semvec/pypi-packages huggingface dataset:
sip-python 0.0.2
Python bindings for the SIP solver.
Requires Python: >=3.10

# sip_python
[![pip](https://github.com/joaospinto/sip_python/actions/workflows/pip.yml/badge.svg)](https://github.com/joaospinto/sip_python/actions?query=workflow%3Apip)
[![wheels](https://github.com/joaospinto/sip_python/actions/workflows/wheels.yml/badge.svg)](https://github.com/joaospinto/sip_python/actions?query=workflow%3Awheels)

Python bindings for the [SIP](https://github.com/joaospinto/sip) solver.
quickstart-vdk 0.2.1810444937
Versatile Data Kit SDK packaging containing common plugins to get started quickly using it.

# Quickstart-VDK

<a href="https://pypistats.org/packages/quickstart-vdk" alt="Monthly Downloads">
        <img src="https://img.shields.io/pypi/dm/quickstart-vdk.svg" alt="monthly download count for quickstart-vdk"></a>

This is the first VDK packaging that users would install to play around with.

It packages:

* Plugin for a local database to get started quickly
* Plugin for job management (vdk-control-cli)
* Plugin for local Control Service installation (vdk-server)

See also [Versatile Data Kit Getting Started](https://github.com/vmware/versatile-data-kit/wiki/Getting-Started).
ntorch 1.0.0
A simple PyTorch framework for quick neural network prototyping
Requires Python: >=3.8


# 🧠 ntorch

`ntorch` 是一个轻量级的 PyTorch 框架，旨在帮助开发者快速构建神经网络原型。它支持多层感知机（MLP）、卷积神经网络（CNN）、强化学习（DQN）和生成对抗网络（GAN），并提供自动模型构建、训练流程封装以及可视化工具。

---

## 📦 安装

确保你已安装 Python 3.8 或更高版本，并安装依赖：

```bash
pip install torch torchvision matplotlib gym
```

然后克隆仓库并本地安装：

```bash
git clone https://github.com/safe049/ntorch.git
cd ntorch
pip install -e .
```

---

## 🤝 贡献指南

欢迎提交 PR 和 Issue！  

---

## 📄 License

MIT License – See [LICENSE](LICENSE) for details.

---

## 📬 联系作者

GitHub: [@safe049](https://github.com/safe049)  
Email: safe049@163.com

---
jaraco.compat 4.3.1
Modules providing forward compatibility across Python versions
Requires Python: >=3.9

.. image:: https://img.shields.io/pypi/v/jaraco.compat.svg
   :target: https://pypi.org/project/jaraco.compat

.. image:: https://img.shields.io/pypi/pyversions/jaraco.compat.svg

.. image:: https://github.com/jaraco/jaraco.compat/actions/workflows/main.yml/badge.svg
   :target: https://github.com/jaraco/jaraco.compat/actions?query=workflow%3A%22tests%22
   :alt: tests

.. image:: https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json
    :target: https://github.com/astral-sh/ruff
    :alt: Ruff

.. image:: https://readthedocs.org/projects/jaracocompat/badge/?version=latest
   :target: https://jaracocompat.readthedocs.io/en/latest/?badge=latest

.. image:: https://img.shields.io/badge/skeleton-2025-informational
   :target: https://blog.jaraco.com/skeleton

Forward compatibility for Python packages,
allowing future constructs to be borrowed before they are available in
the standard library.

`♫ It's going to be the future soon. It won't always be this way, when the things that make me weak and strange get engineered away. ♫ <https://www.youtube.com/watch?v=l5PEz3kGbp4>`_

Usage
=====

Import functions from the appropriate compat.pyXX module in your python
code. When a package is eventually ready to upgrade beyond pyXX,
easily locate (with a grep) and replace those functions with the
canonical implementations.

Example
=======

Say you want a namedtuple (introduced in Python 2.6) in a project which
supports Python 2.5 and greater::

    from compat.py25 import namedtuple
    MyTuple = namedtuple('MyTuple', 'a b c')
    mt = MyTuple(1,2,3)

With jaraco.compat installed, this code will run on Python 2.5 and
greater. When the project is ready to move to Python 2.6, one can easily
grep for py25 and make the necessary replacements with minimal
impact on the code. In this case::

    from collections import namedtuple
    MyTuple = namedtuple('MyTuple', 'a b c')
    mt = MyTuple(1,2,3)
simple-dh 1.0.0
Simple Animation Maker
Keywords: animation

```shell
pip install simple-dh
```

```py
from dh import *
img=cv2.imread('testimg.png')
mx,my=img.shape[0],img.shape[1]
mx//=2
my//=2
spin(img,30,2,'result.mp4',col=(255,255,255))
enlarge(img,2,'result2.mp4',(my,mx),col=(255,255,255))
enlarge_spin(img,30,2,'result3.mp4',(my,mx),col=(255,255,255))
translate(img,110,250,2,'result4.mp4',col=(255,255,255))
spin(img,30,2,'result.gif',col=(255,255,255))
enlarge(img,2,'result2.gif',(my,mx),col=(255,255,255))
enlarge_spin(img,30,2,'result3.gif',(my,mx),col=(255,255,255))
translate(img,110,250,2,'result4.gif',col=(255,255,255))
```
# simple_dh
 简易动画制作器


需要的库：[opencv-python](https://pypi.org/project/opencv-python)，[imageio](https://pypi.org/project/imageio)

目前支持如下动画，详细简介请看注释：
* 旋转
* 放大
* 放大旋转
* 平移

效果：

[![result.gif](https://i.postimg.cc/qgfSC9JM/result.gif)](https://postimg.cc/0KfcTXKL)

[![result2.gif](https://i.postimg.cc/x1QjwZv2/result2.gif)](https://postimg.cc/TpkXmCN7)

[![result3.gif](https://i.postimg.cc/WbGTw7Qf/result3.gif)](https://postimg.cc/XpYRV9Nw)

[![result4.gif](https://i.postimg.cc/tTnHZd3k/result4.gif)](https://postimg.cc/r0TH7rYR)

Simple Animation Maker

Required libraries: [opencv-python](https://pypi.org/project/opencv-python)，[imageio](https://pypi.org/project/imageio)

Currently, these types of animation are supported. Please refer to the comments for a detailed introduction:
* Spin
* Enlarge
* Enlarge and spin
* Translate

Effect:

[![result.gif](https://i.postimg.cc/qgfSC9JM/result.gif)](https://postimg.cc/0KfcTXKL)

[![result2.gif](https://i.postimg.cc/x1QjwZv2/result2.gif)](https://postimg.cc/TpkXmCN7)

[![result3.gif](https://i.postimg.cc/WbGTw7Qf/result3.gif)](https://postimg.cc/XpYRV9Nw)

[![result4.gif](https://i.postimg.cc/tTnHZd3k/result4.gif)](https://postimg.cc/r0TH7rYR)