semvec/pypi-packages huggingface dataset:
NextTestRunner 0.0.5
新一代，自动化测试执行器
Requires Python: >=3.7
Keywords: sveltest linux python selenium unittest

[GitHub]() | [Gitee]() 

# NextTestRunner 



> NextTestRunner 新一代测试执行器，可无缝对接unittest及sveltest，强大且丰富的测试报告。


## Features

1、更为详细的测试执行结果输出、逼格逐渐提升。

2、与unittest无间隙对接、提供更为复杂的TestRunner。

3、丰富的测试结果，输出不同模板的HTML格式报告。





一个简单测试的demo：

```python
from fastTest import TestCase,main


class TestDemoTo1(TestCase):
    """简单的测试demo"""

    def setUp(self):
        pass

    def tearDown(self):
        pass


    def test_case_demo(self):

        self.assertEqual("sweet","sweet")


if __name__ == '__main__':
    main(verbosity=1)
```

执行后的结果

```

================================ 用例开始执行 =================================
test_case_demo (__main__.TestDemoTo1)   PASS
******************************** 测试结果汇总 *********************************
     执行结果     
┌────────┬───────┐
│ status │ count │
├────────┼───────┤
│ PASS   │ 1     │
│ FAIL   │ 0     │
│ SKIP   │ 0     │
│ ERROR  │ 0     │
│ COUNT  │ 1     │
└────────┴───────┘
================= 总共运行了 1 条测试用例  总共运行了 0.000s ==================
```

终端的结果:

 	![image](README.assets/143005934-83e7e617-a07a-4b77-8bef-97260931d1c7-16376623560173.png)



参数化实例：

```python



from fast_testing import TestView,main
from fast_testing.core.components.parameterized import char,parameterized


@parameterized()
class TestDemoTo1(TestView):
    """简单的测试demo"""

    def setUp(self):
        pass

    def tearDown(self):
        pass

    @char("sweet","testcase")
    def test_case_demo(self,a):
        self.assertEqual("sweet",a,msg=666)


if __name__ == '__main__':
    main(verbosity=1)
    
```

内置参数化、提供多种可能性选择如：随机数据、自定义参数、数据库读取、文件数据读取等

```
================================ 用例开始执行 =================================
test_case_demo_1 (__main__.TestDemoTo1)   PASS
test_case_demo_2 (__main__.TestDemoTo1)   FAIL
-------------------------------- 铺抓到的异常 ---------------------------------
>>> test_case_demo_2 (__main__.TestDemoTo1)
Traceback (most recent call last):
  File "D:\python39\lib\site-packages\sweet\core\components\parameterized.py", 
line 446, in wrapper
    return func(self,*args, **kwargs)
  File "F:\app\test_case_666.py", line 90, in test_case_demo
    self.assertEqual("sweet",a,msg=666)
AssertionError: 'sweet' != 'testcase'
- sweet
+ testcase
 : 666

******************************** 测试结果汇总 *********************************
     执行结果     
┌────────┬───────┐
│ status │ count │
├────────┼───────┤
│ PASS   │ 1     │
│ FAIL   │ 1     │
│ SKIP   │ 0     │
│ ERROR  │ 0     │
│ COUNT  │ 2     │
└────────┴───────┘
================= 总共运行了 2 条测试用例  总共运行了 0.001s ==================

```








## 文档

有关完整文档，包括安装、教程和 PDF 文档，请参阅 暂无

技术操作文档也会给大家编写完成 请尽请期待





### 如果你在使用 fastTest 库发现bug请联系我 gfl13453001@163.com










​
i3d-jax 0.0.1
I3D in Jax

# I3D-Jax
Jax / Flax port of the original [Kinetics-400 I3D network](https://tfhub.dev/deepmind/i3d-kinetics-400/1) from TF

# Installation
`pip install i3d-jax`

# Usage
For convenience, we provide a wrapper to run inference on input videos
```python
import i3d_jax
import numpy as np

video = np.random.randn(1, 16, 224, 224, 3) # B x T x H x W x C in [-1, 1]
i3d = i3d_jax.I3DWrapper(replicate=False) # set to True to auto-use pmap

# out returns a tuple of:
# 1) logits
# 2) a dictionary mapping endpoint names to features at each endpoint
out = i3d(video)
```

You can separate get the model and variables through:
```python
import i3d_jax

# Load model
i3d_model = i3d_jax.InceptionI3d()

# Load variables (params + batch_stats)
variables = i3d_jax.load_variables(replicate=False)
```
educba-zh 2022.11.28.0
EduCba 中文系列教程
Requires Python: >=3.6

# EduCba 中文系列教程

> 原文：[EduCba](https://www.educba.com/)
> 
> 协议：[CC BY-NC-SA 4.0](http://creativecommons.org/licenses/by-nc-sa/4.0/)
> 
> 以斗争求团结则团结存，以妥协求团结则团结亡。——教员

* [在线阅读](https://educba.apachecn.org)
* [在线阅读（Gitee）](https://apachecn.gitee.io/doc-template/)
* [ApacheCN 学习资源](http://docs.apachecn.org/)

## 贡献指南

本项目需要校对，欢迎大家提交 Pull Request。

> 请您勇敢地去翻译和改进翻译。虽然我们追求卓越，但我们并不要求您做到十全十美，因此请不要担心因为翻译上犯错——在大部分情况下，我们的服务器已经记录所有的翻译，因此您不必担心会因为您的失误遭到无法挽回的破坏。（改编自维基百科）

## 联系方式

### 负责人

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

### 其他

*   在我们的 [apachecn/educba-zh](https://github.com/apachecn/educba-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/educba-zh
docker run -tid -p <port>:80 apachecn0/educba-zh
# 访问 http://localhost:{port} 查看文档
```

### PYPI

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

### NPM

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

## 赞助我们

![](http://data.apachecn.org/img/about/donate.jpg)
i2llserver 1.1.1
Server of LockingLock project
Requires Python: >=3.6

# ESP32S3 LockingLock Server

This repo is the server part of LockingLock project.

[Github Link](https://github.com/i2cy/LockingLock_Python)

# Installation
`pip install i2llserver`

# Setup
`i2llsrv setup`

This command will help you to edit a configuration file and 
add startup scripts on boot in systemd

# Auto-Startup on Linux
By running `i2llsrv setup` command, setup wizard will ask you in the end
of setup sequence for choosing whether should it register a systemd 
service. Choose yes to generate service file and register which requires
root permission or sudo permission.

However, if the setup wizard failed to register startup service, it will generate
a one-script-done shell script at your home directory which named as:

`enable_auto-startup_for_i2ll.sh`

By executing this shell scripts by root or sudo, the automatic startup
service will be registered which named as `i2llserver.service`

Use `service i2llserver start|stop|restart` to control server
SuperPyLib 0.0.9
Package for calculating 2-D integral and finite element numerical solutions for Poisson equation with non-overlapping shapes in the presence of Superconducting materials. Updated Get module with straight forward explicit expression for Electric field.
Requires Python: >=3.8

What is SuperPyLib?

SuperPyLib is a Python package for calculating 2-D integral and finite element numerical solutions for Poisson equation with non-overlapping shapes in the presence of Superconducting materials. Updated Get module with straight forward explicit expression for Electric field.

Dependencies:

Python 3.8+, Numpy 1.23.1, Joblib 1.1.0, Matplotlib 3.5.2, Shapely 1.8.4, Triangle 20220202 and Scipy 1.8.1

Version:

SuperPyLib 0.0.9