cfdb 0.8.4

CF conventions multi-dimensional array storage on top of Booklet

cfdb

CF conventions multi-dimensional array storage on top of Booklet

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Documentation: https://mullenkamp.github.io/cfdb/

Source Code: https://github.com/mullenkamp/cfdb

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cfdb is a pure Python database for managing labeled multi-dimensional arrays following the CF conventions. It is an alternative to netCDF4/xarray, built on Booklet for local file storage and EBooklet for S3 sync. Thread-safe and multiprocessing-safe via locks.

Installation

pip install cfdb

Quick Example

import cfdb
import numpy as np

with cfdb.open_dataset('example.cfdb', flag='n') as ds:
    lat = ds.create.coord.lat(data=np.linspace(-90, 90, 181, dtype='float32'))
    lon = ds.create.coord.lon(data=np.linspace(-180, 180, 361, dtype='float32'))
    temp = ds.create.data_var.generic('temperature', ('latitude', 'longitude'), dtype='float32')
    temp[:] = np.random.rand(181, 361).astype('float32') * 40 - 10

with cfdb.open_dataset('example.cfdb') as ds:
    for slices, data in ds['temperature'].iter_chunks(include_data=True):
        print(slices, data.shape)

Multivariable Rechunking

Efficiently iterate over multiple variables with synchronized chunks:

with cfdb.open_dataset('data.cfdb') as ds:
    # Synchronized iteration over temperature and pressure
    for target_chunk, var_data in ds.iter_chunks({'latitude': 50, 'longitude': 50}):
        temp = var_data['temperature']
        pres = var_data['pressure']
        # Perform calculations on aligned blocks

See the full documentation for user guides, concepts, and API reference.

License

This project is licensed under the terms of the Apache Software License 2.0.