semvec/pypi-packages huggingface dataset:
multiprocess-logger 0.5
一个安全可靠高效的进程间日志处理器  A safe, reliable and efficient inter process log processor 新增压缩和压缩等级参数 add gzip fix bugs
Requires Python: >=3.5

###                                                                        多进程日志切换处理器

- 一个安全可靠高效的进程间日志处理器  A safe, reliable and efficient inter process log processor fix bugs 修复上一版的bug

- speed about 7100 lines/s 0.8M/s (10 processes) 7100行/s 0.8M/s 测试环境 虚拟机(virtual machine) 

- CentOS7 64 

- python3.7 

- 机械硬盘 hard disk

- 添加测试用例

- 新增参数 need_zip 是否需要日志压缩 布尔值 (需要以命名关键字参数传入)

- 新增参数 compresslevel 日志压缩的gzip等级 默认为9 (需要以命名关键字参数传入)

- v 0.5 修复上一版(0.4)的bug

- ```
  import logging
  
  from multiprocessing import Process
  from logging import Formatter
  
  from multiprocess_logger import MultiprocessingHandler
  
  handler = MultiprocessingHandler(filename='./ppp.log',
                                   maxBytes=1024 * 1024, backupCount=10, need_zip=True, compresslevel=9)
  fmt = Formatter(fmt='%(asctime)s - %(process)d - %(name)s - %(filename)s[line:%(lineno)d] - %(levelname)s: %(message)s')
  handler.setFormatter(fmt=fmt)
  logger = logging.getLogger('SHIT')
  logger.addHandler(handler)
  logger.setLevel(logging.INFO)
  
  logging.basicConfig(level=logging.ERROR,
                      format='%(asctime)s - %(process)d - %(name)s - %(filename)s[line:%(lineno)d] - %(levelname)s: %(message)s')
  
  
  def write_log():
      while True:
          logger.info('Hello World!------------Hello World!')
  
  
  if __name__ == '__main__':
      # write_log()
      p_list = []
      for i in range(6):
          p_list.append(Process(target=write_log))
  
      for i in p_list:
          i.start()
  
  
  ```
mesl 1.0
A Library designed to create external minecraft scripts.
Requires Python: >=3.8

This library is designed to create External minecraft scripts. Hence the name MESL (Minecraft External Script Library). It is NOT a library for creating plugins or forge modifications, clients or datapacks. The usage of this library may be against the rules of some Minecraft Servers. Use it at your own risk.

You can check the documentation and the Library's GitHub at:

https://github.com/MrKelpy/MESL

I hope you enjoy it! Any bug reports are highly appreciated.
simpleTorch 0.0.3
This package is built on pytorch to avoid some standard steps
Requires Python: >=3.6

# simpleTorch
This repo aims to train neural networks with pytorch simple. The data are normalized insede the class. The validation is performed automatically. The output model gets the unscaled data and returns the output unscaled (The scaling is performed inside). This way the user do not interact the scaling,; however the user can select to not use the default scaling and scale the data before the training

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install foobar.

```bash
pip install simpleTorch
```

## Usage
A more detailed example in example_of_usage.ipynb
```python
# X array with inputs in np
# F labels in np
# model is the neural net written in pytorch
import simpleTorch.train_ann
train_ann(model, X, F,plot=True)

```

## Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

## License
[MIT](https://choosealicense.com/licenses/mit/)