Zarrita
Zarrita is an experimental implementation of Zarr v3 including sharding. This is only a technical proof of concept meant for generating sample datasets. Not recommended for production use.
Setup
import zarrita
import numpy as np
store = zarrita.LocalStore('testoutput') # or zarrita.RemoteStore('s3://bucket/test')
testdata = np.arange(0, 16 * 16, dtype='int32').reshape((16, 16))
Create an array
a = zarrita.Array.create(
store / 'array',
shape=(16, 16),
dtype='int32',
chunk_shape=(2, 8),
codecs=[
zarrita.codecs.bytes_codec(),
zarrita.codecs.blosc_codec(typesize=4),
],
attributes={'question': 'life', 'answer': 42}
)
a[:, :] = testdata
Open an array
a = zarrita.Array.open(store / 'array')
assert np.array_equal(a[:, :], testdata)
Create an array with sharding
a = zarrita.Array.create(
store / 'sharding',
shape=(16, 16),
dtype='int32',
chunk_shape=(16, 16),
chunk_key_encoding=('v2', '.'),
codecs=[
zarrita.codecs.sharding_codec(
chunk_shape=(8, 8),
codecs=[
zarrita.codecs.bytes_codec(),
zarrita.codecs.blosc_codec(typesize=4),
]
),
],
)
a[:, :] = testdata
assert np.array_equal(a[:, :], testdata)
Create a group
g = zarrita.Group.create(store / 'group')
g2 = g.create_group('group2')
a = g2.create_array(
'array',
shape=(16, 16),
dtype='int32',
chunk_shape=(16, 16),
)
a[:, :] = testdata
Open a group
g = zarrita.Group.open(store / 'group')
g2 = g['group2']
a = g['group2']['array']
assert np.array_equal(a[:, :], testdata)
Resize array
a.resize((10, 10))
Update attributes
a.update_attributes({'question': 'life', 'answer': 0})
Zarr v2
a = zarrita.ArrayV2.create(
store / 'array',
shape=(16, 16),
dtype='int32',
chunks=(2, 8),
)
a[:, :] = testdata
a3 = a.convert_to_v3()
assert a3.metadata.shape == a.shape
Async methods
a = await zarrita.Array.create_async(
store / 'array_async',
shape=(16, 16),
dtype='int32',
chunk_shape=(2, 8),
)
await a.async_[:, :].set(testdata)
assert np.array_equal(await a.async_[:, :].get(), testdata)
Credits
This is a largely-rewritten fork of zarrita by @alimanfoo. It implements the Zarr v3 draft specification created by @alimanfoo, @jstriebel, @jbms et al.
Licensed under MIT
1 maintainer
Metadata
1 maintainer
Release files for zarrita 0.2.7
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| zarrita-0.2.7.tar.gz | 24.9 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| zarrita-0.2.7-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 55.5 kB
Release files / zarrita-0.2.7.tar.gz
| Download URL | zarrita-0.2.7.tar.gz |
|---|---|
| Size | 24.9 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
f607d401f6f179e1b95e8cb089301287df2ba92c6a301d5659c645feafa05a4a
|
|
BLAKE2b-256 checksum How to use checksums |
ad5ace27b43d6fc3c6a7520d15f598f32905210cfc7d7f5b42119f5a10e753f1
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/1.8.3 CPython/3.11.9 Darwin/23.5.0
|
Release files / zarrita-0.2.7-py3-none-any.whl
| Download URL | zarrita-0.2.7-py3-none-any.whl |
|---|---|
| Size | 30.6 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
c9b830be3c3b5376dca94d6dc573747d5674148aa0b0b758d1511a43fee22c26
|
|
BLAKE2b-256 checksum How to use checksums |
1437817ee1313ce7fdf8a52e85ccba15873c1ae6ad3761f61702cd90846cb81c
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/1.8.3 CPython/3.11.9 Darwin/23.5.0
|
Security for zarrita 0.2.7
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
