Skip to main content

A library for efficient large data operations designed for handling arrays hierarchically using an object-oriented approach

Project description

noder

NODER (Node-Oriented Data Extraction & Representation) is a hybrid C++/Python library for hierarchical scientific data handling with NumPy-backed payloads.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

noder-1.1.8-cp313-cp313-win_amd64.whl (4.8 MB view details)

Uploaded CPython 3.13Windows x86-64

noder-1.1.8-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (5.9 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.27+ x86-64manylinux: glibc 2.28+ x86-64

noder-1.1.8-cp313-cp313-macosx_15_0_arm64.whl (2.7 MB view details)

Uploaded CPython 3.13macOS 15.0+ ARM64

noder-1.1.8-cp312-cp312-win_amd64.whl (4.8 MB view details)

Uploaded CPython 3.12Windows x86-64

noder-1.1.8-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (5.9 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.27+ x86-64manylinux: glibc 2.28+ x86-64

noder-1.1.8-cp312-cp312-macosx_15_0_arm64.whl (2.7 MB view details)

Uploaded CPython 3.12macOS 15.0+ ARM64

noder-1.1.8-cp311-cp311-win_amd64.whl (4.8 MB view details)

Uploaded CPython 3.11Windows x86-64

noder-1.1.8-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (5.9 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.27+ x86-64manylinux: glibc 2.28+ x86-64

noder-1.1.8-cp311-cp311-macosx_15_0_arm64.whl (2.7 MB view details)

Uploaded CPython 3.11macOS 15.0+ ARM64

noder-1.1.8-cp310-cp310-win_amd64.whl (4.8 MB view details)

Uploaded CPython 3.10Windows x86-64

noder-1.1.8-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (5.9 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.27+ x86-64manylinux: glibc 2.28+ x86-64

noder-1.1.8-cp310-cp310-macosx_15_0_arm64.whl (2.7 MB view details)

Uploaded CPython 3.10macOS 15.0+ ARM64

noder-1.1.8-cp39-cp39-win_amd64.whl (4.8 MB view details)

Uploaded CPython 3.9Windows x86-64

noder-1.1.8-cp39-cp39-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (5.9 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.27+ x86-64manylinux: glibc 2.28+ x86-64

noder-1.1.8-cp39-cp39-macosx_15_0_arm64.whl (2.7 MB view details)

Uploaded CPython 3.9macOS 15.0+ ARM64

noder-1.1.8-cp38-cp38-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (5.9 MB view details)

Uploaded CPython 3.8manylinux: glibc 2.27+ x86-64manylinux: glibc 2.28+ x86-64

File details

Details for the file noder-1.1.8-cp313-cp313-win_amd64.whl.

File metadata

  • Download URL: noder-1.1.8-cp313-cp313-win_amd64.whl
  • Upload date:
  • Size: 4.8 MB
  • Tags: CPython 3.13, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.13

File hashes

Hashes for noder-1.1.8-cp313-cp313-win_amd64.whl
Algorithm Hash digest
SHA256 a3aa346be7fb561c9d2a5c32de15bd7c49cdc47aaac6e00ae0b4541952ad4eb5
MD5 fadbf40d330ec51cca8d8d609f2b8d49
BLAKE2b-256 b76739d0a8e18f59a8cffdb34ae4a9c1e9b360b85b255bdc5efa63318a888a81

See more details on using hashes here.

File details

Details for the file noder-1.1.8-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for noder-1.1.8-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 839bcd5b1ff6ea597054c18dc36d1f57e859170975f46dfbdf494d369b1e589d
MD5 e2207f96c9040ac52e1b8d5e9c913a88
BLAKE2b-256 25fba70f4b47e529d8ffdb9cbea3cbc62a3ac8cd498b3434d6c452b707da91b8

See more details on using hashes here.

File details

Details for the file noder-1.1.8-cp313-cp313-macosx_15_0_arm64.whl.

File metadata

File hashes

Hashes for noder-1.1.8-cp313-cp313-macosx_15_0_arm64.whl
Algorithm Hash digest
SHA256 b6dd7a1cd741ae5846014de7b290639af9b46f3763fed11b79e238b2e4026b96
MD5 c3c2c2b3d32b3310a0d2124ec22c5ec9
BLAKE2b-256 fe2678e85b3d8709dc4ab7a3292647a4f79dc6405185aa206ead823929e8c446

See more details on using hashes here.

File details

Details for the file noder-1.1.8-cp312-cp312-win_amd64.whl.

File metadata

  • Download URL: noder-1.1.8-cp312-cp312-win_amd64.whl
  • Upload date:
  • Size: 4.8 MB
  • Tags: CPython 3.12, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.13

File hashes

Hashes for noder-1.1.8-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 707290f384397786055928b2f23b5b5239af56114d640f593d7764e20ccfb926
MD5 48aaa3504bb159ef9a4915ed1c41ee8a
BLAKE2b-256 796f87a21136086889b3259d12400a89aa4bac817ecfd21b0cb7e58f04f18689

See more details on using hashes here.

File details

Details for the file noder-1.1.8-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for noder-1.1.8-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 9f59b5f567fb1a1139f1b603bb96e221a5bfdb5a4b971554ccdcef75117f37bb
MD5 ecfc3a9728e1aa47ae9fa3bd897b3250
BLAKE2b-256 880ed05c7514ac6e2f37d91244a4e3d8113825c447536d84064f1943c2a16d2f

See more details on using hashes here.

File details

Details for the file noder-1.1.8-cp312-cp312-macosx_15_0_arm64.whl.

File metadata

File hashes

Hashes for noder-1.1.8-cp312-cp312-macosx_15_0_arm64.whl
Algorithm Hash digest
SHA256 91cc09114d3ecf681107d9d50e8749b58bef0edd0c429d3bfc3dc15da4af9b09
MD5 ccbf64ffe0a68260c42c149a6d744cb1
BLAKE2b-256 504cd08dc7bb0de5da577f96170f7672d9956de3e32a3156b0b562535cd2c21b

See more details on using hashes here.

File details

Details for the file noder-1.1.8-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: noder-1.1.8-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 4.8 MB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.13

File hashes

Hashes for noder-1.1.8-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 5bd96a0425fc8f627d9e26430bac5b5fe2121b1e3116771ce072e747f4ce4b33
MD5 bc39fa0012e04c7981bc4ff24c2040b7
BLAKE2b-256 faee28937052aba3f6e7074b4d0b16f1b4b79e939eed3c740b907e9576e4cfb5

See more details on using hashes here.

File details

Details for the file noder-1.1.8-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for noder-1.1.8-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 aad7de44eb6b13ac948d49a1928e7fbbf640debc239602c433367aa9c4b1c38c
MD5 69a663ea129e40afd7de93bb96af216f
BLAKE2b-256 53e08215b666cae79fc96a53d6299507fbda1c218343520819b8b344fef050b5

See more details on using hashes here.

File details

Details for the file noder-1.1.8-cp311-cp311-macosx_15_0_arm64.whl.

File metadata

File hashes

Hashes for noder-1.1.8-cp311-cp311-macosx_15_0_arm64.whl
Algorithm Hash digest
SHA256 20c773d49350b54c713d325753386b776d76253fa5964e6c64bf846ba5b86ebf
MD5 35133c7967ccfdc2fc4bdea731587e9c
BLAKE2b-256 0a0757c384ea42b17c7d0c1b239df2f258ab639395de2d01f1ee89f6c1558867

See more details on using hashes here.

File details

Details for the file noder-1.1.8-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: noder-1.1.8-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 4.8 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.13

File hashes

Hashes for noder-1.1.8-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 daa60d9bc2da662eaeb121a3f83a43ab2ebb8cd776bb5de9bc41f818a355caef
MD5 65f1e5d2bf2f1c8aeafa0247b42ebdef
BLAKE2b-256 46ad65a2b428815e4c46761ba8c0ae389f4268eb150815a0f518f7492f616473

See more details on using hashes here.

File details

Details for the file noder-1.1.8-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for noder-1.1.8-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 c0ca0f9d5e7b89702fdc8f333a5001aa11c76934537668fd3a0e28e53bafeca5
MD5 204482e926b0e0cbbbdcab89b3322a4c
BLAKE2b-256 02aeaa5a60e9601c8f0e61fc12b8ae8012410d3edd05483b60eb2d2a7d6f8209

See more details on using hashes here.

File details

Details for the file noder-1.1.8-cp310-cp310-macosx_15_0_arm64.whl.

File metadata

File hashes

Hashes for noder-1.1.8-cp310-cp310-macosx_15_0_arm64.whl
Algorithm Hash digest
SHA256 984151321ea6db993c1d5b5890fff5362521ed025b416909eaf62e07a73f4432
MD5 4c223313045ad2421099402388ec6fff
BLAKE2b-256 0f9f7f1ef89fd794a646545ee3484a2e9dfcdcf25f0e52d61bd6849d62442122

See more details on using hashes here.

File details

Details for the file noder-1.1.8-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: noder-1.1.8-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 4.8 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.13

File hashes

Hashes for noder-1.1.8-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 851b231201ae51e92bec1a0aa5c31603fa64656dce33b0c03d8ea8a93cae533e
MD5 c73ffd3e0bde8d3697efc50eb96f0f0c
BLAKE2b-256 92f8bf29f37b7389f78aff59e757b748f9d1a8dfc2886d684dff85b6ef00d0fc

See more details on using hashes here.

File details

Details for the file noder-1.1.8-cp39-cp39-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for noder-1.1.8-cp39-cp39-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 c123c8c71feca459bc332d459a1e9c4db6a4110289f1f28483a12d7d4bd0f135
MD5 50dfc6b0edd3b7567b38093d48d278f1
BLAKE2b-256 a18c7d3e95edbf51e3681b3657b27f439990a9438013014b681d2851eca86903

See more details on using hashes here.

File details

Details for the file noder-1.1.8-cp39-cp39-macosx_15_0_arm64.whl.

File metadata

  • Download URL: noder-1.1.8-cp39-cp39-macosx_15_0_arm64.whl
  • Upload date:
  • Size: 2.7 MB
  • Tags: CPython 3.9, macOS 15.0+ ARM64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.13

File hashes

Hashes for noder-1.1.8-cp39-cp39-macosx_15_0_arm64.whl
Algorithm Hash digest
SHA256 b6c316c92dae76df31925d7fbc774ca7735f7aec7c1583815a5901d4703f8079
MD5 7fbbe58688d64b508b3eb0dfef55dc44
BLAKE2b-256 d92af3f5eb1c62abacce89ec0fbe6ccfa54ba5d5f1caea68e433e2c525d369dd

See more details on using hashes here.

File details

Details for the file noder-1.1.8-cp38-cp38-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for noder-1.1.8-cp38-cp38-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 745c35bc89a6e1bcf29f22ab1014bdd1933b2fe43d20a9871c80f9057d0ec1e0
MD5 c54194c2d705f0473b1eb68ffc1a2be8
BLAKE2b-256 57b74672660be92c58e6d496ba1c748666ed0d5ca4592573bf254d86ea158797

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page