kaggleease 1.3.10

The fastest, notebook-first way to load Kaggle datasets into pandas with one line.

KaggleEase 🚀

The Universal Kaggle Gateway for Data Scientists

KaggleEase is a minimalist, high-performance Python library designed to bridge the gap between Kaggle's vast data ecosystem and your local or Colab development environment. It replaces the heavy official Kaggle package with a smart, self-healing REST client that "just works."

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📘 The Masterclass Notebook

Before you dive into the code, check out our KaggleEase_Masterclass.ipynb located in the root directory.

It is the definitive guide for everything from authentication to advanced universal format loading.

[!TIP] Open the Masterclass Notebook to see every feature in action with zero-boilerplate code.

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🌟 Top Features

Feature	Description
🚀 Universal Load	Handles CSV, Parquet, JSON, Excel, and SQLite automatically.
🏆 Native Competitions	Official competition slugs (like titanic) work out of the box.
🛡️ No-Crash Fallback	Returns local path strings for non-tabular data (Images/Models).
🧠 Deep Intelligence	Fuzzy handle matching, implicit resolution, and self-healing APIs.
✨ IPython Magics	Use %kaggle_load for zero-boilerplate loading in notebooks.

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⚡ Quick Start

1. Installation

!pip install kaggleease --upgrade

2. Authentication (Foolproof)

You can set environment variables (safest) or use kaggle.json.

import os
os.environ['KAGGLE_USERNAME'] = "your_username"
os.environ['KAGGLE_KEY'] = "your_api_key"

3. Load Anything

from kaggleease import load

# Loaded as a Pandas DataFrame automatically
df = load("titanic") 

# Images? Returns the local path string
path = load("resnet50")

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🛠️ Advanced Usage

Universal Formats

# Load JSON
df = load("rtatman/iris-dataset-json-version")

# Load SQLite (Auto-detects the first table!)
df = load("world-bank/world-development-indicators")

Deep-Scan Intelligence

If a dataset has an obscured API (like heptapod/titanic), KaggleEase bypassed the error, downloads the data, and scans every subdirectory to find your CSV for you.

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🤝 Contributing & Support

Built by Data Scientists, for Data Scientists.

• GitHub: Dinesh-raya/kaagleease
• PyPI: kaggleease

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KaggleEase v1.3.9 - The "Universal Resilience" Release.