semvec/pypi-packages huggingface dataset:
pytest-vscode-pycharm-cls 0.6
A PyTest helper to enable start remote debugger on test start or failure or when pytest.set_trace is used.

A PyTest helper to enable start remote debugger on test start or failure or when pytest.set_trace is used. Works with Visual Studio Code and PyCharm.
pytest /path/to/your/tests --pdbcls=pytest_vscode_pycharm_cls.Pdb --debug-wait-timeout=5000 --trace
pytest /path/to/your/tests --pdbcls=pytest_vscode_pycharm_cls.Pdb --debug-wait-timeout=5000 --pdb
chatGPT-debugger 0.1.3
Debug Python code with ChatGPT3 and get error explanations and corrected code.
Requires Python: >=3.7

# ChatGPT Debugger
This package allows you to debug Python code with the help of **ChatGPT3**, a large language model developed by OpenAI. Instead of just getting an error message when running your code, you will get a more detailed explanation of why the error occurred, how to fix it, and a corrected version of the code. This can save you time and effort in trying to figure out why your code is not working, and give you a better understanding of how to fix it. The package integrates ChatGPT3's advanced language processing capabilities to provide you with accurate and helpful debugging information. Whether you're a beginner or an experienced programmer, the ChatGPT_debugger can help you write better and more efficient code.

## Instructions

1. Install:

```
pip install chatGPT_debugger
```

2. How to Debug Python code with ChatGPT_debugger:

The ChatGPT_debugger package offers an easy way to debug your Python code. To use it, simply add the debug decorator to the function you want to debug. For example:

```python
from chatGPT_debugger.chatGPT_debugger import debug

@debug
def calculate_age(date_of_birth:int) -> int:
    current_year = "2023"
    age = current_year - date_of_birth
    return age
    
calculate_age(2000)
```

By using the debug decorator, instead of encountering an error, you will receive output explaining why the error occurred, how to fix it, and the corrected code, among other things."

3. The Benefits of ChatGPT_debugger

The ChatGPT_debugger package is an extremely useful tool for beginner Python programmers. Debugging code can often be a challenging and time-consuming task, especially for those who are just starting out. With the ChatGPT_debugger, however, debugging is made simple and intuitive. By simply adding the debug decorator to your code, you can receive detailed information about any errors or issues, including explanations, suggestions for fixing the problem, and corrected code. This makes it easier for beginner programmers to identify and resolve problems, allowing them to focus on writing and improving their code. The ChatGPT_debugger is an excellent resource for anyone looking to streamline their debugging process and become more confident in their Python programming skills.
JIT 0.2.7
This is a package for my just in time
Requires Python: >=3

Project description
jit is a toscawidgets2 (tw2) wrapper for thejit.

Live Demo
Peep the live demonstration and screenshots.

Links
You can get the source from` github`, check out the PyPI page, and report or look into bugs.

Description
toscawidgets2 (tw2) aims to be a practical and useful widgets framework that helps people build interactive websites with compelling features, faster and easier. Widgets are re-usable web components that can include a template, server-side code and JavaScripts/CSS resources. The library aims to be: flexible, reliable, documented, performant, and as simple as possible.

The JavaScript InfoVis Toolkit (thejit) is a javascript library that provides web standard based tools to create interactive data visualizations for the Web. It is pretty, interactive, and fast.

This module, jit, provides toscawidgets2 (tw2) widgets that render thejit data visualizations.

Sampling jit in the WidgetBrowser
The best way to scope out jit is to load its widgets in the devtools WidgetBrowser. To see the source code that configures them, check out jit/tw2/jit/samples.py

To give it a try you’ll need git, python, and virtualenvwrapper. Run:

$ git clone git://github.com/NocoldBob/jit.git
$ cd jit
(jit) $ pip install devtools
(jit) $ python setup.py develop
(jit) $ paster browser
…and browse to http://localhost:8000/ to check it out.

### egs:
import JIT
JIT.delayMicrosecond(10) # 延时10us，在windows上最少延时1000us（windows系统限制）
hypergrad 0.0.1
Simple and extensible hypergradient for PyTorch
Requires Python: >=3.10

# [hypergrad](mosko.tokyo/hypergrad) ![pytest](https://github.com/moskomule/hypergrad/workflows/pytest/badge.svg)

Simple and extensible hypergradient for PyTorch

<!-- [![PyPI - Version](https://img.shields.io/pypi/v/hypergrad.svg)](https://pypi.org/project/hypergrad)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/hypergrad.svg)](https://pypi.org/project/hypergrad) -->

## Installation

First, install `torch` and its accompanying `torchvision` appropriately. Then,

```console
pip install hypergrad
```

## Methods

### Implicit hypergradient approximation (via approximated inverse Hessian-vector product)

* conjugate gradient
* [Neumann-series approximation](https://proceedings.mlr.press/v108/lorraine20a.html)
* [Nyström method](to_be_updated)

Implementation of these methods can be found in `hypergrad/approximate_ihvp.py`

## Citation

To cite this repository,

```bibtex
@software{hypergrad,
    author = {Ryuichiro Hataya},
    title = {{hypergrad}},
    url = {https://github.com/moskomule/hypergrad},
    year = {2023}
}
```

`hypergrad` is developed as a part of the following research projects:

```bibtex
@inproceedings{hataya2023nystrom,
    author = {Ryuichiro Hataya and Makoto Yamada},
    title = {{Nystr\"om Method for Accurate and Scalable Implicit Differentiation}},
    booktitle = {AISTATS},
    year = {2023}
}
```
ibooker-witchcraft-zh 2023.2.1.0
布客魔法译文集
Requires Python: >=3.6

# 布客魔法译文集

> 协议：[CC BY-NC-SA 4.0](http://creativecommons.org/licenses/by-nc-sa/4.0/)
> 
> 阶段：机翻（1）
> 
> 偌大的地球，放不下一张灵修的书桌。

* [在线阅读](https://mgc.flygon.net)
* [在线阅读（Gitee）](https://apachecn.gitee.io/doc-template/)
* [ApacheCN 学习资源](http://docs.apachecn.org/)
* [ApacheCN 翻译校对兼职群 713436582](https://jq.qq.com/?_wv=1027&k=VSNtgpjb)

## 贡献指南

为了不断改进翻译质量，我们特此启动了【翻译、校对、笔记整理活动】，开设了多个校对项目。贡献者校对一章之后可以领取千字2\~4元的奖励。进行中的校对活动请见[活动列表](https://home.apachecn.org/#/docs/activity/docs-activity)。更多详情请联系飞龙（Q562826179，V:wizardforcel）。

## 联系方式

### 负责人

* [飞龙](https://github.com/wizardforcel): 562826179

### 其他

*   在我们的 [apachecn/ibooker-witchcraft-zh](https://github.com/apachecn/ibooker-witchcraft-zh) github 上提 issue.
*   发邮件到 Email: `apachecn@163.com`.
*   在我们的 [组织学习交流群](https://www.apachecn.org/#/docs/join) 中联系群主/管理员即可.

## 下载

### Docker

```
docker pull apachecn0/ibooker-witchcraft-zh
docker run -tid -p <port>:80 apachecn0/ibooker-witchcraft-zh
# 访问 http://localhost:{port} 查看文档
```

### PYPI

```
pip install ibooker-witchcraft-zh
ibooker-witchcraft-zh <port>
# 访问 http://localhost:{port} 查看文档
```

### NPM

```
npm install -g ibooker-witchcraft-zh
ibooker-witchcraft-zh <port>
# 访问 http://localhost:{port} 查看文档
```

## 其它协议

霞鹜文楷采用 [SIL 开放字体协议 1.1](https://github.com/lxgw/LxgwWenKai/blob/main/SIL_Open_Font_License_1.1.txt)。

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