：动态指定日志文件名，并设置环境变量
log_filename = f"run_{time.strftime('%Y%m%d_%H%M%S')}.log"
os.environ['LOG_LEVEL'] = 'INFO' # 生产环境
# os.environ['LOG_LEVEL'] = 'DEBUG' # 调试时

zy_log.setup_logging(log_file_override=log_filename)
# --- 初始化完成 ---

# 默认模式下，无需指定文件名：日志会写入项目根目录的 `log/<YYYY-MM-DD>/<basename>_<HH-MM-SS>.log`，
# 同一天的运行会自动聚合到同一日期文件夹中，便于快速定位每次运行。

# 获取主模块的 logger
logger = zy_log.get_logger(__name__)

logger.info(f"算法启动，日志将记录到: {log_filename}")

# 运行您的核心算法
try:
    run_my_core_algo()
    logger.info("算法运行成功结束。")
except Exception as e:
    logger.critical(f"算法主流程意外崩溃: {e}", exc_info=True)

```

### 2. 在任意子模块中使用

在您的任何算法子模块中：

```python
# your_project/core_algo.py
import zy_log
import time

# [关键] 直接获取 logger，它已经被 main.py 配置好了
logger = zy_log.get_logger(__name__)

def run_my_core_algo():
    
    # 1. 记录正常流程 (Normal)
    logger.info("开始加载数据模型...")
    
    # 2. 记录警告 (Warning)
    logger.warning("检测到 5% 的缺失值，将使用均值填充。")
    
    # 3. 记录致命错误 (Error)
    try:
        if "关键数据" is None:
            # 这会记录一个红色的 Error 日志，然后抛出 RuntimeError
            logger.error_and_raise("关键数据为 None，算法无法继续！")
            
    except RuntimeError as e:
        logger.error(f"算法因致命错误中断: {e}")
        raise # 必须重新抛出，让上层知道

```

## 贡献

欢迎提交 PR 或 Issue。

## 许可证

本项目使用 [MIT License](LICENSE) 授权。
quarto-batch-convert 2025.9.2
Converts multiple Jupyter notebooks to Quarto documents at once
Requires Python: >=3.13
Keywords: quarto, jupyter, notebook, converter, cli

# Quarto Batch Converter

## Description

Quarto Batch Converter is a utility that converts `ipynb` files to `qmd` files using the [Quarto command line](https://quarto.org/). This tool is designed to simplify the process of converting multiple `ipynb` files at once, making it ideal for large projects or batch conversions.

This cli is equivalent to perform the following statement on multiple times:

```sh
quarto convert file.ipynb
```

## Features

* Converts files to files using `quarto convert` (`ipynb` to `qmd`, `qmd` to `ipynb`) 
* Filters file based on extension (default: `ipynb`)
* Filters file based on a match pattern that could be replaced for the output file (e.g. `_test.ipynb` -> `test.qmd`)
* Preserves the original directory structure of the input files
* Allows specifying a prefix for the converted files
* Supports glob style paths as well as recursion in the subdirectory

## Installation

To install Quarto Batch Converter, run the following command:
```bash
pipx install quarto_batch_convert
```
This will install the package and make the `quarto_batch_convert` and its alias `qbc` command line available.

## Usage

To use Quarto Batch Converter, navigate to the directory containing the `ipynb` files you want to convert and run the following command:
```bash
quarto_batch_convert <input_paths> [options]
```
Replace `<input_paths>` with one or more directory paths, file paths, or glob patterns to search for `ipynb` files.

### Options

* `-e`, `--extension`: File extension to filter files when input is a directory (default: `.ipynb`)
* `-m`, `--match-replace-pattern`: Match pattern and optional replace pattern, separated by a forward slash. If no slash is present, only matching is performed.
* `-p`, `--prefix`: Prefix to add to the new file name
* `-k`, `--keep-extension`: Keep the original extension as part of the filename
* `-o`, `--output-path`: Output path where to generate the `.qmd` files (default: current directory)
* `-r`, `--recursive`: Search files recursively when input is a directory

### Examples

* Convert all `ipynb` files in the current directory (no subdirectory):
```bash
quarto_batch_convert .
```
* Convert all `ipynb` files in the `notebooks` directory and its subdirectories:
```bash
quarto_batch_convert notebooks -r
```
* Convert all `ipynb` files in the `notebooks` directory and add a prefix `converted_` to the output files:
```bash
quarto_batch_convert notebooks -p converted_
```
* Convert all `ipynb` files in the `notebooks` directory and replace the string `old_` with `new_` in the file names:
```bash
quarto_batch_convert notebooks -m old_/new_
```
## Contributing

Contributions to Quarto Batch Converter are welcome. If you have any issues or feature requests, please submit a pull request or open an issue on the GitHub repository.

## License

Quarto Batch Converter is licensed under the [MIT License](https://opensource.org/licenses/MIT).
qiskit-ibm-ai-local-transpiler 0.5.5
This package allows you to run a local version of the Qiskit AI-powered transpiler passes.
Requires Python: >=3.10
Keywords: qiskit, quantum circuit, quantum computing, AI, AI transpiler, Qiskit AI, quantum, sdk

# AI Transpiler Local

This package allows you to run a local version of the AI-powered transpiler passes.

## Using the AI Transpiler locally

Check out the related documentation in <https://docs.quantum.ibm.com/guides/ai-transpiler-passes>

## Run tests locally

### Quick start (recommended)

1. Sync dependencies:
   ```bash
   uv sync
   ```

2. Run tests:
   ```bash
   uv run pytest tests
   ```

### Using a specific Python version

Create a virtual environment with a specific Python version (3.10-3.14 supported):

```bash
# Create venv with desired Python version
uv venv --python 3.14

# Activate the environment
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

# Install the package and test dependencies
uv pip install . pytest pytest-asyncio

# Run tests
pytest tests
```