semvec/pypi-packages huggingface dataset:
DatasetHandler-Group2 0.1.0
Dataset handler
Requires Python: >=3.6

# DatasetHandler_Group2 Library

DatasetHandler_Group2 is a Python library designed to simplify data cleaning, preprocessing and visualization created by the PBL group 2 of the third year of the bachelor's degree in Engineering Physics Applied to Industry at the AsFabrik campus of Mondragon Unibertsitatea.

The library created by the group formed by Irati Azpilgain, Mikel Ballesteros, Ander Crespo, Estibaliz Cruz, Lucas Lafuente and Mikel Puerta offers an easy-to-use interface for common data science tasks such as handling missing values, removing outliers and creating graphs.

## Installation

You can install DatasetHandler_Group2 via pip:

```bash
pip install DatasetHandler_Group2
```

## Usage

Here's a basic example of how to use DatasetHandler_Group2:

```python
from DatasetHandler_Group2 import DatasetHandler_Group2

# Initialize with your dataset and start the menu
handler = DatasetHandler_Group2(data="sample.csv")
handler.initiate()
```

## Features

- Load datasets from CSV or Excel files.
- Clean data by dropping or imputing missing values.
- Detect and remove outliers.
- Generate descriptive plots such as histograms, scatter plots, and heatmaps.
- Save the cleaned dataset back to a file.

## Dependencies

The following Python libraries are required:

- pandas
- numpy
- seaborn
- matplotlib
- scikit-learn

You can install them via pip:

```bash
pip install pandas numpy seaborn matplotlib scikit-learn
```
## License

This project is licensed under the MIT License.

## Contact

For questions or issues, please contact mikel.puerta@alumni.mondragon.edu
DataHandler-Group2 0.1.0
Dataset handler
Requires Python: >=3.11.5

# DatasetHandler_Group2 Library

DatasetHandler_Group2 is a Python library designed to simplify data cleaning, preprocessing and visualization created by the PBL group 2 of the third year of the bachelor's degree in Engineering Physics Applied to Industry at the AsFabrik campus of Mondragon Unibertsitatea.
The library created by the group formed by Irati Azpilgain, Mikel Ballesteros, Ander Crespo, Estibaliz Cruz, Lucas Lafuente and Mikel Puerta offers an easy-to-use interface for common data science tasks such as handling missing values, removing outliers and creating graphs.

## Installation

You can install DatasetHandler_Group2 via pip:

```bash
pip install DatasetHandler_Group2
```

## Usage

Here's a basic example of how to use DatasetHandler_Group2:

```python
from DatasetHandler_Group2 import DatasetHandler_Group2

# Initialize with your dataset and start the menu
handler = DatasetHandler_Group2(data="sample.csv")
handler.initiate()
```

## Features

- Load datasets from CSV or Excel files.
- Clean data by dropping or imputing missing values.
- Detect and remove outliers.
- Generate descriptive plots such as histograms, scatter plots, and heatmaps.
- Save the cleaned dataset back to a file.

## Dependencies

The following Python libraries are required:

- pandas
- numpy
- seaborn
- matplotlib
- scikit-learn

You can install them via pip:

```bash
pip install pandas numpy seaborn matplotlib scikit-learn
```
## License

This project is licensed under the MIT License.

## Contact

For questions or issues, please contact mikel.puerta@alumni.mondragon.edu
dtfpy 1.0.12
Dealertower Python Framework for microservices.
Requires Python: >=3.11

# DTFPy (Dealertower Python Framework)

## Overview

**DTFPy** (Dealertower Python Framework) is a lightweight, scalable, and high-performance framework designed to simplify the development and deployment of microservices. Built on top of **FastAPI**, it leverages modern Python libraries and tools to streamline application development while maintaining flexibility and modularity.

---

## Features

- **FastAPI-Based:** Quick and efficient web framework for building APIs.
- **Database Integration:** Seamless integration with PostgreSQL using SQLAlchemy and asyncpg.
- **Task Scheduling:** Robust support for asynchronous tasks and periodic scheduling via Celery and Redis.
- **File Uploads:** Easy handling of multipart data using python-multipart.
- **Security:** JWT and other authentication methods supported through python-jose.
- **Cloud Support:** AWS integration with boto3 for scalable cloud operations.
- **Dependency Management:** Configuration-driven setup using python-dotenv and pydantic-settings.
- **Logging and Monitoring:** Support for reliable logging and external integrations.

---

## Installation

You can install DTFPy using `pip`:

```bash
pip install dtfpy
```
psswd-box-generator 0.1.8
Password generating library specifically built for use in my Psswd Box application.
Requires Python: <3.14,>=3.12

## Donations

- [Buy Me A Coffee](https://www.buymeacoffee.com/KingKairos)
- [GitHub Sponsors](https://github.com/sponsors/melvinquick)

## Purpose

This was a library I wrote for another project of mine called [Psswd Box](https://psswdbox.com/). It will generate passwords of various character types and lengths. By default, just running it as main will produce a password with lowercase letters, uppercase letters, numbers, and symbols, and it will be 20 characters long.
OVKFusion 0.1.0
A Python library for interacting with OVK.to platform
Requires Python: >=3.7

# ⚠️ **Warning: Still in Development!** ⚠️

**OVKFusion** is a work in progress. Features are subject to change, and bugs may exist. Please be aware that some functionality might not be fully stable. Contributions and feedback are appreciated!

---

# OVKFusion

**Developer**: Syirezz Cheese | [@syirezz](https://ovk.to/syirezz)

**License**: MIT License

OVKFusion is a Python library for interacting with the ovk.to platform, offering simple and powerful functionality to access account and authentication features. This library is still in progress, so feel free to contribute and stay tuned for future updates.

## Features

- **Authentication**: Securely authenticate and retrieve tokens.
- **User Info**: Retrieve user profile information.
- **OVK Access**: Interact with OVK services using the OVK class.
- **Other Features**: More to come. [We still need complete 70% of features to be done.]

## Installation

To install the library, run:

```bash
pip install ovkfusion
```

Usage
```python
from ovkfusion import Auth, OVK, Account

# Authenticate and get token
auth = Auth("######", "########", "https://ovk.to").get_token()

# Initialize OVK and Account instances
OpenVK = OVK()
User = Account()

# Get version information
print(OpenVK.version())  # Returns: {'response': 'Altair Preview (bbcb9451-nightly)'}

# Get user profile information
print(User.getProfileInfo())  
# Returns:
# {
#     'response': {
#         'first_name': 'Syirezz',
#         'photo_200': 'https://kaslana.ovk.to/hentai/fa/fa8e3e38c371226b703d7bae313872fedba05d02c1a9e611e77c37d62c02ad3feb9d16e8221a76c7a00b0aeeb52930dab45a040dcf023a2f89e07bedfb5d0eef_cropped/normal.jpeg',
#         'nickname': 'syirezz',
#         'is_service_account': False,
#         'id': 20348,
#         'is_verified': False,
#         'verification_status': 'unverified',
#         'last_name': 'Cheese',
#         'home_town': None,
#         'status': 'Создаю OVKFusion',
#         'bdate': '16.07.2011',
#         'bdate_visibility': 1,
#         'phone': '+420 ** *** 228',
#         'relation': 0,
#         'screen_name': 'syirezz',
#         'sex': 1
#     }
# }
```

Development Status

⚠️ This library is still in progress ⚠️

This project is being actively developed. There might be bugs, incomplete features, and frequent updates. Please report any issues you encounter, and check back for updates!

Contributing

Contributions are welcome! Feel free to fork the repository, submit issues, or create pull requests. Your help is appreciated as we work to improve OVKFusion.

License

This project is licensed under the MIT License. See the LICENSE file for more details.

Thank you for using OVKFusion! We hope you find it useful and easy to integrate with ovk.to.