semvec/pypi-packages huggingface dataset:
autopush 0.1.1
autopush cli tool allows to run git commands more simply
Requires Python: >=3.7

<p> Description: <b>autogit-cli</b> designed to guide users through common Git tasks interactively, which can be useful in projects requiring frequent updates, as it minimizes manual Git commands by offering a user-friendly CLI interface.</p>

<p><a href="#error-fix">Error `autogit` is not recognized. For help click me</a></p>

## INSTALLATION


<h1 align=center >pip install autopush</h1>


| Function    |  Auto Fetch     |
|-------------|----------------|
| `.gitignore` | node_modules/,dist/,.env,*.log,coverage/,.DS_Store,git_history.json and  more . . .
| `[+added, -removed]`     | **main.py [+56 ] [-6 ], index.js [+27 ] [-3 ],index.js [+10] [-3]** |
|`commit suggest`| *'Updated files', 'Refactor code', 'Fix bugs', 'Enhance performance', 'Add new feature', and more . . .*|
|`branch fetch`| origin/main *(default)*, master, custom branch|
|`git history`| Shows previous activity in json format in current project.|


## Usage

# Type `autopush` in your terminal with your active and remotely `Git` repo in project.

> Note: Current project has remote git repo exits, if not it will show error.

```js
// shows  Branch , SHA , Commit msg
{ Branch: "main", SHA: "p5m73l0", Commit: "Fix bugs" }
```
```js
//  create a githistory.json file where all GITHUB history is shown as json format

autopush -h 
```


<!-- This below block is for NPM -->

<!-- ### Error fix -->

<!-- ```cmd
setx PATH "%PATH%;%APPDATA%\npm"
```
The command `setx PATH "%PATH%;%APPDATA%\npm"` appends the npm global installation directory `(%APPDATA%\npm)` to the `PATH` environment variable on Windows. This allows you to run globally installed npm packages from any command prompt or terminal without needing to specify their full paths. The change is permanent and will affect new terminal sessions. --># autopush
task-weaver 0.2.1
A flexible task scheduling and server management library
Requires Python: >=3.10

# Task Weaver

Task Weaver 是一个强大的分布式任务管理库，专门用于处理GPU和API资源的任务调度和执行。它提供了灵活的任务队列管理、服务器资源分配和任务执行监控功能。

## 特性

- 支持多种任务类型（GPU任务和API任务）
- 智能的服务器资源分配
- 任务优先级管理
- 实时任务状态监控
- 可靠的错误处理和恢复机制
- 支持异步并发执行
- 服务器健康检查和自动重连

## 安装

使用 pip 安装:

```bash
pip install task-weaver
```

## 快速开始

### 基本使用

```python
from task_weaver import (
    task_manager,
    server_manager,
    task_catalog,
    TaskPriority,
    ResourceType
)

# 1. 注册服务器
server_manager.register_server(
    ip="http://192.168.1.100:8000",
    server_name="gpu-1",
    description="GPU Server 1",
    tier=1,
    available_task_types=["image_generation"],
    server_type=ResourceType.GPU
)

# 2. 定义并注册任务处理器
async def process_image(server, task_info, **params):
    # 实现你的任务处理逻辑
    result = await your_processing_logic(params)
    return result

task_catalog.add_task(
    task_type="image_generation",
    executor=process_image,
    required_resources=ResourceType.GPU
)

# 3. 创建并执行任务
async def main():
    task = await task_manager.create_task(
        task_type="image_generation",
        params={
            "prompt": "A beautiful sunset",
            "steps": 30
        },
        priority=TaskPriority.HIGH
    )
    
    # 获取任务状态
    task_info = task_manager.get_task_info(task.task_info.task_id)
```

### 服务器管理

```python
# 添加服务器到运行队列
success, message = server_manager.add_running_server(ip="http://192.168.1.100:8000")

# 从运行队列中移除服务器
success, message = server_manager.remove_running_server(ip="http://192.168.1.100:8000")

# 检查服务器状态
server = server_manager.get_server_by_identifier(ip="http://192.168.1.100:8000")
```

## 高级功能

### 任务优先级

Task Weaver 支持三种任务优先级：

```python
from task_weaver import TaskPriority

# 创建不同优先级的任务
high_priority_task = await task_manager.create_task(
    task_type="image_generation",
    params=params,
    priority=TaskPriority.HIGH
)

medium_priority_task = await task_manager.create_task(
    task_type="image_generation",
    params=params,
    priority=TaskPriority.MEDIUM
)

low_priority_task = await task_manager.create_task(
    task_type="image_generation",
    params=params,
    priority=TaskPriority.LOW
)
```

### 任务状态监控

```python
from task_weaver import TaskStatus

# 获取任务信息
task_info = task_manager.get_task_info(task_id)

# 检查任务状态
if task_info.status == TaskStatus.FINISH:
    print("任务完成:", task_info.result)
elif task_info.status == TaskStatus.FAIL:
    print("任务失败:", task_info.error)
```

## 配置要求

- Python 3.10 或更高版本
- 异步支持 (asyncio)
- 网络连接（用于服务器通信）

## 许可证

本项目采用 MIT 许可证。详见 [LICENSE](LICENSE) 文件。

## 贡献

欢迎提交问题和拉取请求。对于重大更改，请先开issue讨论您想要更改的内容。

## 作者

- creeponsky (wenhaozuo1@gmail.com)