Skip to main content

Read and write large, multi-dimensional arrays

Project description

TensorStore

Library for reading and writing large multi-dimensional arrays.

License PyPI Build Docs

Documentation and installation instructions are at https://google.github.io/tensorstore.

This is not an officially supported Google product.

License

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this software except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0.

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

tensorstore-0.1.26.tar.gz (4.9 MB view details)

Uploaded Source

Built Distributions

tensorstore-0.1.26-cp310-cp310-win_amd64.whl (6.1 MB view details)

Uploaded CPython 3.10 Windows x86-64

tensorstore-0.1.26-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.8 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

tensorstore-0.1.26-cp310-cp310-macosx_11_0_arm64.whl (7.0 MB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

tensorstore-0.1.26-cp310-cp310-macosx_10_14_x86_64.whl (8.6 MB view details)

Uploaded CPython 3.10 macOS 10.14+ x86-64

tensorstore-0.1.26-cp39-cp39-win_amd64.whl (6.1 MB view details)

Uploaded CPython 3.9 Windows x86-64

tensorstore-0.1.26-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.8 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

tensorstore-0.1.26-cp39-cp39-macosx_11_0_arm64.whl (7.0 MB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

tensorstore-0.1.26-cp39-cp39-macosx_10_14_x86_64.whl (8.6 MB view details)

Uploaded CPython 3.9 macOS 10.14+ x86-64

tensorstore-0.1.26-cp38-cp38-win_amd64.whl (6.1 MB view details)

Uploaded CPython 3.8 Windows x86-64

tensorstore-0.1.26-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.8 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

tensorstore-0.1.26-cp38-cp38-macosx_11_0_arm64.whl (7.0 MB view details)

Uploaded CPython 3.8 macOS 11.0+ ARM64

tensorstore-0.1.26-cp38-cp38-macosx_10_14_x86_64.whl (8.6 MB view details)

Uploaded CPython 3.8 macOS 10.14+ x86-64

tensorstore-0.1.26-cp37-cp37m-win_amd64.whl (6.1 MB view details)

Uploaded CPython 3.7m Windows x86-64

tensorstore-0.1.26-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.8 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ x86-64

tensorstore-0.1.26-cp37-cp37m-macosx_10_14_x86_64.whl (8.5 MB view details)

Uploaded CPython 3.7m macOS 10.14+ x86-64

File details

Details for the file tensorstore-0.1.26.tar.gz.

File metadata

  • Download URL: tensorstore-0.1.26.tar.gz
  • Upload date:
  • Size: 4.9 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.14

File hashes

Hashes for tensorstore-0.1.26.tar.gz
Algorithm Hash digest
SHA256 418a9edd454d30c0bde5bd15dcc5f2649daee5c602f0cfbc50ab9f939fb1a294
MD5 c1d7a2c35c56b8ef432aa78523fcf350
BLAKE2b-256 ee8b10c5890e94a7b9eff695d63e24bc4bce451527f1960129fcc90cec036301

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.26-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.26-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 1d3ecf70f06b22b9a1097ff4d5d5b0661c1805c5d901024b63e5e5a2ab7a6c7c
MD5 3576d1a3e64f722807f910a87bad8e36
BLAKE2b-256 f3c315b446208e8f23bd172539be5af6e485cde9c3048ab1c88248cf2c729e28

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.26-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.26-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 047569025d4747783f19fdf497957932edf0ca99cefe0587e8a431162c26c586
MD5 df90b704da6ce04d1a2c07ffdec789aa
BLAKE2b-256 0f01edb43dccc3d97faaa3d7d02547c0cf663ffc453d9461840be249839e1f3b

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.26-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.26-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 18dc9416a3ae6a48cb2b840993c00d5b2045d6ce0d82dd992e8f567b11feeede
MD5 66e1e69981eda023b08a13d379da568a
BLAKE2b-256 8154dd909cfea5cc3c5a821145f3c9c7c1fe6424dfd41c8fa1089c9d1f8b67ca

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.26-cp310-cp310-macosx_10_14_x86_64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.26-cp310-cp310-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 3ac23b8f2b79615ada7637c15ec6efa5106ea7ac5797644e0119c0eed4976607
MD5 e47f1d0e669c5ce28ee606f987cd6f55
BLAKE2b-256 1ff391b4692e777769594bea453de0eca0fdde425ffb248e7989c7d861b57698

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.26-cp39-cp39-win_amd64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.26-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 f008bff7c987c40d3f991f8cde5b4ab3ee477dd6376945ae6b9eb32e0c83f840
MD5 e59138c1a238126f405d21ea664ef67a
BLAKE2b-256 15250a2ba32fce32e2a01d2df929fa175bb73ddf9183c6e552ad26344ee3c27f

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.26-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.26-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 02dd1d7ca916dc6569eda634faa614bf7626a604d678bf8fe985ea1c5c6829a3
MD5 d7f826a444e4b6361293e69f3c13cdaa
BLAKE2b-256 71f26e270c3df7dc40d874a83f086ba27abbe18712f415973b68f1f7251d7fde

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.26-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.26-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 13ff5bd92fe9e52825a3e9562618996ad2229b772679311cfbcabb7aa1ff96c3
MD5 2fb7ef3a82b86a1a22486b80b88864d2
BLAKE2b-256 d01f95a234497a9c9b735085138e0020a68d051a34a4697fe8cb530742a7d43a

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.26-cp39-cp39-macosx_10_14_x86_64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.26-cp39-cp39-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 4196fbf2865c3af6b5e64f815c2fb6976f9dbc8440e3b462eabddca1d6f1321e
MD5 b64889ae6e19f268bcaad0319594c199
BLAKE2b-256 483c1023da1691b25517912d959b736a93b2034a9218ad71755bf408c1c5a7b3

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.26-cp38-cp38-win_amd64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.26-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 29407a0f335d0671b9fdffa613626987ef311ad84cdf40926c34cb0d7e059b25
MD5 66d5c4a2feefd853955eb275dac08549
BLAKE2b-256 b54a90b2983a0e8f4eab9ddd6e1f60e3baa7b817a344634b1a4248759b0436e0

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.26-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.26-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 8d12d3039d09dd2106099250667fd44b42c77aeed1f5e1724a27615fd316fe1c
MD5 366ab8397284765431d6906e9a7574a0
BLAKE2b-256 202fbef28d2ea26dc09acccbbccc1e71abaa4fcf6323045f775e666239cc3cac

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.26-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.26-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 1b350bd3e5c361dbf8bb804c69c522a0c89205909b6ea73432136b6b8c4e651a
MD5 db2c5497f7fd163c93bb07571e8b7c72
BLAKE2b-256 35a8fbcb5d6075aad0a328de3e0dd2e5a7e3971fff8f748c2d64ad58e33c3c5d

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.26-cp38-cp38-macosx_10_14_x86_64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.26-cp38-cp38-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 a096face50ae61b3a538f8569f887642d353ef0f1d85b3a61b89318734bd8381
MD5 d0e908c5647501a58e6d571f37de88fe
BLAKE2b-256 b5aae1d0b989fd71ef081a5f89054f72c2be8b029d5e85bb493ec591479050a4

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.26-cp37-cp37m-win_amd64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.26-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 a53ee6c626e2b7e9157c267d91bc98fc3b8fa20383a3b14457c2edf9feb97bfe
MD5 19e225e12f5817bb45f8fd12905e08fe
BLAKE2b-256 9202f9e313547adf48348b91057ffe53f0bd0c82322a292cc0d7e66b698f2358

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.26-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.26-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 d98bc687e81052ba8c3718f4895caf6ddf45ae6438a9df7af7335770f9cf824d
MD5 5d9e5d3d90fd83d65c84968cabbc90b1
BLAKE2b-256 613ca0156f06629b2f9c1e54230e4507492737c3b34e0a4fbd91ac29a32a818e

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.26-cp37-cp37m-macosx_10_14_x86_64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.26-cp37-cp37m-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 bc4aa90a519fb0bdaef00e6168b7d887573cd31adaef0d11534c5f3980ff6081
MD5 3a24b3082f9c01f467f8138d9af7c9e1
BLAKE2b-256 fd39239dcb1203e790685b9199965c35e205290f10a8b0faf3a5ecff998b2c2f

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page