semvec/pypi-packages huggingface dataset:
duitku-python 0.2.6
Duitku Python SDK
Requires Python: >=3.5

# Duitku Python API Client Library
[![pypi](https://img.shields.io/pypi/v/duitku-python)](https://pypi.org/project/duitku-python/)
[![Build Status](https://github.com/idoyudha/duitku-python/actions/workflows/python.yml/badge.svg?branch=master)](https://github.com/idoyudha/duitku-python/actions/workflows/python.yml?query=branch%3Amaster)
[![License: MIT](https://img.shields.io/badge/License-MIT-red.svg)](https://opensource.org/licenses/MIT)

Duitku API Library for Python
## Supported Feature
|        Feature         |              Function                |                HTTP Request                   |              Description              |
|------------------------|--------------------------------------|-----------------------------------------------|---------------------------------------|
| Get Payment Method     | duitku.payment.get_methods           | POST /merchant/paymentmethod/getpaymentmethod | Get list of available payment methods |
| Craete New Invoice     | duitku.invoice.create                | POST /merchant/createInvoice                  | Create Transaction via POP API        |
| Create New Transaction | duitku.transaction.create            | POST /merchant/v2/inquiry                     | Create Transaction via V2 API         |
| Get Transaction        | duitku.transaction.get_status        | POST /merchant/transactionStatus              | Get Transaction via V2 API            |

## Requirements
- Python 3.5 or later
- Duitku account, [register here](https://dashboard.duitku.com/Account/Register)
- [API Key](https://docs.duitku.com/en/account/#account-integration--getting-api-key)

## Documentation
- https://docs.duitku.com/

## Installation
Get this library, add to your project

```bash
pip install duitku-python
```

## Example Usage
```python
import requests
import Duitku

from http import HTTPStatus
from datetime import datetime

duitku = Duitku.Duitku()

client = duitku.client
client.merchant_code = "YOUR MERCHANT CODE"
client.api_key = "YOUR API KEY"
client.environment = client.SandboxEnv

create_invoice_req = {
    "paymentAmount": 10001,
    "merchantOrderId": datetime.now().strfti("%Y%m%d%H%M%S"),
    "productDetails": "test invoice",
    "email": "test@duitku.com",
    "callbackUrl": "https://duitku.com/callback",
    "returnUrl": "https://duitku.com"
}
result = self.duitku.invoice.create(create_invoice_req)
print(result)
```

## Support
If you have a feature request or spotted a bug or a techical problem, [create an issue here](https://github.com/idoyudha/duitku-python/issues/new/choose).
For other questions, please contact duitku through their live chat on your dashboard.

## License
MIT license. For more information, see the LICENSE file.
nnops 0.1.0
Neural Network Operators
Requires Python: >=3.8
Keywords: Deep Learning, Neural Network Operators, Artificial Intelligence

### Install
```shell
pip install nnops
```

### Example
```python
import nnops, nnops.tensor

x = nnops.tensor.randn(2, 3)
y = nnops.tensor.randn(3, 4)

x = (x + 2) * 3
y = (y - 4) / 5
z = x @ y # [2, 4]
```

### Sponsor
<table align="center">
    <thead>
        <tr>
            <th colspan="2">公众号</th>
        </tr>
    </thead>
    <tbody align="center" valign="center">
        <tr>
            <td colspan="2"><img src="https://jiauzhang.github.io/ghstatic/images/ofa_m.png" style="height: 196px" alt="AliPay.png"></td>
        </tr>
    </tbody>
    <thead>
        <tr>
            <th>AliPay</th>
            <th>WeChatPay</th>
        </tr>
    </thead>
    <tbody align="center" valign="center">
        <tr>
            <td><img src="https://jiauzhang.github.io/AliPay.png" style="width: 196px; height: 196px" alt="AliPay.png"></td>
            <td><img src="https://jiauzhang.github.io/WeChatPay.png" style="width: 196px; height: 196px" alt="WeChatPay.png"></td>
        </tr>
    </tbody>
</table>
pygbagfx 0.0.13
Python wrapper for the GBA graphics tool from https://github.com/pret/pokeemerald.
Requires Python: >=3

# pygbagfx

Python wrapper for the GBA graphics tool from
https://github.com/pret/pokeemerald

This is used in [Archipelago cross-game multiworld randomizer](https://github.com/ArchipelagoMW/Archipelago).

## Import from package

* Install from PyPI via `pip install pygbagfx`
* Or download a [release](https://github.com/RhenaudTheLukark/pygbagfx/releases) and `pip install` it
* Or clone, build and install a wheel from source using
  ```
  git clone https://github.com/RhenaudTheLukark/pygbagfx --recurse-submodules
  python3 -m build --wheel
  pip install dist/*.whl
  ```

## Import from source

* Clone with submodules using
  ```
  git clone https://github.com/RhenaudTheLukark/pygbagfx --recurse-submodules
  ```
* Simply import the cloned repo, it will auto-compile or run through cppyy.
  Either a C compiler or [cppyy](https://pypi.org/project/cppyy/) is required.

## API

```python
main(input: Path, output: Path)  # transforms a resource into another
```
dsapi-llmclient 0.1.5
轻量级LLM API客户端库，支持缓存、重试和详细日志记录功能
Requires Python: >=3.6

# LLMClient

轻量级LLM API客户端库，基于Python开发，支持缓存、重试和详细日志记录功能。

作者: Leo <marticle.ios@gmail.com>

[English Version](README_EN.md) | [中文版](README_ZH.md)

## 特性

- **轻量便捷**：简洁的API设计，易于集成和使用
- **环境变量控制**：通过环境变量灵活配置所有功能
- **SQLite缓存**：内置高效的本地缓存机制，减少重复API调用
- **自动重试**：内置智能重试机制，应对网络波动和临时错误
- **详细日志**：可配置的详细日志记录，支持调试模式

## 安装

```bash
# 克隆仓库
git clone https://github.com/yourusername/llmclient.git
cd llmclient

# 安装依赖
pip install -r requirements.txt

# 安装库（开发模式）
pip install -e .
```

## 环境变量配置

创建`.env`文件并配置以下环境变量：

```
# API配置
LLM_API_BASE=https://api.deepseek.com/v1
LLM_API_KEY=your_api_key_here
LLM_MODEL=deepseek-chat
LLM_MAX_TOKENS=8000
LLM_TEMPERATURE=1.0

# 缓存配置
LLM_CACHE_ENABLED=true
LLM_CACHE_PATH=~/.llmclient/cache.db
LLM_CACHE_EXPIRY_DAYS=30

# 调试配置
LLM_DEBUG=false
LLM_DEBUG_DIR=~/.llmclient/logs

# 重试配置
LLM_RETRY_ATTEMPTS=3
LLM_RETRY_MIN_WAIT=2
LLM_RETRY_MAX_WAIT=10
```

## 快速开始

### 基本用法

```python
from llmclient import LLMClient

# 创建客户端（使用环境变量配置）
client = LLMClient()

# 发送简单请求
response = client.completion("请用一句话介绍人工智能。")
print(response)
```

### 自定义配置

```python
from llmclient import LLMClient, LLMConfig

# 创建自定义配置
config = LLMConfig(
    api_base="https://api.deepseek.com/v1",
    api_key="your_api_key_here",
    model="deepseek-chat",
    max_tokens=2000,
    temperature=0.7,
    cache_enabled=True,
    debug_enabled=True
)

# 使用自定义配置创建客户端
client = LLMClient(config)

# 发送请求
response = client.completion("请列举三种常见的机器学习算法。")
print(response)
```

### 多轮对话

```python
from llmclient import LLMClient

client = LLMClient()

# 构建对话历史
messages = [
    {"role": "user", "content": "你好，我想了解一下深度学习。"},
    {"role": "assistant", "content": "你好！深度学习是机器学习的一个分支，它使用多层神经网络来模拟人脑的学习过程。有什么具体方面你想了解的吗？"},
    {"role": "user", "content": "请介绍一下CNN和RNN的区别。"}
]

response = client.chat_completion(messages)
print(response)
```

### 使用工具函数

```python
from llmclient import LLMClient
from llmclient.utils import format_prompt, extract_json, chunk_text

client = LLMClient()

# 使用模板
template = """请为一家{industry}公司起一个名字，要求：
1. 名字要简洁易记
2. 能反映公司的行业特点
3. 有创意和现代感"""

prompt = format_prompt(template, industry="人工智能")
response = client.completion(prompt)
print(response)

# 分割长文本
long_text = "这是一段非常长的文本..." * 100
chunks = chunk_text(long_text, chunk_size=4000, overlap=200)
for chunk in chunks:
    response = client.completion(chunk)
    print(response)
```

## 高级功能

### 缓存管理

```python
from llmclient import LLMClient

client = LLMClient()

# 清理过期缓存
deleted_count = client.clear_cache()
print(f"已清理 {deleted_count} 条过期缓存")

# 清理指定天数前的缓存
deleted_count = client.clear_cache(days=7)
print(f"已清理 {deleted_count} 条7天前的缓存")
```

### 调试模式

```python
from llmclient import LLMClient

client = LLMClient()

# 启用调试模式
client.set_debug(True)

# 发送请求（将记录详细日志）
response = client.completion("这是一个测试请求")

# 禁用调试模式
client.set_debug(False)
```

## 示例脚本

查看 `example.py` 获取更多使用示例。

```bash
python example.py
```

## 依赖

- requests: HTTP请求
- tenacity: 重试机制
- python-dotenv: 环境变量加载
- sqlite3: 内置缓存数据库

## 许可证

MIT
crossbill 0.1.7
A library for building Finagle-style asynchronous clients and servers
Requires Python: >=3.11
Keywords: crossbill, finagle, service, filter, asynchronous, future, request, response

# Crossbill

[![PyPI version](https://img.shields.io/pypi/v/crossbill.svg)](https://pypi.org/project/crossbill/)

## Description

Crossbill is a Python library focused on building Finagle-style `Service`-based
asynchronous clients and servers. It is very much a work in progress, and as
such, does not follow semantic versioning, nor should the APIs be considered
stable.

## Getting Started

Crossbill is published to PyPI. Here's a walkthrough of how to include it as a
dependency in your project via `uv`.

### Create a New Project

```shell
$ uv init crossbill-demo
$ cd crossbill-demo
```

### Add Crossbill as a Dependency

```shell
$ uv add crossbill
```

### Code the Example

By default, `uv` will generate a `hello.py` file. Replace its contents with the
following code:

```python
import asyncio
from crossbill.core import Service
from crossbill.string import (
    StringClient,
    StringRequest,
    StringResponse,
    StringServer,
)
from crossbill.transport import Address


class EchoService(Service[StringRequest, StringResponse]):
    async def __call__(self, request: StringRequest) -> StringResponse:
        return StringResponse(request.value)


async def main() -> None:
    address = Address("localhost", 12345)
    server = StringServer()
    await server.serve(address, EchoService())

    message = "Hello from crossbill-demo!"
    client = StringClient()
    await client.connect(address)
    response = await client(StringRequest(message))
    print(response.value)

    await client.close()
    await server.close()


if __name__ == "__main__":
    asyncio.run(main())
```

### Run the Example

```shell
$ uv run hello.py
Hello from crossbill-demo!
```

## Development

The `crossbill` project uses `uv`, "[a]n extremely fast Python package and
project manager, written in Rust." If you don't have it installed, follow
the [installation guide](https://docs.astral.sh/uv/getting-started/installation/)
in order to do so.

### Dependency Installation

With `uv` installed, run the following from the command line to ensure that all
dependencies are properly installed.

```shell
$ uv sync
```
### Typing

This project uses type hints extensively, and uses both `pyright` and `mypy` to see
issues related to them.

To see the existing issues, run the following from the command line.

```shell
$ uv run pyright .
$ uv run mypy .
```

### Testing

This project uses `pytest` along with `asyncio` in order to run asynchronous
tests. A predominant number of tests within this library will fit that criteria
due to the nature of the domain space. 

To run the existing unit tests, run the following from the command line.

```shell
$ uv run pytest
```

#### Coverage

This project uses `coverage` and `pytest-cov` for measuring code coverage. To
generate the report when running tests, run the following from the command line.

```shell
$ uv run pytest --cov
```
YcthProgressbar 1.0.0
一个具有高性能、主题切换和动画效果的PySide6自定义进度条组件
Requires Python: >=3.6
Keywords: pyside6, qt, progressbar, ui, widget, theme, animated, gradient


# YcthProgressbar

一个为PySide6设计的高度可定制的进度条组件，具有以下特性：

- 多种预定义主题（默认、暗色、亮色、蓝色）
- 自定义样式支持
- 平滑动画效果
- 渐变色填充选项
- 高性能渲染
- 易于集成和使用

适用于需要美观、现代化UI的Python Qt应用程序。