semvec/pypi-packages huggingface dataset:
logcontext 0.1.1
A simple logging system for (async) contexts
Requires Python: >=3.7
Keywords: async,logging,context

This module helps to solve the following problem:

You have an async program. It does lots of things in parallel.
You don't really know what's happening. Then you get a deadlock,
or a cancellation whose initial trigger is masked by another error
or an unprotected async call within a `finally:` block.

You now have no idea what's happening, and low-level instrumentation
of your code causes the error to get lost in the noise.

Here's how `logcontext` can help.

First, wrap your main code::

	from logcontext import main_context
	def main():
		with main_context():
			... # whatever your program does
	
Then you wrap each possibly-interesting block, nursery, async context, …
with

	from logcontext import context_of
	...
	async def code_of_interest(arg):
		with context_of("interesting: %s", arg) as ctx:
		    ... # start some subtask

			# display what my subcontexts are doing, if anything
			ctx.log_tree()  


Text and positional arguments will be passed to `logging.log`.

Reporting on the current state of your code is then as easy as::

	from logcontext import log_backtrace, log_tree

	...
	log_tree()  # reports the whole program's context tree
	log_backtrace()  # reports the contexts leading to the current code

Both `context_of` and `log_tree` accept a log level. This way you can
selectively attach higher log levels to possibly-interesting code.
"Uninteresting" subtrees are skipped.

"""

from ._main import main_context, context_of, log_backtrace, log_tree
valou 0.0.1
A small example package
Requires Python: >=3.7

# M1-2022-git

## Introduction
This repository is a fork from the previous repository.
The bugs in the converter have been fixed and now we want to publish our work as a publicly available python package.

## Getting started
You should be working from **your own repository** that is a fork of M1-2022-git-workflow.
In order to run this project, you will have to follow these steps.
1. Clone this project
2. move into the project folder
``` shell
cd M1-2022-git-workflow
```
3. Set up a virtual environment
 * Create the virtual environment
 ```shell
 python -m venv myvenv
 ```
 * Activate venv
 ```shell
 . venv/bin/activate
 ```
4. Install pytest
```shell
pip install -U pytest
```
5. Execute main script
```shell
python main.py
```

## Instructions
### Merge feature branch into dev
Now that the converter has no more bugs, we want to merge our branch feature into the dev branch.
We will do a pull request (on your own repo). On GitHub, go to the "Pull requests tab" and click "New pull request".
Select *base* and *compare*. Remember : we want to merge *decimal-binary-converter* into *dev*. 
Then, *Create the pull request*. Add some description of the work you have done and publish the Pull Request.

**Note** : We could have just merge *decimal-binary-converter* into *dev* from the command line. However, when working on a real project, you probably won't have the rights to do so. Remember : dev is a public branch. So all the work going down there should be carefully reviewed and tested.


### Publish your work
We now have an awesome binary/decimal two ways converter ! It's time to publish it so the rest of the world can enjoy it !
We will publish it on PyPI (Python Package Index) which is a public repository of softwares for Python.
1. First, you have to create an account on [Pypi.org](https://pypi.org/)
2. Then, in your repository, you will find a [.github directory](/.github)
3. Inside this directory, you will find .yml files that defines workflows (using GitHub actions)
4. Open the yml files and take time to understand them. Do not hesitate to ask the teacher about them

#### Hands on !
5. We want to create a workflow that will, on publish, test our code and if tests succeed, then publish our package on PyPI
6. In GitHub, click on the *Actions* tab, then click on *new workflow*
7. Choose among the suggestions the template that best suits your use-case and click *Configure*
8. You may find some useful informations in the [Python documentation](https://packaging.python.org/en/latest/tutorials/packaging-projects/)
9. When creating a release on GitHub, do not forget to create a tag corresponding to that release

#### Pull request
10. Once the workflow is setup and tested (you have published your package using it) you can open a pull request to the [original repository](https://github.com/rgt-yncrea/M1-2022-git-workflow)
Corentin 0.0.1
A small example package
Requires Python: >=3.7

# M1-2022-git

## Introduction
This repository is a fork from the previous repository.
The bugs in the converter have been fixed and now we want to publish our work as a publicly available python package.

## Getting started
You should be working from **your own repository** that is a fork of M1-2022-git-workflow.
In order to run this project, you will have to follow these steps.
1. Clone this project
2. move into the project folder
``` shell
cd M1-2022-git-workflow
```
3. Set up a virtual environment
 * Create the virtual environment
 ```shell
 python -m venv myvenv
 ```
 * Activate venv
 ```shell
 . venv/bin/activate
 ```
4. Install pytest
```shell
pip install -U pytest
```
5. Execute main script
```shell
python main.py
```

## Instructions
### Merge feature branch into dev
Now that the converter has no more bugs, we want to merge our branch feature into the dev branch.
We will do a pull request (on your own repo). On GitHub, go to the "Pull requests tab" and click "New pull request".
Select *base* and *compare*. Remember : we want to merge *decimal-binary-converter* into *dev*. 
Then, *Create the pull request*. Add some description of the work you have done and publish the Pull Request.

**Note** : We could have just merge *decimal-binary-converter* into *dev* from the command line. However, when working on a real project, you probably won't have the rights to do so. Remember : dev is a public branch. So all the work going down there should be carefully reviewed and tested.


### Publish your work
We now have an awesome binary/decimal two ways converter ! It's time to publish it so the rest of the world can enjoy it !
We will publish it on PyPI (Python Package Index) which is a public repository of softwares for Python.
1. First, you have to create an account on [Pypi.org](https://pypi.org/)
2. Then, in your repository, you will find a [.github directory](/.github)
3. Inside this directory, you will find .yml files that defines workflows (using GitHub actions)
4. Open the yml files and take time to understand them. Do not hesitate to ask the teacher about them

#### Hands on !
5. We want to create a workflow that will, on publish, test our code and if tests succeed, then publish our package on PyPI
6. In GitHub, click on the *Actions* tab, then click on *new workflow*
7. Choose among the suggestions the template that best suits your use-case and click *Configure*
8. You may find some useful informations in the [Python documentation](https://packaging.python.org/en/latest/tutorials/packaging-projects/)
9. When creating a release on GitHub, do not forget to create a tag corresponding to that release

#### Pull request
10. Once the workflow is setup and tested (you have published your package using it) you can open a pull request to the [original repository](https://github.com/rgt-yncrea/M1-2022-git-workflow)
hamming-digital-filters 0.1.0
Digital Filters by R.W.Hamming. Implementation.
Requires Python: >=3.7

# hamming-digital-filters
[![](https://img.shields.io/pypi/v/hamming-digital-filters?color=green)](https://pypi.org/project/hamming-digital-filters/)[![license](https://img.shields.io/badge/license-BSD-red.svg)](https://www.freebsd.org/doc/en/articles/bsdl-gpl/article.html)


## Digital filters by R.W.Hamming. Implementation.

See [wiki](https://github.com/vbotka/hamming-digital-filters/wiki). Feel free to [share your feedback and report issues](https://github.com/vbotka/hamming-digital-filters/issues).

[Contributions are welcome](https://github.com/firstcontributions/first-contributions).


## Modules


### gradient

[Differentiation Filters](https://github.com/vbotka/hamming-digital-filters/wiki/Module-gradient.-Differentiation-Filters.)

* [gradient_nr](https://github.com/vbotka/hamming-digital-filters/wiki/Module-gradient.-Differentiation-Filters.#gradientgradient_nr) Nonrecursive Differentiation Filter


### lowpass

[Low-Pass Filters](https://github.com/vbotka/hamming-digital-filters/wiki/Module-lowpass.-Low-Pass-Filters.)

* [lowpass_nr](https://github.com/vbotka/hamming-digital-filters/wiki/Module-lowpass.-Low-Pass-Filters.#lowpasslowpass_nr) Nonrecursive Low-Pass Filter
* [lowpass_mt](https://github.com/vbotka/hamming-digital-filters/wiki/Module-lowpass.-Low-Pass-Filters.#lowpasslowpass_mt) Monotone Low-Pass Filter

## References

* Digital Filters by R.W.Hamming,third edition; Dover publications,
  INC., Mineola, New York; ISBN 0-486-65088-X
example-package-Mailliw83 0.0.1
A small example package
Requires Python: >=3.7

# M1-2022-git

## Introduction
This repository is a fork from the previous repository.
The bugs in the converter have been fixed and now we want to publish our work as a publicly available python package.

## Getting started
You should be working from **your own repository** that is a fork of M1-2022-git-workflow.
In order to run this project, you will have to follow these steps.
1. Clone this project
2. move into the project folder
``` shell
cd M1-2022-git-workflow
```
3. Set up a virtual environment
 * Create the virtual environment
 ```shell
 python -m venv myvenv
 ```
 * Activate venv
 ```shell
 . venv/bin/activate
 ```
4. Install pytest
```shell
pip install -U pytest
```
5. Execute main script
```shell
python main.py
```

## Instructions
### Merge feature branch into dev
Now that the converter has no more bugs, we want to merge our branch feature into the dev branch.
We will do a pull request (on your own repo). On GitHub, go to the "Pull requests tab" and click "New pull request".
Select *base* and *compare*. Remember : we want to merge *decimal-binary-converter* into *dev*. 
Then, *Create the pull request*. Add some description of the work you have done and publish the Pull Request.

**Note** : We could have just merge *decimal-binary-converter* into *dev* from the command line. However, when working on a real project, you probably won't have the rights to do so. Remember : dev is a public branch. So all the work going down there should be carefully reviewed and tested.


### Publish your work
We now have an awesome binary/decimal two ways converter ! It's time to publish it so the rest of the world can enjoy it !
We will publish it on PyPI (Python Package Index) which is a public repository of softwares for Python.
1. First, you have to create an account on [Pypi.org](https://pypi.org/)
2. Then, in your repository, you will find a [.github directory](/.github)
3. Inside this directory, you will find .yml files that defines workflows (using GitHub actions)
4. Open the yml files and take time to understand them. Do not hesitate to ask the teacher about them

#### Hands on !
5. We want to create a workflow that will, on publish, test our code and if tests succeed, then publish our package on PyPI
6. In GitHub, click on the *Actions* tab, then click on *new workflow*
7. Choose among the suggestions the template that best suits your use-case and click *Configure*
8. You may find some useful informations in the [Python documentation](https://packaging.python.org/en/latest/tutorials/packaging-projects/)
9. When creating a release on GitHub, do not forget to create a tag corresponding to that release

#### Pull request
10. Once the workflow is setup and tested (you have published your package using it) you can open a pull request to the [original repository](https://github.com/rgt-yncrea/M1-2022-git-workflow)
zuanshi-shengming-lingshu 2022.9.29.0
钻石生命灵数
Requires Python: >=3.6

# 钻石生命灵数

## 下载

### Docker

```
docker pull apachecn0/zuanshi-shengming-lingshu
docker run -tid -p <port>:80 apachecn0/zuanshi-shengming-lingshu
# 访问 http://localhost:{port} 查看文档
```

### PYPI

```
pip install zuanshi-shengming-lingshu
zuanshi-shengming-lingshu <port>
# 访问 http://localhost:{port} 查看文档
```

### NPM

```
npm install -g zuanshi-shengming-lingshu
zuanshi-shengming-lingshu <port>
# 访问 http://localhost:{port} 查看文档
```
zhengnian-fangliao 2022.9.29.0
正念芳疗
Requires Python: >=3.6

# 正念芳疗

## 下载

### Docker

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

### PYPI

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

### NPM

```
npm install -g zhengnian-fangliao
zhengnian-fangliao <port>
# 访问 http://localhost:{port} 查看文档
```
zhaohuan-tianshi 2022.9.29.0
召唤天使
Requires Python: >=3.6

# 召唤天使

## 下载

### Docker

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

### PYPI

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

### NPM

```
npm install -g zhaohuan-tianshi
zhaohuan-tianshi <port>
# 访问 http://localhost:{port} 查看文档
```
yutianshi-lianjie 2022.9.29.0
与天使连结
Requires Python: >=3.6

# 与天使连结

## 下载

### Docker

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

### PYPI

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

### NPM

```
npm install -g yutianshi-lianjie
yutianshi-lianjie <port>
# 访问 http://localhost:{port} 查看文档
```
yunzhanshu 2022.9.29.0
云占术
Requires Python: >=3.6

# 云占术

## 下载

### Docker

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

### PYPI

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

### NPM

```
npm install -g yunzhanshu
yunzhanshu <port>
# 访问 http://localhost:{port} 查看文档
```
yujian-shenqide-dujiaoshou 2022.9.29.0
遇见神奇的独角兽
Requires Python: >=3.6

# 遇见神奇的独角兽

## 下载

### Docker

```
docker pull apachecn0/yujian-shenqide-dujiaoshou
docker run -tid -p <port>:80 apachecn0/yujian-shenqide-dujiaoshou
# 访问 http://localhost:{port} 查看文档
```

### PYPI

```
pip install yujian-shenqide-dujiaoshou
yujian-shenqide-dujiaoshou <port>
# 访问 http://localhost:{port} 查看文档
```

### NPM

```
npm install -g yujian-shenqide-dujiaoshou
yujian-shenqide-dujiaoshou <port>
# 访问 http://localhost:{port} 查看文档
```
yueliang-mofa 2022.9.29.0
月亮魔法
Requires Python: >=3.6

# 月亮魔法

## 下载

### Docker

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

### PYPI

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

### NPM

```
npm install -g yueliang-mofa
yueliang-mofa <port>
# 访问 http://localhost:{port} 查看文档
```
yongtaluo-xieriji 2022.9.29.0
用塔罗写日记
Requires Python: >=3.6

# 用塔罗写日记

## 下载

### Docker

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

### PYPI

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

### NPM

```
npm install -g yongtaluo-xieriji
yongtaluo-xieriji <port>
# 访问 http://localhost:{port} 查看文档
```
yaocao-yumofa 2022.9.29.0
药草与魔法
Requires Python: >=3.6

# 药草与魔法

## 下载

### Docker

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

### PYPI

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

### NPM

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