semvec/pypi-packages huggingface dataset:
password-lib 0.0.3
`password-lib` is a Python library for generating secure passwords, configuring strength requirements, and checking password strength. With customizable length and requirements, it enhances application security. Use password-lib to easily generate strong passwords and ensure password security.
Requires Python: >=3.9

# Overview

`password-lib` is a Python library for generating secure passwords, configuring strength requirements, and checking password strength. With customizable length and requirements, it enhances application security. Use password-lib to easily generate strong passwords and ensure password security.

## Requirements

- python 3.9 or higher

## Installation

```sh
py -m pip install password-lib
```

## Usage

```sh
> from password_lib.utils import PasswordUtil

> # Create an instance of the PasswordUtil class
> password_util = PasswordUtil()

> # Configure the password strength requirements
> password_util.configure_strength(min_length=10)
> password = password_util.generate_password()
> is_secure = password_util.is_secure(password)
> password
0GpDjb@4M.RZRQY_HHCq7CzJI
> is_secure
True

```

## Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are **greatly appreciated**.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement".
Don't forget to give the project a star! Thanks again!

1. Fork the Project
2. Create your Feature Branch (`git checkout -b feature/AmazingFeature`)
3. Commit your Changes (`git commit -m 'Add some AmazingFeature'`)
4. Push to the Branch (`git push origin feature/AmazingFeature`)
5. Open a Pull Request

## License

Distributed under the MIT License. See `LICENSE` for more information.

## Links

https://github.com/ardf/password_utils
antgo 0.1.24
machine learning experiment platform

======================
Antgo
======================

.. image:: https://raw.githubusercontent.com/jianzfb/antgo/master/antgo/resource/static/card.png
    :alt: Antgo

Target
----------------------
Antgo is a machine learning experiment manage platform, which has been integrated deeply with MLTalker.
Antgo provides a one-stop model development,  deployment, analyze, auto-optimize and manage environment.

Installation
----------------------
1. (RECOMMENDED) use docker

    `docker environment <docker/README.md>`__.

2. install from pip

    pip install antgo


3. install from source

    1. git clone https://github.com/jianzfb/antgo.git
    2. cd antgo
    3. pip install -r requirements.txt
    4. python setup.py build_ext install


Register
-----------------------
Register in `MLTalker <http://www.mltalker.com/>`__.

.. image:: https://raw.githubusercontent.com/jianzfb/antgo/master/antgo/resource/static/register.png
    :alt: Antgo and MLTalker

All user experiment records would be managed by MLTalker in user's personal page.


Quick Example
-----------------------

1.step create mvp code(cifar10 classification task)

    antgo create mvp --name=cifar10

2.step start training process

    python3 ./cifar10/main.py --exp=cifar10 --gpu-id=0 --process=train

3.step check training log

    in ./output/cifar10/output/checkpoint

4.step export onnx model

    python3 ./cifar10/main.py --exp=cifar10 --checkpoint=./output/cifar10/output/checkpoint/epoch_1500.pth --process=export