semvec/pypi-packages huggingface dataset:
causal-drift 0.1.0
A causal feature selection (Causal DRIFT: Causal Dimensionality Reduction via Inference of Feature Treatments) library using residual-based ATE estimation.
Requires Python: >=3.7

﻿# deepCausal

**deepCausal** is a Python library for causal feature ranking and selection based on residual treatment effect estimation.  
It uses double machine learning and residualization techniques to estimate the causal impact (ATE) of each feature on a continuous or categorical outcome.

## 🔍 Key Features

- Supports both **continuous** and **categorical** outcomes
- Uses **residual-on-residual regression** for causal interpretation
- Identifies **confounders** automatically
- Ranks features by **causal strength**, not just correlation

## 🚀 Usage 

from deepCausal import DeepCausal
import pandas as pd
import numpy as np

df = pd.DataFrame({
    'X1': np.random.randn(100),
    'X2': np.random.rand(100),
    'X3': np.random.randn(100),
    'Y': np.random.randn(100)
})

X = df[['X1', 'X2', 'X3']]
y = df['Y']

model = DeepCausal()
model.fit(X, y, outcome_type='continuous')

print(model.get_feature_ate())

📄 License
This project is licensed under the MIT License. 

🧪 Disclaimer
This method is experimental and currently under research evaluation. Feedback and pull requests are welcome!
thefirstpackage 0.1.0
A simple Python package example
Requires Python: >=3.6

# Simple Todo App

A lightweight, easy-to-use todo list application built with Python and Tkinter.

## Features

- Add new tasks
- Mark tasks as complete/incomplete
- Delete individual tasks
- Clear all tasks at once
- Automatic saving of tasks between sessions
- Clean, modern user interface

## Requirements

- Python 3.x
- Tkinter (usually comes pre-installed with Python)

## How to Run

Simply run the Python script:

```
python todo_app.py
```

## Usage

1. **Add a task**: Type your task in the input field and press Enter or click "Add Task"
2. **Mark as complete**: Select a task and click "Mark Complete"
3. **Delete a task**: Select a task and click "Delete Task"
4. **Clear all tasks**: Click "Clear All" (will ask for confirmation)

## Data Storage

Tasks are automatically saved to a file named `todo_tasks.json` in the same directory as the application. This ensures your tasks persist between sessions.