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-0.1.48.tar.gz (6.4 MB view details)

Uploaded Source

Built Distributions

tensorstore-0.1.48-cp311-cp311-win_amd64.whl (10.7 MB view details)

Uploaded CPython 3.11 Windows x86-64

tensorstore-0.1.48-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.8 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64

tensorstore-0.1.48-cp311-cp311-macosx_11_0_arm64.whl (12.7 MB view details)

Uploaded CPython 3.11 macOS 11.0+ ARM64

tensorstore-0.1.48-cp311-cp311-macosx_10_14_x86_64.whl (14.7 MB view details)

Uploaded CPython 3.11 macOS 10.14+ x86-64

tensorstore-0.1.48-cp310-cp310-win_amd64.whl (10.7 MB view details)

Uploaded CPython 3.10 Windows x86-64

tensorstore-0.1.48-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.8 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

tensorstore-0.1.48-cp310-cp310-macosx_11_0_arm64.whl (12.7 MB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

tensorstore-0.1.48-cp310-cp310-macosx_10_14_x86_64.whl (14.7 MB view details)

Uploaded CPython 3.10 macOS 10.14+ x86-64

tensorstore-0.1.48-cp39-cp39-win_amd64.whl (10.6 MB view details)

Uploaded CPython 3.9 Windows x86-64

tensorstore-0.1.48-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (13.8 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

tensorstore-0.1.48-cp39-cp39-macosx_11_0_arm64.whl (12.7 MB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

tensorstore-0.1.48-cp39-cp39-macosx_10_14_x86_64.whl (14.7 MB view details)

Uploaded CPython 3.9 macOS 10.14+ x86-64

File details

Details for the file tensorstore-0.1.48.tar.gz.

File metadata

  • Download URL: tensorstore-0.1.48.tar.gz
  • Upload date:
  • Size: 6.4 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.8.18

File hashes

Hashes for tensorstore-0.1.48.tar.gz
Algorithm Hash digest
SHA256 cf07a75aaa84098cf7b4d673485a326cde1695101225a04bc7b557fcc3c2cbb7
MD5 8ac2710f208ae59f145350d0053a09f7
BLAKE2b-256 8d11e503f2c903b37985ae5ed45b3c4aebe2d159c6484153bcca8dc0d9666956

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.48-cp311-cp311-win_amd64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.48-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 3ad7719d9ef2ceda0a914045b4b16df7ea34a796c1c554873efcd5f111dbf571
MD5 34941598216791944892162f73ec4f02
BLAKE2b-256 fb2d7f3ded4280ee2dd02a76eb04623394f70bc66e02b5785f3b164d55915911

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.48-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.48-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 71fd49927789a4aeaf27a49efa37b58deb90a77d692818e5933475131d9d2d58
MD5 5cc0c07253b027c8558b007b82d50eba
BLAKE2b-256 df10f93ea2be44dc400a6acbb9eadfdcc8fabd98a47de10f83fe974eef9313af

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.48-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.48-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 accb376b0c2fea352e6c96b2644b1719bfcd13e9dc38434aa5ec263ed656b29c
MD5 850fb050649af88080447cfb26517b5a
BLAKE2b-256 32fbf70ef008b8c332bce95a4f5d3fa2939ecd6f8a66a52f7cf746d4bd64487d

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.48-cp311-cp311-macosx_10_14_x86_64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.48-cp311-cp311-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 5fe92b3af8afa1f385357ae21d55beaf432a212103dbec8460be65e24cde0abc
MD5 2214cf658cea74cbf066cb63938d56d5
BLAKE2b-256 53ef51864cb201568479c79b66fae47ab6b719b907fedea7067957fc9df6b1fc

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.48-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.48-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 c76f38f71045c3b4594f49ea040a38399db5936471fbbdedef524c07c204294e
MD5 fbd23f8d82e1321df6b65f275570d1bd
BLAKE2b-256 5581bb27b26741bc976fec33ec8b0cc09d79c30cc9ff0bee8c11ddf65858defc

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.48-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.48-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 4533b5e302cba6cfaa97c53a3da0cceb67a918ca4d1a4f18212d14782201b99a
MD5 61d262bb0df202bdae085ba01b74415a
BLAKE2b-256 1162a07d4c838dd3ebac4efe7adc08bf096d54a0744248f81289da67b4e2375e

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.48-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.48-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 586acf91bf28803b9a086a9381988b9ac788c01dabb3dfae24fb32e223660b9b
MD5 d60e178c56b4e951f36ce57dc1719559
BLAKE2b-256 736021a2c33cf46b6eb30306abb56298a0efc4ec5152590e9fe250a16f444b13

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.48-cp310-cp310-macosx_10_14_x86_64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.48-cp310-cp310-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 7dfc12ed0681cb6cdfa0cf6d77debfd9ae7a6ebd0c1dffd0aed833b263c4f0fc
MD5 8a6f33dc23f22769b257bce1a8a32f14
BLAKE2b-256 65fdfeab658a6584fa039c3e0a73ec96178011bf9b3db7d572c6309d52134615

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.48-cp39-cp39-win_amd64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.48-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 e9e4ef3334b18f6ffc39d479e42118f6f66bb99eee8f920f0a97a71f9cf0f092
MD5 9358b74ee58d544fbb54db85c76e84ce
BLAKE2b-256 e5388fde7987572e36a16674feb8a6747aabf631931c1b17d3bef5db26ab880d

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.48-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.48-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 6f4e658b4159596a2fd54f20432593b6b76eb2bbcbcceb55e490562da82429ca
MD5 7d2f48f872a6a2e0c9c023763e370855
BLAKE2b-256 4b11b34d38600a427fd8a7e16543408bf594977a617a78f7a4695a0d4156bbc2

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.48-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.48-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 2ec05e9b5616b1661380dbe7dcd6c17ccf909be0da80b4350e2806ef05803fe0
MD5 f500ba3705c19b4ddbe04cc73f5fba5f
BLAKE2b-256 6b99749c50477d5ea665f87e8c5fd91f1bc54e14a04f5be22f24148bb074b3f9

See more details on using hashes here.

Provenance

File details

Details for the file tensorstore-0.1.48-cp39-cp39-macosx_10_14_x86_64.whl.

File metadata

File hashes

Hashes for tensorstore-0.1.48-cp39-cp39-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 e0314fb0af93a695a33b5d02b4a90e5fb2a664561ec40799a8f1de28760ce833
MD5 6b55cb740fef9a17e6477eee3888d914
BLAKE2b-256 21a555796f7d6fe27af91980e1a62889e5ec2c0e0dc1feba148e7ff61d5cb1c2

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