The reference guide contains a detailed description of the functions, modules, and objects included in Zarr. The reference describes how the methods work and which parameters can …

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Examples >>> import numpy as np >>> import zarr >>> a = np.arange(10000000, dtype='i4').reshape(10000, 1000) >>> z = zarr.array(a, chunks=(1000, 100)) >>> z.shape …

Zarr supports hierarchical organization of arrays via groups. As with arrays, groups can be stored in memory, on disk, or via other storage systems that support a similar interface.

Zarr is a powerful library for storage of n-dimensional arrays, supporting chunking, compression, and various backends, making it a versatile choice for scientific and large-scale data.

Storage guide # Zarr-Python supports multiple storage backends, including: local file systems, Zip files, remote stores via fsspec (S3, HTTP, etc.), and in-memory stores. In Zarr-Python 3, …

Compressors # A number of different compressors can be used with Zarr. Zarr includes Blosc, Zstandard and Gzip compressors. Additional compressors are available through a separate …

Returning False can be useful for stores which implement their own consolidation mechanism outside of the zarr-python implementation. supports_deletes: bool = False #

Zarr arrays and groups can be pickled, as long as the underlying store object can be pickled. With the exception of the zarr.storage.MemoryStore, any of the storage classes provided in the …

Storage (zarr.storage) ¶ This module contains storage classes for use with Zarr arrays and groups. Note that any object implementing the MutableMapping interface from the collections …