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-0.1.40.tar.gz (5.7 MB view details)

Uploaded Source

Built Distributions

tensorstore-0.1.40-cp311-cp311-win_amd64.whl (10.0 MB view details)

Uploaded CPython 3.11 Windows x86-64

tensorstore-0.1.40-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (12.9 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64

tensorstore-0.1.40-cp311-cp311-macosx_11_0_arm64.whl (11.9 MB view details)

Uploaded CPython 3.11 macOS 11.0+ ARM64

tensorstore-0.1.40-cp311-cp311-macosx_10_14_x86_64.whl (13.8 MB view details)

Uploaded CPython 3.11 macOS 10.14+ x86-64

tensorstore-0.1.40-cp310-cp310-win_amd64.whl (10.0 MB view details)

Uploaded CPython 3.10 Windows x86-64

tensorstore-0.1.40-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (12.9 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

tensorstore-0.1.40-cp310-cp310-macosx_11_0_arm64.whl (11.9 MB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

tensorstore-0.1.40-cp310-cp310-macosx_10_14_x86_64.whl (13.8 MB view details)

Uploaded CPython 3.10 macOS 10.14+ x86-64

tensorstore-0.1.40-cp39-cp39-win_amd64.whl (10.0 MB view details)

Uploaded CPython 3.9 Windows x86-64

tensorstore-0.1.40-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (12.9 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

tensorstore-0.1.40-cp39-cp39-macosx_11_0_arm64.whl (11.9 MB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

tensorstore-0.1.40-cp39-cp39-macosx_10_14_x86_64.whl (13.8 MB view details)

Uploaded CPython 3.9 macOS 10.14+ x86-64

tensorstore-0.1.40-cp38-cp38-win_amd64.whl (10.0 MB view details)

Uploaded CPython 3.8 Windows x86-64

tensorstore-0.1.40-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (12.9 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

tensorstore-0.1.40-cp38-cp38-macosx_11_0_arm64.whl (11.9 MB view details)

Uploaded CPython 3.8 macOS 11.0+ ARM64

tensorstore-0.1.40-cp38-cp38-macosx_10_14_x86_64.whl (13.8 MB view details)

Uploaded CPython 3.8 macOS 10.14+ x86-64

File details

Details for the file tensorstore-0.1.40.tar.gz.

File metadata

  • Download URL: tensorstore-0.1.40.tar.gz
  • Upload date:
  • Size: 5.7 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.8.17

File hashes

Hashes for tensorstore-0.1.40.tar.gz
Algorithm Hash digest
SHA256 41517dbd3919e5a5ee2be69b51bdd528b57c9b35f533e6fc83f6155a378fdf8a
MD5 e7d28a70a2688602a13d285a27ab244a
BLAKE2b-256 efb02834bf5bd272b74b6ad4e7bcd390b9a4e37975332bd0d597b951576cd58d

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.40-cp311-cp311-win_amd64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.40-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 26ab0b2dfefbb3c5bb12ae8e27ca273f8b15069fad344bde615a5e2dbdf1171d
MD5 882c7762909fb3416c9cb4cc9f801d66
BLAKE2b-256 7a10ee60a7ca41dae44e2eb823904b461be1f55d9564b0d661a9c119f63cac7e

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.40-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.40-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 060e63f10079cfc26ee1b110b190e88c91d3278528405d6991de266bcdd273fb
MD5 f45cda649691cdae542ee86a09bc1462
BLAKE2b-256 733b2404e892bf91da1e748a8ce2f29b074f2c267f52daacf888c6b005dc9755

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.40-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.40-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 49bd2dbfd64f409e27f5bd326e98c95a9ade40f66f482e5277b097b94c070a7d
MD5 aa2cf6df26f7fe4d52151ce67362392f
BLAKE2b-256 8265b272cdc7ac2f079fc73d51bfb8a52c5d6f007faf5aa0a236c9fd63a8d7fd

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.40-cp311-cp311-macosx_10_14_x86_64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.40-cp311-cp311-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 79ef100f26e731c12fc4872efaaa4bee505b918104731b3521a55a2974281a51
MD5 cddda65299ed8fdd54ccd390c809e992
BLAKE2b-256 f50d3b6326daac39a9aaebc79cd53229a8bc3a6ef0c9efd41e1c5c9dc1ad2d14

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.40-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.40-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 69e3f3352843fe4c3334a7634aea8b60e53263639d06383edbd9fc63f86293cd
MD5 3eab3d9686581608814833d61c4b5071
BLAKE2b-256 d6dc17cc34dab40b1349a822f5a5fc001bab056fa949027de3bf2d6a39ca9af6

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.40-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.40-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 66ecb6cc12d5f79d0231b76da4b369216aa75c7c368e48eb646e3c786b66e36c
MD5 207c4321d99cea8c3cfed86a06e0eae8
BLAKE2b-256 6ad753b9b412602f57537e31009b252f4159864aa9c76c88457a8e89ebc870ea

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.40-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.40-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 e93b5ae2bbb54e7a1b15ae055d6cfc7e6f6b0311741b4f58d8f8ff29a40f5671
MD5 13aefb43cded093f6d4584aa9ecbee44
BLAKE2b-256 d365aaab5d961e3a9545b23f9cb1b8e3b36db6450ed826790c81526d548a6362

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.40-cp310-cp310-macosx_10_14_x86_64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.40-cp310-cp310-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 9a184f8b3a6392e1b7f209bd8932328a2df086625f75d8bc9d21ddff6e909614
MD5 65a72d517626f444f83ab989208f24a0
BLAKE2b-256 2fc19c72e2b486fbb250bbc30b06f813b255d8e23a60fbff83b3c0f7be3472de

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.40-cp39-cp39-win_amd64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.40-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 9dd7027591743a19965f3b87363b0c7725d6d8e52acb5a9ea19533dbcf40fa13
MD5 7c6c42737734ceb682b890d676cd76fd
BLAKE2b-256 018b98a95efde0d5b1e81b804a0037e805d79f5abb8dee13c44ace2bc3bfd87e

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.40-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.40-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 8ee0b3c07583de7908f451ea7ede6d8ec37b9e0b4947ddbc9e83e600bdfa6ce6
MD5 169bd51fa1da6b2f3ab796e4d6d4c818
BLAKE2b-256 36a897d76c0cea3f4558a9b2f7f79d592e40841f1aef879aff063d89f0bf6365

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.40-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.40-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 d9e25a1a4a32fc6dc99f1b1f04d2a46a3e62234de176f160a59cfa09cab158eb
MD5 cadc7058aa73331699d6745593827962
BLAKE2b-256 f1398c9bd769e49f0675476c4a3f46003264d636efbc1f9efc44ff252741551e

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.40-cp39-cp39-macosx_10_14_x86_64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.40-cp39-cp39-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 33a84480f6f462fb456a6b4a5ad42e08cc030ece719d9b305c6cb74aa4a70717
MD5 0435de0226ac59c914216bb887fe9f41
BLAKE2b-256 b08532dd1e423406bd4cfb160b425a116cee4edda2eda6b0248d170a0206dcff

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.40-cp38-cp38-win_amd64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.40-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 f32ce021112fba4efb096e0ebe16733b8786d33a031e3f0ec289b86d426e25c3
MD5 b0111f8ad3d0cbfe0a7722ef66b80543
BLAKE2b-256 dda345ce51432c28ab7e5a1ae383f47a7a8608510aca628078d21a4b718e4ee0

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.40-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.40-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 f7751e74b9eb571d827d4bbce6f7c5b349343e45ee1962d934019ef57bc79e73
MD5 0d70c3158fe1eea1d1f7a6cc7c6caef9
BLAKE2b-256 b1e0052ad528496a406d5f6ebaf3db379e4c016e97617f8da19b9d18d6e6b89e

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.40-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.40-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 81224f28022dfa186e8fbcc5d0b9859c2b2b3f284c5f3db42d6cc958cb83dab5
MD5 543899f07edde3fb12307ccd496536e4
BLAKE2b-256 6f068d9b6bf3e8df5a8de15b2621bfa49e346ca284491b4f906634fbfd2d7ec2

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.40-cp38-cp38-macosx_10_14_x86_64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.40-cp38-cp38-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 dc3242c372786660066ede40340dfd7984de86f3c841ad4d8d1eb82a1d80affb
MD5 67d24a0308e4857db7e4f9a73b974062
BLAKE2b-256 6eda69f07e5babf2b83802fa92fc1b4a35fbdf53e2877b095e510ca91bef08a2

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