Skip to main content

Read and write large, multi-dimensional arrays

Project description

TensorStore

License PyPI Build Docs

TensorStore is an open-source C++ and Python software library designed for storage and manipulation of large multi-dimensional arrays that:

  • Provides advanced, fully composable indexing operations and virtual views.

  • Provides a uniform API for reading and writing multiple array formats, including zarr and N5.

  • Natively supports multiple storage systems, such as local and network filesystems, Google Cloud Storage, HTTP servers, and in-memory storage.

  • Offers an asynchronous API to enable high-throughput access even to high-latency remote storage.

  • Supports read/writeback caching and transactions, with strong atomicity, isolation, consistency, and durability (ACID) guarantees.

  • Supports safe, efficient access from multiple processes and machines via optimistic concurrency.

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

Getting Started

To get started using the TensorStore Python API, you can install the tensorstore PyPI package using:

pip install tensorstore

Refer to the tutorials and API documentation, or the announcement on the Google Research Blog for more details.

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-0.1.42.tar.gz (6.2 MB view details)

Uploaded Source

Built Distributions

tensorstore-0.1.42-cp311-cp311-win_amd64.whl (10.1 MB view details)

Uploaded CPython 3.11 Windows x86-64

tensorstore-0.1.42-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.0 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64

tensorstore-0.1.42-cp311-cp311-macosx_11_0_arm64.whl (12.0 MB view details)

Uploaded CPython 3.11 macOS 11.0+ ARM64

tensorstore-0.1.42-cp311-cp311-macosx_10_14_x86_64.whl (13.9 MB view details)

Uploaded CPython 3.11 macOS 10.14+ x86-64

tensorstore-0.1.42-cp310-cp310-win_amd64.whl (10.1 MB view details)

Uploaded CPython 3.10 Windows x86-64

tensorstore-0.1.42-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.0 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

tensorstore-0.1.42-cp310-cp310-macosx_11_0_arm64.whl (12.0 MB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

tensorstore-0.1.42-cp310-cp310-macosx_10_14_x86_64.whl (13.9 MB view details)

Uploaded CPython 3.10 macOS 10.14+ x86-64

tensorstore-0.1.42-cp39-cp39-win_amd64.whl (10.1 MB view details)

Uploaded CPython 3.9 Windows x86-64

tensorstore-0.1.42-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.0 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

tensorstore-0.1.42-cp39-cp39-macosx_11_0_arm64.whl (12.0 MB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

tensorstore-0.1.42-cp39-cp39-macosx_10_14_x86_64.whl (13.9 MB view details)

Uploaded CPython 3.9 macOS 10.14+ x86-64

tensorstore-0.1.42-cp38-cp38-win_amd64.whl (10.1 MB view details)

Uploaded CPython 3.8 Windows x86-64

tensorstore-0.1.42-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.0 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

tensorstore-0.1.42-cp38-cp38-macosx_11_0_arm64.whl (12.0 MB view details)

Uploaded CPython 3.8 macOS 11.0+ ARM64

tensorstore-0.1.42-cp38-cp38-macosx_10_14_x86_64.whl (13.9 MB view details)

Uploaded CPython 3.8 macOS 10.14+ x86-64

File details

Details for the file tensorstore-0.1.42.tar.gz.

File metadata

  • Download URL: tensorstore-0.1.42.tar.gz
  • Upload date:
  • Size: 6.2 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.8.18

File hashes

Hashes for tensorstore-0.1.42.tar.gz
Algorithm Hash digest
SHA256 1526bc2d437edf52cf5bcfcbd4af10163478e7512897b1c86395245e46eca62a
MD5 07808c17deccf414864fc90beca0a46a
BLAKE2b-256 bf9b14d2a8ec11aedd717d06f9a9594c44112880c2005d70c2f3d66738528bd6

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.42-cp311-cp311-win_amd64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.42-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 d39740842ccd207aa2f4be7ae2409a33a4dec69aa6b5f57dcc81ed803e23ce29
MD5 4c4a7cf48233bca77ce03f98bdc04ae6
BLAKE2b-256 54fc811441c6e1a36985800909077523b5f02a9fd35b66844640a488bdb5b33f

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.42-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.42-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 4ccb04e39463007634539344be68fc44d2f94839a9eaa8a22ac277db46c44f84
MD5 1a4896151d46f2dfde9806e7f0bd3d2a
BLAKE2b-256 480af073cec0ba481dd639f6e220c552c6fd7f24d3fe50a8f3d0b35b86ed72fb

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.42-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.42-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 1c07b4bb90f4c3151e1808a7f3384bf80eab6ca020d62c781aec61c88de632cf
MD5 62b474055af84c326f13aed8cfe08c12
BLAKE2b-256 e8b0a707ad15b5df0414837590f0b8c35937eb68cabc657154bb6ce6e49b72a4

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.42-cp311-cp311-macosx_10_14_x86_64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.42-cp311-cp311-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 19ef63adce6aaad042833779f25544de0161bbe5bb77c9abf1be3d0eaf4549c9
MD5 0e3cd0e0deb11195a6522f0e754f2321
BLAKE2b-256 28b596053aff7ca19a3793eae8eab55d20f37de2f326b8de5d4c909b73d18936

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.42-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.42-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 d54ef49defa543beff1ce50e9fe497f515a6fbe95d788246c806d87a91447e6f
MD5 a45fc6019ce8190618f81f97dc090660
BLAKE2b-256 a8ee7018dfe7e533a3af08aaa5685883798bd6fa207841cee81f19d4d16dc127

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.42-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.42-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 41f2e053cb9ce1e0f776b42a2e91a02b2d1465e43092f6bfda51c816e58a45e1
MD5 280487b8224686dad40d9e3459ef44be
BLAKE2b-256 3f920939f3c028cae72cde44daafa54fc76f651e9ba59004c4a09544af01d247

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.42-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.42-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 7590dd8e0cc066609da24ea95ada555ec8d2c3bb1cb91d5414ff5637afc83782
MD5 38a5df1ce7205175a3c1d6c05af78ffe
BLAKE2b-256 99f47af35d499711f4bbf3cc67e7669487d2a782d9ae8e724587538731b1ce62

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.42-cp310-cp310-macosx_10_14_x86_64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.42-cp310-cp310-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 99ce763c6328040bd4b787a9e3469d17300fd84dd04dc059ec7a3e14efedf927
MD5 b171ad7b2f481dc5fd5d64b02ffd37df
BLAKE2b-256 3b9ac35960fdac857eb9d054ec1c1596087b68655ef83f5a658b207b77c7c99f

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.42-cp39-cp39-win_amd64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.42-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 7c8be0422a44c46aa0aee1e4ea9d38a61ca1fb87de8482cd3030ba655f092586
MD5 6c05cd802011101efc34bb6a5dbd4a98
BLAKE2b-256 07dc9e2468fad0a2658f84451bdcd031c11297cf29a90215e1c5a6ced8fc16ce

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.42-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.42-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 9944bba17254ae4a3a1341b13f4b8aedb8bcafb591c5f12150a142224eeedf35
MD5 eb7f9d2efa0e86fa6252d691e8039399
BLAKE2b-256 1acb411491152a858c715b4c0cb86c2c084876ef79bffecf4ee4df59b2413cd3

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.42-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.42-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 2b42583883b63db19532fdd513f7c4258eefd4f5c6e13755a89f1223d4cba9ed
MD5 9041e5d472e01fa1dfad9863663cee57
BLAKE2b-256 e00164318417a5d46cc521135a7a59c062e49c48aca76f77eb5c6283180e996f

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.42-cp39-cp39-macosx_10_14_x86_64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.42-cp39-cp39-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 51841c75ef4b8853b7e61a3d3f8c46ffe22d480b2c46a2b42a0fdf46d310261a
MD5 e3b7995e22e1855c26b2b62d20eddae6
BLAKE2b-256 4381bc7ee911a7729747b49de906a2647a9ed37927d8c9833e1044e5b2473856

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.42-cp38-cp38-win_amd64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.42-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 3c2d1737d5c82993c33d4db23ce9b2260f623716dc7a9ec658ccfe69c69f2975
MD5 4de529b851f1b056847c3d648524a0ea
BLAKE2b-256 71148f5a33d5014b9ce600d1427d9695c10802cbbcdda6079753b21f5874e008

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.42-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.42-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 6ea4fb88849d4a6453ca36475cf666a2f8976184fc65abc119ccd602516ec502
MD5 6bdbb426664876935a8faeae58b62309
BLAKE2b-256 03892d9d124961d9696c4371b633f5f2e58d734c1b0b88549d865784ede773fb

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.42-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.42-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 f11fa73e31c0c029e6ca191d7930aba4dc8939c71648e434a26ac6f416732fe6
MD5 ac52a78d1afe663f2c99238651942eeb
BLAKE2b-256 2d80a1f6e33badfdffafcbed7b958c8fae19e3152704a1ae3cd6bc0e7c1d8031

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.42-cp38-cp38-macosx_10_14_x86_64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.42-cp38-cp38-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 b5e4a4e3b4088ad42596ebc88e9b59223dc1da30475e1ff18ef038dec3f0485c
MD5 c2586eefcf525efdceb6f039a17e9069
BLAKE2b-256 dcd7c99a9f1ab61bb52e75b1ca1d5feaeb0af4b0525827953a7fb534f9a30544

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