Read and write NumPy binary files (.npy and .npz) in Dart.

Usage

Load an ndarray from an .npy file:

final ndarray = await NdArray.load('example.npy');

Create an ndarray and save it as an .npy file:

final ndarray = NdArray.fromList([1.0, 2.0, 3.0]);
await ndarray.save('example_save.npy');

Conveniently save an n-dimensional List to an .npy file:

await save('example_save.npy', [[1, 2, 3], [4, 5, 6]]);

Read (compressed) .npz files:

final npzFile = await NpzFile.load('example.npz');
final arr_0 = npzFile.take('arr_0.npy');
final arr_1 = npzFile.take('arr_1.npy');

Write (compressed) .npz files:

final array1 = NdArray.fromList([1.0, 2.0, 3.0]);
final array2 = NdArray.fromList([[true, false, true]]);

final npzFile = NpzFile();

npzFile.add(array1);
npzFile.add(array2);

await npzFile.save('example_save.npz');

Features

Load and save n-dimensional arrays from and to the following file formats:

✅ .npy
✅ .npz (compressed and uncompressed)

Supported data types:

✅ float64, float32
✅ int64, int32, int16, int8
✅ uint64, uint32, uint16, uint8
✅ bool

Supported memory representations:

✅ Little and big endian
✅ C and Fortran order

Tests

dart test will run integration tests, too, so make sure to have python and numpy installed and python available in your system's PATH.

Contribute

• Feel free to create an issue in case you found a bug, have any questions or want to propose new features.
• Please check open issues before creating a new one.
• Make sure to satisfy formatter, analyzer and tests when opening a pull request.

Further Reading

More information on the .npy format can be found here.

License

You can use, redistribute and/or modify the code under the terms of the MIT License.