semvec/pypi-packages huggingface dataset:
loudify_worker 0.0.post13
Initialisation module of loudify_worker.

# loudify-worker

> Running a GNU Radio flowgraph as a ZMQ worker.

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<br />
<p align="center">
  <a href="https://github.com/martynvdijke/gr-lora_sdr/settings">
    <img src="pictures/worker.png" alt="Logo">
  </a>

  <h3 align="center">Loudify - worker</h3>

  <p align="center">
    Loudify worker, running gnuradio flowgraph as a ZMQ worker.
    <br />
    <a href="https://martynvdijke.github.io/loudify-worker/html/index.html"><strong>Explore the docs »</strong></a>
    <br />
    <br />
    <a href="https://github.com/martynvdijke/loudify-worker/issues">Report a bug</a>
    <a href="https://github.com/martynvdijke/loudify-worker/issues">Request a feature</a>
  </p>
</p>

## Summary
This project is a worker for the ZMQ broker - worker setup for LoRa and part of a larger project, see [broker](https://github.com/martynvdijke/loudify-broker) and [gr-lora_sdr](https://github.com/martynvdijke/gr-lora_sdr).

## Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Make sure to add or update tests as appropriate.

## [Changelog](CHANGELOG.md)
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buptlibrecord 0.0.1
Export BUPT Library Records.
Requires Python: >=3.5
Keywords: bupt library record

# BUPT Library Record Backup

用于导出个人北邮图书馆图书借阅记录。跨平台，但仅支持 Python 3。

需要输入使用学工号和密码登录北邮统一身份认证后的 Cookie中的 `JSESSIONID`，然后程序会自动导出全部的图书借阅记录并保存到文件，将会生成 3 个文件，包含原始数据的 json 格式文件，借阅过的图书列表，借阅日志（包含借阅，续借和还书三种操作）

## 如何获取 JSESSIONID

1. 登录北邮统一身份认证
   如网址 my.bupt.edu.cn
   
2. 按 F12 打开开发者工具

3. 在 FireFox 浏览器点击存储（Store）选项卡，Chrome 或 Edge 浏览器点击应用选项卡，再点击展开 Cookie


4. 查看Cookie中 JSESSIONID 的值

Firefox：
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Edge / Chrome：

![image.png](https://i.loli.net/2021/06/24/AuWrHKERSeyCtX6.png)

## 安装

直接使用 pip 安装

`pip install buptlibrecord`

## 使用

登录 `buptlibrecord JSESSIONID` 


### 在 python 中调用

```python
import buptlibrecord

book_info_list, totalPage, total_count = buptlibrecord.get_all_record_list(JSESSIONID) 

```
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Bapy Package.

# Bash, Ansible and Python Utils.

## Install

## Docker 
```bash
docker pull kalilinux/kali:latest
```

```bash
apt update -y; apt full-upgrade -y; apt install -y kali-linux-everything
sudo python3 -m pip install --upgrade bapy
```

### With pip available

#### No python
```bash
sudo apt update -y; apt install python3.8 python3-pip -y
sudo python3 -m pip install --upgrade bapy

```

#### With sudo in debian/kali or macos in bootstrap if brew not installed
```bash
sudo python3 -m pip install --upgrade bapy
```

#### When brew installed:

```bash
python3 -m pip install --upgrade bapy
```

### Upload & Upgrade

```bash
rebashrc
```

## Update secrets (token, etc.) and ssh keys on source server and other servers

### On the git source code server

Update the repository and:

```bash
rc secrets  # secrets-push.sh
rebash
```

#### On other servers
```bash
rc secrets  #secrets-pull.sh 
rebash
```

## Other PyPi Projects Upload and Upgrade

### On the git source code server

Perform any tests and:

```bash
rc up  # project-upload.sh <path> <major|minor> <j5pu|jose-nferx|pypi>
```

#### On other servers

```bash
upgrade.sh name
```
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movshon-lab-to-nwb 0.1.1
NWB conversion scripts and tutorials.

# movshon-lab-to-nwb

[![PyPI version](https://badge.fury.io/py/movshon-lab-to-nwb.svg)](https://badge.fury.io/py/movshon-lab-to-nwb)

NWB conversion scripts and tutorials. A collaboration with [Movshon Lab](https://www.cns.nyu.edu/labs/movshonlab/).

- Blackrock processing through SpikeInterface
- Blackrock conversion to NWB
- OpenEphys processing through SpikeInterface
- OpenEphys conversion to NWB
- SpikeGLX processing through SpikeInterface
- SpikeGLX conversion to NWB
- Expo conversion to NWB

# Install
To clone the repository and set up a conda environment, do:
```
$ git clone https://github.com/catalystneuro/movshon-lab-to-nwb
$ conda env create -f movshon-lab-to-nwb/make_env.yml
$ source activate env_movshon
```

Alternatively, to install directly in an existing environment:
```
$ pip install movshon-lab-to-nwb
```


# Spike sorting
SpikeInterface examples for each experiment can be found in [tutorials](https://github.com/catalystneuro/movshon-lab-to-nwb/tree/main/tutorials).

Check SpikeInterface [documentation](https://spikeinterface.readthedocs.io/en/latest/sortersinfo.html) for a list of available spike sorters and how to install them.


# NWB conversion
After activating the correct environment, the conversion function can be used in different forms:

**1. Imported and run from a python script:** <br/>
Detailed and simple examples for each experiment can be found in [tutorials](https://github.com/catalystneuro/movshon-lab-to-nwb/tree/main/tutorials)


**2. Graphical User Interface:** <br/>
To use the GUI, first install [nwb-web-gui](https://github.com/catalystneuro/nwb-web-gui):
```shell
$ pip install nwb-web-gui
```

The GUI can be run from the terminal:
```shell
$ nwbgui-movshon [experiment_name]
```
Current options for experiment names are: `blackrock`, `openephys`, and `spikeglx`. The NWB Web GUI should open in your browser. If it does not open automatically (and no error messages were printed in your terminal), just open your browser and navigate to `localhost:5000`.

The GUI eases the task of editing the metadata of the resulting `nwb` file, it is integrated with the conversion module (conversion on-click) and allows for quick visual exploration the data in the end file with [nwb-jupyter-widgets](https://github.com/NeurodataWithoutBorders/nwb-jupyter-widgets).


**4. Tutorial:** <br/>
At [tutorials](https://github.com/catalystneuro/movshon-lab-to-nwb/tree/main/tutorials) you can also find Jupyter notebooks with the step-by-step process of conversion.
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CryptoAuthToken 1.1.8
A token authentication method.
Keywords: TokenAuthentication,CryptoAuthToken,Authentication,Token

## CryptoAuthToken  
  
* `A way for authenticating using token with cryptographic encryption system.`  
  
<br>  
  
## Installation  
  
* Install Package Using `pip`  
  ```shell script  
   python3 pip install CryptoAuthToken  
   ```  
    
<br>  
  
### How to use:  

* `Note: ` After installing First time if you try to use or import this, it will print out `Initializing CryptoTokenAuth for the first time.We generate random cerdentials to keep this secure.` and exit.
this is the way it works it will only happen for the first time.it creates random cerdentials so you'r Token salt is totally random from others.

* Creating a Token  
    ```python  
    from CryptoAuthToken import CryptoToken  
    CryptoToken = CryptoToken(key='Mysecretkey')  
      
    token = CryptoToken.create()  
    print(token)  
      
    >>gAAAAABg0fTUjXv1D62TrwaQ==.....  
    ```  
  
* Validating Token.
`If the token was created with the same key then it's a valid token.Returns: Boolean`
    ```python  
    from CryptoAuthToken import CryptoToken  
    CryptoToken = CryptoToken(key='Mysecretkey')  
      
    token = 'gAAAAABg0fTUjXv1D62TrwaQ==...'
    is_valid = CryptoToken.authenticate(token=token)
    
    print(is_valid)
	
	>> True
    ```
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Python 翻译 API [当前支持:百度翻译、小牛翻译]
Requires Python: >=3.9,<4.0

# Python 翻译 API

* [百度翻译开放平台](https://fanyi-api.baidu.com/)
* [小牛翻译](https://niutrans.com/)
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XCMS distribution standard library that will be hosted on PyPI
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