semvec/pypi-packages huggingface dataset:
fakenews-framework 0.1.2
A simple machine-learning framework for detecting fake news using preprocessing, feature extraction, and multiple ML models.
License: MIT
Requires Python: >=3.9

# Fake News Framework

A simple, modular, and reusable **machine-learning framework** for detecting fake news using preprocessing, feature extraction, and multiple ML models.  
Developed by **BaByLabs**.

---

## Features

- Clean and modular **data preprocessing pipeline**
- TF-IDF feature extraction for text classification
- Multiple ML models (Logistic Regression, Random Forest, etc.)
- Easy-to-use `predict.py` script for running predictions on new text
- Well-structured and extendable package layout
- Ready for publishing as a Python library (PyPI-compatible)

---

## Installation (once published to PyPI)

```bash
pip install fakenews-framework

```

---

## Credit to these for our OOP-Final Project:

Fake News Detection 
By: Sameer Patel
Source: https://www.kaggle.com/code/therealsampat/fake-news-detection  

Fake News Classification 
By: Ahmed Hafez
Source: https://www.kaggle.com/code/ahmedtronic/fake-news-classification 

---
amino.dorks.fix 3.9.11.14
Library for Amino. Telegram - https://t.me/aminodorks
License: MIT
Requires Python: >=3.10
Keywords: aminoapps, amino.fix, amino, aminodorks, amino-bot, narvii, api, python, python3, python3.x, misterio060

# amino.dorks.fix

**amino.dorks.fix** — a fixed version of the old [aminofix](https://github.com/Minori101/Amino.fix) library, restored to work properly with the Amino API. It works on **[DorksRestAPI](https://github.com/AminoDorks/DorksRestAPI)**.

📢 Telegram: [@aminodorks](https://t.me/aminodorks)

---

## 📦 Installation

```bash
pip install amino.dorks.fix
```

Or from repository:

```bash
git clone https://github.com/misterio060/amino.dorks.fix
cd amino.dorks.fix
pip install .
```

---

## 🔧 Usage

Example of login and performing a check-in:

```python
import aminodorksfix

client = aminodorksfix.Client('go to @aminodorks_bot to get api key')
client.login(email='<EMAIL>', password='<PASSWORD>')
print('logged in', client.profile.nickname)

sub_client = aminodorksfix.SubClient(comId='comId', profile=client.profile)
sub_client.check_in()
```

---

## 📚 Documentation

Currently, documentation is in progress.
For now, you can use old `aminofix` examples since the API is mostly the same.