resnap 0.0.1

A Python library that captures and replays function results to save time, boost performance.

resnap

Smart function output snapshots and caching for Python
resnap snapshots and reuses function outputs based on their inputs, saving time with smart caching and metadata tracking.

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🚀 Features

• Snapshot and cache function/method outputs on disk
• Avoid re-executing code when inputs haven’t changed
• Supports multiple formats:
  • For pd.DataFrame objects: parquet (default) and csv
  • For other objects: pkl (default), json, and txt.
    (Note that for the "json" format, the object type must be compatible with the json.dump method.)
• Stores metadata automatically
• Add custom metadata
• Minimal setup, flexible usage

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📦 Installation

pip install resnap

🧪 Quick Example

from resnap import snap

@snap()
def expensive_computation(x, y):
    print("Running the actual computation...")
    return x * y + 42

result = expensive_computation(10, 2)

Second call with same arguments:

# Output is retrieved from cache — no print, no computation
result = expensive_computation(10, 2)

📁 Output Structure

Each snapshot includes:

• A result file (in the format of your choice)
• A metadata file (e.g., timestamp, arguments, execution time, etc.)

📚 Documentation

(Coming soon)

🛡️ License

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

🤝 Contributing

Contributions, issues and feature requests are welcome! Feel free to open a PR or start a discussion.

⭐️ Show your support If you find this project useful, give it a ⭐️ on GitHub!