semvec/pypi-packages huggingface dataset:
load-MongoDB 0.0.1
A python package for connecting with mongodb database.
License: MIT
Requires Python: >=3.7

# requirements_dev.txt we use for the testing
It makes it easier to install and manage dependencies for development and testing, separate from the dependencies required for production.

# difference between requirements_dev.txt and requirements.txt

requirements.txt is used to specify the dependencies required to run the production code of a Python project, while requirements_dev.txt is used to specify the dependencies required for development and testing purposes.

# tox.ini
We use if for the testing in the python package testing against different version of the python 

## how tox works tox enviornment creation
1. Install depedencies and packages 
2. Run commands
3. Its a combination of the (virtualenvwrapper and makefile)
4. It creates a .tox


# pyproject.toml
it is being used for configuration the python project it is a alternative of the setup.cfg file. its containts configuration related to the build system
such as the build tool used package name version author license and dependencies

# setup.cfg
In summary, setup.cfg is used by setuptools to configure the packaging and installation of a Python projec

# Testing python application
*types of testing*
1. Automated testing 
2. Manual testing

*Mode of testing*
1. Unit testing
2. Integration tests

*Testing frameworks*

1. pytest
2. unittest
3. robotframework
4. selenium
5. behave
6. doctest

# check with the code style formatting and syntax(coding standard)

1. pylint
2. flake8(it is best because it containt 3 library pylint pycodestyle mccabe)
3. pycodestyle
mngdataclean 0.4.2
Text preprocessing package
License: MIT
Keywords: text,preprocessing

# Preprocess YourText

Preprocess YourText is a Python package for text preprocessing tasks, designed to simplify and streamline the process of cleaning and preparing text data for natural language processing (NLP) tasks.

## Features

- **HTML Tag Removal**: Easily remove HTML tags from text data.
- **URL Removal**: Remove URLs from text data.
- **Email Removal**: Remove email addresses from text data.
- **Special Character Removal**: Remove special characters from text data.
- **Accent Removal**: Remove accents from characters in text data.
- **Contractions Expansion**: Expand contractions in text data (e.g., "don't" to "do not").
- **Lemmatization**: Lemmatize words in text data to their base form.
- **Spelling Correction**: Correct spelling mistakes in text data.

## License

This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.

## Installation

You can install the package via pip:

```bash
pip install mngdataclean

## Usage
import mngdataclean as mdc

# Example usage:
text = "This is an example text with HTML tags <b>and URLs</b>."
clean_text = mdc.get_clean(text)
print(clean_text)

#output is 
This is an example text with HTML tags and URLs.