semvec/pypi-packages huggingface dataset:
pyPreprocessing 0.0.2
package preprocessing of datasets, especially from spectroscopy
Requires Python: >=3.6

[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](https://opensource.org/licenses/MIT)
[![build workflow](https://github.com/AlexanderSouthan/pyPreprocessing/actions/workflows/main.yml/badge.svg)](https://github.com/AlexanderSouthan/pyPreprocessing/actions/workflows/main.yml)
[![codecov](https://codecov.io/gh/AlexanderSouthan/pyPreprocessing/branch/master/graph/badge.svg?token=7GN1K2MVJ3)](https://codecov.io/gh/AlexanderSouthan/pyPreprocessing)

# pyPreprocessing
## General information
For preprocessing of datasets like Raman spectra, infrared spectra, UV/Vis
spectra, but also HPLC data and many other types of data, currently via
baseline correction, smoothing, filtering, transformation, normalization and
derivative. It relies on numpy, pandas, scipy, tqdm and scikit-learn, but also
on https://github.com/AlexanderSouthan/pyDataFitting for the introduction of
equality constraints into the polynomial baseline estimation methods, and
https://github.com/AlexanderSouthan/little_helpers.

## Documentation
Please visit:
https://alexandersouthan.github.io/pyPreprocessing/
tesla-ce-provider 0.0.9
TeSLA Python SDK for providers
Requires Python: >=3.6

[![PyPi Version](https://img.shields.io/pypi/v/tesla-ce-provider.svg)](https://pypi.python.org/pypi/tesla-ce-provider/)
[![codecov](https://codecov.io/gh/tesla-ce/python-provider-sdk/branch/main/graph/badge.svg?token=PJJQMW981P)](https://codecov.io/gh/tesla-ce/python-provider-sdk)
[![AGPL License](https://img.shields.io/badge/license-AGPL-blue.svg)](http://www.gnu.org/licenses/agpl-3.0)  
[![Quality gate](https://sonar.sunai.uoc.edu/api/project_badges/quality_gate?project=tesla-ce_python-provider-sdk)](https://sonar.sunai.uoc.edu/dashboard?id=tesla-ce_python-provider-sdk)
# TeSLA CE Providers Python SDK

| :warning: This repository is **under construction**. Final release of TeSLA Community Edition source code is expected by the **end of 2021** |
| --- |

## Description
Description: A description of your project follows. A good description is clear, short, and to the point. Describe the importance of your project, and what it does.

## Installation
Installation: Installation is the next section in an effective README. Tell other users how to install your project locally. Optionally, include a gif to make the process even more clear for other people.

## Usage
Usage: The next section is usage, in which you instruct other people on how to use your project after they’ve installed it. This would also be a good place to include screenshots of your project in action.

## Contributing
Contributing: Larger projects often have sections on contributing to their project, in which contribution instructions are outlined. Sometimes, this is a separate file. If you have specific contribution preferences, explain them so that other developers know how to best contribute to your work. To learn more about how to help others contribute, check out the guide for setting guidelines for repository contributors.

## Credits
Credits: Include a section for credits in order to highlight and link to the authors of your project.

## License
This project is licensed under [AGPL v3 licence](http://www.gnu.org/licenses/agpl-3.0).
tesla-ce-client 0.0.4
TeSLA CE Client for Python
Requires Python: >=3.6

[![PyPi Version](https://img.shields.io/pypi/v/tesla-ce-client.svg)](https://pypi.python.org/pypi/tesla-ce-client/)
[![codecov](https://codecov.io/gh/tesla-ce/python-client/branch/main/graph/badge.svg?token=PJJQMW981P)](https://codecov.io/gh/tesla-ce/python-client)
[![AGPL License](https://img.shields.io/badge/license-AGPL-blue.svg)](http://www.gnu.org/licenses/agpl-3.0)  
[![Quality gate](https://sonar.sunai.uoc.edu/api/project_badges/quality_gate?project=tesla-ce_python-client)](https://sonar.sunai.uoc.edu/dashboard?id=tesla-ce_python-client)
# TeSLA CE Python Client

| :warning: This repository is **under construction**. Final release of TeSLA Community Edition source code is expected by the **end of 2021** |
| --- |

## Description
Description: A description of your project follows. A good description is clear, short, and to the point. Describe the importance of your project, and what it does.

## Installation
Installation: Installation is the next section in an effective README. Tell other users how to install your project locally. Optionally, include a gif to make the process even more clear for other people.

## Usage
Usage: The next section is usage, in which you instruct other people on how to use your project after they’ve installed it. This would also be a good place to include screenshots of your project in action.

## Contributing
Contributing: Larger projects often have sections on contributing to their project, in which contribution instructions are outlined. Sometimes, this is a separate file. If you have specific contribution preferences, explain them so that other developers know how to best contribute to your work. To learn more about how to help others contribute, check out the guide for setting guidelines for repository contributors.

## Credits
Credits: Include a section for credits in order to highlight and link to the authors of your project.

## License
This project is licensed under [AGPL v3 licence](http://www.gnu.org/licenses/agpl-3.0).
genPwd 1.3.0
This is a sample Description

# Advance_Password_Generator
It will generate random passwords of maximum length 12, avoiding names present in specified files.

# Installation
1-  Install package

`pip install passwgeneration`


2- For updated version
 
`pip install --upgrade passwgeneration`         


3-Import package

`import passwgeneration as p`

4- Generate password

`p.generate_password()`