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.

🚀 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

📦 Installation

To test in local mode

pip install resnap

If you want to use a S3 solution

pip install resnap[boto]

🛠️ Configuration

To use this library, you need to configure it using a pyproject.toml file. Add the following section under [tool.resnap]:

[tool.resnap]
enabled = true                          # Enable or disable the library functionality
save_to = "local"                       # Choose the storage backend (e.g., 'local')
output_base_path = "results"            # Directory where output files will be saved
secrets_file_name = ""                  # Optional: path to a secrets file (leave empty if unused (e.g, 'local'))
enable_remove_old_files = true          # Automatically delete old files based on retention policy
max_history_files_length = 3            # Duration value for file retention, used with max_history_files_time_unit
max_history_files_time_unit = "day"     # Time unit used for history retention (e.g., 'second', 'minute', 'hour', 'day')

🧪 Quick Example

from resnap import resnap

@resnap
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

The documentation is available on ReadTheDocs.

🛡️ 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!