Skip to main content

Python API for efficient storage and retrieval of single-cell data using TileDB

Project description

Overview

This is a Python implementation of the SOMA API specification for interacting with the Unified Single-cell Data Model.

Installation

TileDB-SOMA is available on PyPI and Conda, and can be installed via pip or mamba as indicated below.

python -m pip install tiledbsoma
mamba install -c conda-forge -c tiledb tiledbsoma-py

To install a specific version:

$ python -m pip install git+https://github.com/single-cell-data/TileDB-SOMA.git@0.0.6#subdirectory=apis/python

To update to the latest version:

$ python -m pip install --upgrade tiledbsoma

From source

  • This requires tiledb (see ./setup.cfg for version), in addition to other dependencies in setup.cfg.
  • Clone this repo
  • cd into your checkout and then cd apis/python
  • python -m pip install .
  • Or, if you wish to modify the code and run it, python -m pip install -v -e .
  • If the TileDB and TileDB-SOMA libraries are locally installed to a custom directory, such as /usr/local, set the path with environment variables TILEDB_PATH and TILEDBSOMA_PATH, TILEDB_PATH=/usr/local python -m pip install -v -e .
  • Optionally, if you prefer, you can run that inside venv:
    $ python -m venv venv
    $ . ./venv/bin/activate
    $ python -m pip install -v -e .
    
  • In either case:
    python -m pytest tests
    

Status

Please see https://github.com/single-cell-data/TileDB-SOMA/issues.

platform_config format

When accessing SOMA APIs, TileDB-specific settings can be configured with the platform_config parameter. The options accepted by TileDB SOMA are described here, using TypeScript interface syntax:

interface PlatformConfig {
  tiledb?: TDBConfig;
}

interface TDBConfig {
  create?: TDBCreateOptions;
}

interface TDBCreateOptions {
  dims?: { [dim: string]: TDBDimension };
  attrs?: { [attr: string]: TDBAttr };
  allows_duplicates?: bool;

  offsets_filters?: TDBFilter[];
  validity_filters?: TDBFilter[];

  capacity?: number;
  cell_order?: string;
  tile_order?: string;
}

interface TDBDimension {
  filters?: TDBFilter[];
  tile?: number;
}

interface TDBAttr {
  filters?: TDBFilter[];
}

/**
 * Either the name of a filter (in which case it will use
 * the default arguments) or a specification with filter args.
 */
type TDBFilter = string | TDBFilterSpec;

interface TDBFilterSpec {
  /** The name of the filter. */
  _name: string;
  /** kwargs that are passed when constructing the filter. */
  [kwarg: string]: any;
}

Information for developers

Please see the TileDB-SOMA wiki.

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

tiledbsoma-1.5.3.tar.gz (204.1 kB view details)

Uploaded Source

Built Distributions

tiledbsoma-1.5.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (14.7 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64

tiledbsoma-1.5.3-cp311-cp311-macosx_11_0_arm64.whl (9.1 MB view details)

Uploaded CPython 3.11 macOS 11.0+ ARM64

tiledbsoma-1.5.3-cp311-cp311-macosx_10_14_x86_64.whl (11.7 MB view details)

Uploaded CPython 3.11 macOS 10.14+ x86-64

tiledbsoma-1.5.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (14.7 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

tiledbsoma-1.5.3-cp310-cp310-macosx_11_0_arm64.whl (9.1 MB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

tiledbsoma-1.5.3-cp310-cp310-macosx_10_14_x86_64.whl (11.7 MB view details)

Uploaded CPython 3.10 macOS 10.14+ x86-64

tiledbsoma-1.5.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (14.7 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

tiledbsoma-1.5.3-cp39-cp39-macosx_11_0_arm64.whl (9.1 MB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

tiledbsoma-1.5.3-cp39-cp39-macosx_10_14_x86_64.whl (11.7 MB view details)

Uploaded CPython 3.9 macOS 10.14+ x86-64

tiledbsoma-1.5.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (14.7 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

tiledbsoma-1.5.3-cp38-cp38-macosx_11_0_arm64.whl (9.1 MB view details)

Uploaded CPython 3.8 macOS 11.0+ ARM64

tiledbsoma-1.5.3-cp38-cp38-macosx_10_14_x86_64.whl (11.7 MB view details)

Uploaded CPython 3.8 macOS 10.14+ x86-64

tiledbsoma-1.5.3-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (14.7 MB view details)

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

tiledbsoma-1.5.3-cp37-cp37m-macosx_10_14_x86_64.whl (11.7 MB view details)

Uploaded CPython 3.7m macOS 10.14+ x86-64

File details

Details for the file tiledbsoma-1.5.3.tar.gz.

File metadata

  • Download URL: tiledbsoma-1.5.3.tar.gz
  • Upload date:
  • Size: 204.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.7

File hashes

Hashes for tiledbsoma-1.5.3.tar.gz
Algorithm Hash digest
SHA256 cef3d03f667ba6b806c19a76acb53619546aed1a70d4a604f9bc045c83731cbd
MD5 34b9066dd9f7226e242c2c0f7373efaf
BLAKE2b-256 49f530e2bcf2e696d9efe127cd36ca4fed3c4b8d7bc3bcb2bbb0354159e1d372

See more details on using hashes here.

File details

Details for the file tiledbsoma-1.5.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for tiledbsoma-1.5.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 c70fc1ac52c8d2ddf2318ca3ae1f401d3d098103e7a6ffddf62f36c566418f76
MD5 e6c05a375e316ee31246ec163dc630c1
BLAKE2b-256 520160c659f47c0e051e5f31039e221488edccc7f560ad1ce951fbfb79650498

See more details on using hashes here.

File details

Details for the file tiledbsoma-1.5.3-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for tiledbsoma-1.5.3-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 ef92fae3657f7ccd097eac0efecd0636b15d15e793825c3940c0ce5c7d547e02
MD5 465be3b9650f83190296fb6c6912287b
BLAKE2b-256 e728e525968f7bc84876cdc56db4db3c8afdc9976e1dc5da940de4a34a9086fe

See more details on using hashes here.

File details

Details for the file tiledbsoma-1.5.3-cp311-cp311-macosx_10_14_x86_64.whl.

File metadata

File hashes

Hashes for tiledbsoma-1.5.3-cp311-cp311-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 9caf79c73df770455a2d9089372d90374afd9dca9d48c50eee20cb98c7705ea3
MD5 428d53b5b39ceba87f36e8a8cc45ba73
BLAKE2b-256 00ccac3f010f26970afd7d04e01121880f50adf56fa22ca8883e241397ec27e4

See more details on using hashes here.

File details

Details for the file tiledbsoma-1.5.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for tiledbsoma-1.5.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 1eefc6040f68930c56010476e0f7d90cf8f2bbb54e4d4450eaec40c1e2091ab4
MD5 ed0066a9bbff39aa5d339539f333588c
BLAKE2b-256 76fa75ef031d1be4e7a8864ab8b20364f00ad000783ba44ed93d3744268b5412

See more details on using hashes here.

File details

Details for the file tiledbsoma-1.5.3-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for tiledbsoma-1.5.3-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 a1e218c34b0a25698b1bcef1734b026d4dc8162d263420ba670cf05a26fbe652
MD5 21b5ac9b22252a1dad1b8571d24c4ffc
BLAKE2b-256 633ffaee92339d380e7503322161a9893f915149e66e956aa671d94d31b75573

See more details on using hashes here.

File details

Details for the file tiledbsoma-1.5.3-cp310-cp310-macosx_10_14_x86_64.whl.

File metadata

File hashes

Hashes for tiledbsoma-1.5.3-cp310-cp310-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 b78cd05eecabd25490edf181d5c240939273b57512a3bef73846b0307bbe63b4
MD5 b87b9f76e09656ba5dacd777ce9ab99b
BLAKE2b-256 84aafb97161c030186efff07e28e1f0a25aacbac9de3de8c08f3c9c2507af59f

See more details on using hashes here.

File details

Details for the file tiledbsoma-1.5.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for tiledbsoma-1.5.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 cb85da550755138d449a139cd41d7c2710e32170d3d7e8b97cce4c9257c6332a
MD5 08827da94e45d267e8b22afb44bc1f57
BLAKE2b-256 79bc2cc42a9ade30494cc7cfe13a732f903baf94c125d8a871b48fe6f6e1bc5a

See more details on using hashes here.

File details

Details for the file tiledbsoma-1.5.3-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for tiledbsoma-1.5.3-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 08cf07e242e223172be0011fd46b662d21ab268c811d30b3c826e79d696942a5
MD5 190af832d29f22127e33e2516bfb5726
BLAKE2b-256 eca437540a7a720b5ea7b3922d6d99b5086d4ae36dbba3572ef8c39fb280c148

See more details on using hashes here.

File details

Details for the file tiledbsoma-1.5.3-cp39-cp39-macosx_10_14_x86_64.whl.

File metadata

File hashes

Hashes for tiledbsoma-1.5.3-cp39-cp39-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 0c584bd10c7be35df9d56b2808bd1aa7127c9fe21e0d699c04d73e0676eef7e0
MD5 6a55cb16a8d2d7aebcb1bb28abee33ca
BLAKE2b-256 d309541abeb7eb86378cf2a6f25f37e54584d82b485ae8add679542d165f2fad

See more details on using hashes here.

File details

Details for the file tiledbsoma-1.5.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for tiledbsoma-1.5.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 df8d41154f845ce4fb15b6c14c77ff614f4ba94be0d1c6b2272088cd033b180b
MD5 77710cf0f723000e30c67c35d85b94f2
BLAKE2b-256 7dc80d3788be5a0f1f5aeeb4c4724782eceb086adaf98f5fff7d4300671f548c

See more details on using hashes here.

File details

Details for the file tiledbsoma-1.5.3-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for tiledbsoma-1.5.3-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 74b4075f2594195c379cecc69ac95754d13c5165cd8abc3664c757078e773f19
MD5 ee9fb0bc5786816aea5b7b4c0c51f547
BLAKE2b-256 f1a190cf0afbaf91de4c05f74eab8918cb8dc61d4f23791e872db6bdf8285ff7

See more details on using hashes here.

File details

Details for the file tiledbsoma-1.5.3-cp38-cp38-macosx_10_14_x86_64.whl.

File metadata

File hashes

Hashes for tiledbsoma-1.5.3-cp38-cp38-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 40b45b3f25f65bb78ddb4a450c6ae892bf5803a5b3fb1ce35a28bb54d5004ffc
MD5 041d143cba3ebf90dcff8ed459bee30d
BLAKE2b-256 83f63c6b1207d7d34f7479022c7adf50ed510bfc96d964acbade731ab66a6bbb

See more details on using hashes here.

File details

Details for the file tiledbsoma-1.5.3-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for tiledbsoma-1.5.3-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 6fb29a0ee8a4c49dcc2d532fa6ed8b9908c2c399ae921ec7e64cc035aeb54017
MD5 d745933a9600c1e2c29d1a744e744849
BLAKE2b-256 a849e2a2be6f0d03fd3dc5c7742a20732aa69a56a6c0bb985f7aa53aff680893

See more details on using hashes here.

File details

Details for the file tiledbsoma-1.5.3-cp37-cp37m-macosx_10_14_x86_64.whl.

File metadata

File hashes

Hashes for tiledbsoma-1.5.3-cp37-cp37m-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 f97f2778d4dfe2d225b47836dd84d3efe735098309196ebc3f44693924b3aae4
MD5 d5ee252d1de17d76a31840a236cc66d5
BLAKE2b-256 ad65b88e409047fd33eb5fb7c90154bcbd3b016e985646932e6ff47911398986

See more details on using hashes here.

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