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

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for luisbernardos from gravatar.com luisbernardos

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: GNU LESSER GENERAL PUBLIC LICENSE
  • Author: Luis Bernardos
  • Requires: Python >=3.8
  • Provides-Extra: test , dev , docs
Classifiers
Report project as malware

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

Verified details

These details have been verified by PyPI
Maintainers
Avatar for luisbernardos from gravatar.com luisbernardos

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: GNU LESSER GENERAL PUBLIC LICENSE
  • Author: Luis Bernardos
  • Requires: Python >=3.8
  • Provides-Extra: test , dev , docs
Classifiers

Release history Release notifications | RSS feed

1.1.4

1.1.3

1.1.2

1.1.1

1.1.0

This version

1.0.2

1.0.1

1.0.0

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-1.0.2-cp313-cp313-win_amd64.whl (3.1 MB view details)

Uploaded CPython 3.13Windows x86-64

noder-1.0.2-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (6.1 MB view details)

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

noder-1.0.2-cp313-cp313-macosx_15_0_arm64.whl (3.1 MB view details)

Uploaded CPython 3.13macOS 15.0+ ARM64

noder-1.0.2-cp312-cp312-win_amd64.whl (3.1 MB view details)

Uploaded CPython 3.12Windows x86-64

noder-1.0.2-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (6.1 MB view details)

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

noder-1.0.2-cp312-cp312-macosx_15_0_arm64.whl (3.1 MB view details)

Uploaded CPython 3.12macOS 15.0+ ARM64

noder-1.0.2-cp311-cp311-win_amd64.whl (3.1 MB view details)

Uploaded CPython 3.11Windows x86-64

noder-1.0.2-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (6.1 MB view details)

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

noder-1.0.2-cp311-cp311-macosx_15_0_arm64.whl (3.2 MB view details)

Uploaded CPython 3.11macOS 15.0+ ARM64

noder-1.0.2-cp310-cp310-win_amd64.whl (3.1 MB view details)

Uploaded CPython 3.10Windows x86-64

noder-1.0.2-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (6.1 MB view details)

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

noder-1.0.2-cp310-cp310-macosx_15_0_arm64.whl (3.1 MB view details)

Uploaded CPython 3.10macOS 15.0+ ARM64

noder-1.0.2-cp39-cp39-win_amd64.whl (3.2 MB view details)

Uploaded CPython 3.9Windows x86-64

noder-1.0.2-cp39-cp39-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (6.1 MB view details)

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

noder-1.0.2-cp39-cp39-macosx_15_0_arm64.whl (3.1 MB view details)

Uploaded CPython 3.9macOS 15.0+ ARM64

noder-1.0.2-cp38-cp38-win_amd64.whl (3.1 MB view details)

Uploaded CPython 3.8Windows x86-64

noder-1.0.2-cp38-cp38-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (6.1 MB view details)

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

noder-1.0.2-cp38-cp38-macosx_15_0_arm64.whl (3.1 MB view details)

Uploaded CPython 3.8macOS 15.0+ ARM64

File details

Details for the file noder-1.0.2-cp313-cp313-win_amd64.whl.

File metadata

  • Download URL: noder-1.0.2-cp313-cp313-win_amd64.whl
  • Upload date:
  • Size: 3.1 MB
  • Tags: CPython 3.13, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.12

File hashes

Hashes for noder-1.0.2-cp313-cp313-win_amd64.whl
Algorithm Hash digest
SHA256 1a17323985609aabe821757452376d85c2253c03763da0edee29569c518517e2
MD5 42e37a03277d80e31f4270302fd5088b
BLAKE2b-256 2b407b9a6af695b4e02c13b983e6aa6f3cd69c47c8852e8b78bb113d9b08f39c

See more details on using hashes here.

File details

Details for the file noder-1.0.2-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for noder-1.0.2-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 f9e1e9cdab1ae88dd02541cc82b24442f57b5b48b6513f106814dc40dc6a69e0
MD5 91aa77f49c0b548d2ec37d3f75f040bc
BLAKE2b-256 97dab14f5c0f88334483b41705a618938e3a6dcab3d93457bb2b6ed0a2cc847c

See more details on using hashes here.

File details

Details for the file noder-1.0.2-cp313-cp313-macosx_15_0_arm64.whl.

File metadata

File hashes

Hashes for noder-1.0.2-cp313-cp313-macosx_15_0_arm64.whl
Algorithm Hash digest
SHA256 9d9934562c51a30fad64984b4bf14f8829c76a824ac6219a1ca4348b8efd5dd7
MD5 9eb53f1d306bc3705d184c1ba66aef45
BLAKE2b-256 b2253f0cfd2df7bb9c5e8f05a5c0cb161b7385726330b7a9db2e0d41019a8bf6

See more details on using hashes here.

File details

Details for the file noder-1.0.2-cp312-cp312-win_amd64.whl.

File metadata

  • Download URL: noder-1.0.2-cp312-cp312-win_amd64.whl
  • Upload date:
  • Size: 3.1 MB
  • Tags: CPython 3.12, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.12

File hashes

Hashes for noder-1.0.2-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 c3857b3d82dd815955593576400b8fe5e42289ab6c9065cb5fb5b10f564950a7
MD5 69cb6ebfa3cee72804fab35a2026c30c
BLAKE2b-256 b45f20e6cfbab714244cfefa07d1b3a53f5c8351088c1c3d75231d4a03edd411

See more details on using hashes here.

File details

Details for the file noder-1.0.2-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for noder-1.0.2-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 e71c99a7d1d08cbee1c447731d69b447a3e98235757b8448456a9d632563de0b
MD5 cd4e48956946c56fe77bd69aff2e9b2f
BLAKE2b-256 4c45f414a20809ef08538938644f1f1d774dd7125e09c05cc5c71b256340b439

See more details on using hashes here.

File details

Details for the file noder-1.0.2-cp312-cp312-macosx_15_0_arm64.whl.

File metadata

File hashes

Hashes for noder-1.0.2-cp312-cp312-macosx_15_0_arm64.whl
Algorithm Hash digest
SHA256 3dc7b43783e748bd9ec8152ab97534c0b0188885654fcf9b8b0b9154f5d98341
MD5 79df6b8c5b285021f816db2607f441b7
BLAKE2b-256 8deb087baf9a539cea6aa3e380fc1fbe57c63b2d4e1afa39ebd72b1a997e8f3b

See more details on using hashes here.

File details

Details for the file noder-1.0.2-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: noder-1.0.2-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 3.1 MB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.12

File hashes

Hashes for noder-1.0.2-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 1944af1599233267aca3fb572867e384bb8b8635386abdf4b996f98216b5f061
MD5 028ac990cd27b1caf3397ed0fcbe097e
BLAKE2b-256 adf8f4b1991ab9bbd3fbda36c9ecd54fc9b83ea5d5eaca97bbbf59ab19c278e1

See more details on using hashes here.

File details

Details for the file noder-1.0.2-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for noder-1.0.2-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 f63a324af28e29e2cec98f84b16d1cd2a96dc0abf35c92c0d22c0fd7f16da332
MD5 303a9d8bde6fe6c00dd4f881bc5e91be
BLAKE2b-256 32ff312518274ba26df23fe0d783518382bbcf9c172c4f68e8ff03eefe2cbaad

See more details on using hashes here.

File details

Details for the file noder-1.0.2-cp311-cp311-macosx_15_0_arm64.whl.

File metadata

File hashes

Hashes for noder-1.0.2-cp311-cp311-macosx_15_0_arm64.whl
Algorithm Hash digest
SHA256 abff703e27c68a034f4407ec3e87c284598a5cd3abc41c416be94c0a046ec195
MD5 a4e18c7cef6d3793864a7fd5031710f4
BLAKE2b-256 6acbf46e9f03dd2cb0c5d526b80171b99969da6bc75426cbd7e680061c5fe73b

See more details on using hashes here.

File details

Details for the file noder-1.0.2-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: noder-1.0.2-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 3.1 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.12

File hashes

Hashes for noder-1.0.2-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 c080f91a7de4520c279e0adaa40de545e91080fcefa32725e2a9c1c520ab18b1
MD5 0f4074692f2d29d9d3f61568e3693ad5
BLAKE2b-256 08748d0e282b97b2f433d73add42791cf1ce0280807e8302470c04ea2f36ad13

See more details on using hashes here.

File details

Details for the file noder-1.0.2-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for noder-1.0.2-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 af2c2b487fccae04227fd5531bd46fca4d85370f732ace6595c714e290afc68c
MD5 7412585d72540de4e394ef39852af18c
BLAKE2b-256 ef487e370db81cb08f5307677bc8be4ce563472578448363df88ac4992b2e5bc

See more details on using hashes here.

File details

Details for the file noder-1.0.2-cp310-cp310-macosx_15_0_arm64.whl.

File metadata

File hashes

Hashes for noder-1.0.2-cp310-cp310-macosx_15_0_arm64.whl
Algorithm Hash digest
SHA256 13a1ef39303a1d0ba2446dc50a3ed6b1f1f512c7cc54f3c81b86dcb2b4f39372
MD5 211d41beba7bbc505a716984ebb777fc
BLAKE2b-256 b95025b37263f43441cf66f22a4e5264ca2bbd4a9cbc621c93c81e09ca5d08c0

See more details on using hashes here.

File details

Details for the file noder-1.0.2-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: noder-1.0.2-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 3.2 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.12

File hashes

Hashes for noder-1.0.2-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 bd5dc492dc0216faaa145f49db9f35f2c51f67ab2dbe643812f1f0114d9376ff
MD5 d1796019a07fa75d4dba426868a9b083
BLAKE2b-256 9cc56d54632abab4a2ab9566c1bb3a610149e61cef05b318020279a7d8f87e91

See more details on using hashes here.

File details

Details for the file noder-1.0.2-cp39-cp39-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for noder-1.0.2-cp39-cp39-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 5321eb8982b69eb24fdfbb4b0beb1d24e4e61c1ad5bcf042e5b0bb49766c6a48
MD5 040aa27e2be9759c849e6a55fd90327f
BLAKE2b-256 38e254d2889769f59bbb57f4afd0b904d0659b1092f0bb1a387ea4b9ab7269db

See more details on using hashes here.

File details

Details for the file noder-1.0.2-cp39-cp39-macosx_15_0_arm64.whl.

File metadata

  • Download URL: noder-1.0.2-cp39-cp39-macosx_15_0_arm64.whl
  • Upload date:
  • Size: 3.1 MB
  • Tags: CPython 3.9, macOS 15.0+ ARM64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.12

File hashes

Hashes for noder-1.0.2-cp39-cp39-macosx_15_0_arm64.whl
Algorithm Hash digest
SHA256 a04fb4b508665da6867b950e99c259fa3af5659194d9d1d9491baed694fee45f
MD5 efef284c31d1874320ba50d90831894e
BLAKE2b-256 1a8337564cffd208cc3e86aad7736349767138afd711e32cd4e60c27011a8178

See more details on using hashes here.

File details

Details for the file noder-1.0.2-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: noder-1.0.2-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 3.1 MB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.12

File hashes

Hashes for noder-1.0.2-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 61bd5ec5b5fb1b653f0e8557e90736763baff49c0b03810f8dee0e490b891851
MD5 16d798924917941bae14bbd8c2e1703b
BLAKE2b-256 3f1ab0e347c00c194f7fa93c4ad12f1bfbfb58b1fd48a4537a95baff24a5c480

See more details on using hashes here.

File details

Details for the file noder-1.0.2-cp38-cp38-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for noder-1.0.2-cp38-cp38-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 1e3738ff6fcccdd3be8bf7d0f54b94b1712048c7439502fdfdfbc82602e24688
MD5 e65ff944ada98920e63bc2e250d9d3f5
BLAKE2b-256 fddaa08598c0c3a41d1fd4d9d23fbcf2f0c70186f50c0dfcc363d57ea44a313e

See more details on using hashes here.

File details

Details for the file noder-1.0.2-cp38-cp38-macosx_15_0_arm64.whl.

File metadata

  • Download URL: noder-1.0.2-cp38-cp38-macosx_15_0_arm64.whl
  • Upload date:
  • Size: 3.1 MB
  • Tags: CPython 3.8, macOS 15.0+ ARM64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.12

File hashes

Hashes for noder-1.0.2-cp38-cp38-macosx_15_0_arm64.whl
Algorithm Hash digest
SHA256 2ef37855f0d517b0b9473ab7071a14b545523a4e8c1d98793366ef46e003c205
MD5 5975cba33f8575219a397c2715be8254
BLAKE2b-256 7d3af26909209212829c7b97f3b23f23e998113e835aa7d1beb27c5074d02ea3

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