Skip to main content

No project description provided

Project description

The author of this package has not provided a project description

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

vegafusion_python_embed-0.10.0.tar.gz (6.3 MB view details)

Uploaded Source

Built Distributions

vegafusion_python_embed-0.10.0-cp310-none-win_amd64.whl (9.6 MB view details)

Uploaded CPython 3.10 Windows x86-64

vegafusion_python_embed-0.10.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (9.8 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

vegafusion_python_embed-0.10.0-cp310-cp310-macosx_11_0_arm64.whl (8.0 MB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

vegafusion_python_embed-0.10.0-cp310-cp310-macosx_10_7_x86_64.whl (9.0 MB view details)

Uploaded CPython 3.10 macOS 10.7+ x86-64

vegafusion_python_embed-0.10.0-cp39-none-win_amd64.whl (9.6 MB view details)

Uploaded CPython 3.9 Windows x86-64

vegafusion_python_embed-0.10.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (9.8 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

vegafusion_python_embed-0.10.0-cp39-cp39-macosx_11_0_arm64.whl (8.0 MB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

vegafusion_python_embed-0.10.0-cp39-cp39-macosx_10_7_x86_64.whl (9.0 MB view details)

Uploaded CPython 3.9 macOS 10.7+ x86-64

vegafusion_python_embed-0.10.0-cp38-none-win_amd64.whl (9.6 MB view details)

Uploaded CPython 3.8 Windows x86-64

vegafusion_python_embed-0.10.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (9.8 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

vegafusion_python_embed-0.10.0-cp38-cp38-macosx_11_0_arm64.whl (8.0 MB view details)

Uploaded CPython 3.8 macOS 11.0+ ARM64

vegafusion_python_embed-0.10.0-cp38-cp38-macosx_10_7_x86_64.whl (9.0 MB view details)

Uploaded CPython 3.8 macOS 10.7+ x86-64

vegafusion_python_embed-0.10.0-cp37-none-win_amd64.whl (9.6 MB view details)

Uploaded CPython 3.7 Windows x86-64

vegafusion_python_embed-0.10.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (9.8 MB view details)

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

vegafusion_python_embed-0.10.0-cp37-cp37m-macosx_11_0_arm64.whl (8.0 MB view details)

Uploaded CPython 3.7m macOS 11.0+ ARM64

vegafusion_python_embed-0.10.0-cp37-cp37m-macosx_10_7_x86_64.whl (9.0 MB view details)

Uploaded CPython 3.7m macOS 10.7+ x86-64

File details

Details for the file vegafusion_python_embed-0.10.0.tar.gz.

File metadata

File hashes

Hashes for vegafusion_python_embed-0.10.0.tar.gz
Algorithm Hash digest
SHA256 059cfb7d57d9bd49de0ceeaae98c1f65c10f77bb6967057b4a2808b599ae16c8
MD5 8ebbad074022c78db544da5bdd6682cc
BLAKE2b-256 e67a75e1e065f3b24b212a8f9fa6a5981b3af52b03aa29df2f3fdc0e3ecc6f60

See more details on using hashes here.

Provenance

File details

Details for the file vegafusion_python_embed-0.10.0-cp310-none-win_amd64.whl.

File metadata

File hashes

Hashes for vegafusion_python_embed-0.10.0-cp310-none-win_amd64.whl
Algorithm Hash digest
SHA256 b177b15698c774a3e8af17a52e902b9d152fd5e9498f2013a0dd38333aa05159
MD5 7d84a35330db3ed9917283103e015d09
BLAKE2b-256 9deaea584f6fbd4599ef296ee8c6fb4d22e7200ed3a853e5f892691009570658

See more details on using hashes here.

Provenance

File details

Details for the file vegafusion_python_embed-0.10.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for vegafusion_python_embed-0.10.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 46b7fff7f26a6238ef7678c51f5ac850bd7622e212431440c7e10f75bfd52262
MD5 c24612968f3d18b55abe1a16deee7f7d
BLAKE2b-256 93d11aba626f262abd492142e44fc23eb1206ab35facca2fca787079fad7738d

See more details on using hashes here.

Provenance

File details

Details for the file vegafusion_python_embed-0.10.0-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for vegafusion_python_embed-0.10.0-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 138b7c1e942e6203279d2542ddeae2b5262adf215ec0ea060e6c93268d34e587
MD5 d4526aeae33985d1da6e3515a12268ed
BLAKE2b-256 c4b729833e17fbd92d30175fd9dd2875ad3292e5f5d58faa740f6a45d2cc05e1

See more details on using hashes here.

Provenance

File details

Details for the file vegafusion_python_embed-0.10.0-cp310-cp310-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for vegafusion_python_embed-0.10.0-cp310-cp310-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 7c27e89d756502d5004f6f6279c0a8a1d5dd71b214103318fb34cad858376331
MD5 64414ebf6ffd828794dfeb94dced94de
BLAKE2b-256 3763a588c82caf75d3b003d3b81a2aa750bdf8ddfca5f47befe20ba8563399a7

See more details on using hashes here.

Provenance

File details

Details for the file vegafusion_python_embed-0.10.0-cp39-none-win_amd64.whl.

File metadata

File hashes

Hashes for vegafusion_python_embed-0.10.0-cp39-none-win_amd64.whl
Algorithm Hash digest
SHA256 4ac25e8b5bd580b92dbf62b768c6ce38e3f1f3ede55a799fbbd1f7de3763d96b
MD5 a1eb8e20397ce9afde87432cda0d79aa
BLAKE2b-256 a3604f04a9818115bfd7ecc3146150511a8e65ac875bb03b5f3c6f986231ac16

See more details on using hashes here.

Provenance

File details

Details for the file vegafusion_python_embed-0.10.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for vegafusion_python_embed-0.10.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 5fd8209714b63a8aacea474a967fe9212bf6bf9b60d30149ed08ddcd973b1489
MD5 883669a2b706c871d8f5b3dee2d20e4f
BLAKE2b-256 0dfc8a81965b054d335849b4e6d248cf5b26634dc96b208b7b1f2935faad761f

See more details on using hashes here.

Provenance

File details

Details for the file vegafusion_python_embed-0.10.0-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for vegafusion_python_embed-0.10.0-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 e7b445773822d7775e71d3e1b8ee667c2f755f9a42084fe128ea3ceb4e6fcf1d
MD5 6265688d1b9f9420ad4ae1f0d04179bd
BLAKE2b-256 536541b37a2812fa0c2a19a920169e39576c4c48caee454671d5b93c74eab2c8

See more details on using hashes here.

Provenance

File details

Details for the file vegafusion_python_embed-0.10.0-cp39-cp39-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for vegafusion_python_embed-0.10.0-cp39-cp39-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 f04891212b1cce23718f7012f3364c58637859ce1b10a72d5ba2c93c81f008e4
MD5 f27441106db1b081f981b50dc6360ec3
BLAKE2b-256 69300acb117dc8015094c0e69480912042e497a658cd3691a74ba831b7a0e1d7

See more details on using hashes here.

Provenance

File details

Details for the file vegafusion_python_embed-0.10.0-cp38-none-win_amd64.whl.

File metadata

File hashes

Hashes for vegafusion_python_embed-0.10.0-cp38-none-win_amd64.whl
Algorithm Hash digest
SHA256 778f2d8fb0049acab1581ffe96112af0c55b5c87d97265123b26a5718cbbb293
MD5 d5d6777fddd6310e8d0d0039900e45be
BLAKE2b-256 40b4bc8fef6f3a0f3b107b95d00de51e7eafb5497cce39828178e1863234609e

See more details on using hashes here.

Provenance

File details

Details for the file vegafusion_python_embed-0.10.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for vegafusion_python_embed-0.10.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 ba096217c2d791af1041849eb17095e5db4f95109974f9317f7d18b2de80e57a
MD5 5118a974b96edb0c6ae1a0204c49c7d7
BLAKE2b-256 58efc59b51ebe0075aa06bc2e95441acbbdb516e71d28af0197cc4de8d3ec3ef

See more details on using hashes here.

Provenance

File details

Details for the file vegafusion_python_embed-0.10.0-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for vegafusion_python_embed-0.10.0-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 775035707b895e68979a8ad95b79ab8ceb8db13567ed29c72e586b81491e6308
MD5 72741a3b064e829dafa0511b385333b6
BLAKE2b-256 1f3fc4a3c9b3457d5e05504b15adbcf053b04f5dc0aa5dda148fdeba091e20dc

See more details on using hashes here.

Provenance

File details

Details for the file vegafusion_python_embed-0.10.0-cp38-cp38-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for vegafusion_python_embed-0.10.0-cp38-cp38-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 a4e4f81db114dd08b3e166c90cb4283a0d1bd2ace1a58b15594f2219b3246a91
MD5 84098b2a3949712662a7c7e354b990e3
BLAKE2b-256 7d10ce3ab5ac51485adbac385e881b769d51255b6f1f05831426d759eb1e861f

See more details on using hashes here.

Provenance

File details

Details for the file vegafusion_python_embed-0.10.0-cp37-none-win_amd64.whl.

File metadata

File hashes

Hashes for vegafusion_python_embed-0.10.0-cp37-none-win_amd64.whl
Algorithm Hash digest
SHA256 b600fbbe328efa18c3185009c718238f1ae20367f531658e7db1c5f2c60e6a59
MD5 471186249405e9da6f70fb00a131e10f
BLAKE2b-256 8e8948ce97722c6452e5995477e07730f87f794c20ec94da7188b5c07c7340e8

See more details on using hashes here.

Provenance

File details

Details for the file vegafusion_python_embed-0.10.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for vegafusion_python_embed-0.10.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 982017497206d801ec1b1ed7f9cfcbc27584d6fcd152127b866d6fd904ba6222
MD5 17547cfd24dbe1657dc91fe2f09d71be
BLAKE2b-256 3c3b93827fb96d86567df869d8a0fab6dab2eb38a6b9eef31be5a8fc7aa844fb

See more details on using hashes here.

Provenance

File details

Details for the file vegafusion_python_embed-0.10.0-cp37-cp37m-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for vegafusion_python_embed-0.10.0-cp37-cp37m-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 dc4d754ee95125449b34276289f4098903401ac8de32d4e62b1500f78112b5e7
MD5 ec4f6118ff7e7acfeaacfde6e931110d
BLAKE2b-256 fcf270672b6dcf605b23a4a403ed8dd18db9ceb6639bc6723f51ff2f3d33406e

See more details on using hashes here.

Provenance

File details

Details for the file vegafusion_python_embed-0.10.0-cp37-cp37m-macosx_10_7_x86_64.whl.

File metadata

File hashes

Hashes for vegafusion_python_embed-0.10.0-cp37-cp37m-macosx_10_7_x86_64.whl
Algorithm Hash digest
SHA256 3a30c562af1725c424d4384c7e83439c1b206f16b9a00d914efd539d69dc7924
MD5 ada697321c9d93b9c5bf16b364b65453
BLAKE2b-256 62618efdb9108ffdb1fee538aa02e18d33ef5750d3699a0556bd6f62368f8d62

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