Cython wrapper for Auburns' FastNoise Lite.

These details have not been verified by PyPI

Project links

Homepage

GitHub Statistics

View statistics for this project via Libraries.io, or by using our public dataset on Google BigQuery

Project description

Cython wrapper for the FastNoise Lite library

This wraps Auburns' great FastNoise Lite library using Cython for use in Python 3.6+

Installation

This package is available on the Python Package Index both as source and binary distribution for a variety of Python versions and platforms using the following command:

pip install pyfastnoiselite  # On some systems, "pip" has to be replaced by "pip3"

Note:

This wrapper currently lacks the domain warping functionality and documentation. Both are planned to be added in the future.

Project details

These details have not been verified by PyPI

Project links

Homepage

GitHub Statistics

View statistics for this project via Libraries.io, or by using our public dataset on Google BigQuery

Release history Release notifications | RSS feed

This version

0.0.5

Oct 4, 2023

0.0.4

Mar 25, 2021

0.0.3

Sep 21, 2020

0.0.2

Sep 21, 2020

0.0.1

Sep 21, 2020

Download files

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

Source Distribution

pyfastnoiselite-0.0.5.tar.gz (217.3 kB view hashes)

Uploaded Oct 4, 2023 Source

Built Distributions

pyfastnoiselite-0.0.5-cp312-cp312-win_amd64.whl (103.9 kB view hashes)

Uploaded Oct 4, 2023 CPython 3.12 Windows x86-64

pyfastnoiselite-0.0.5-cp312-cp312-musllinux_1_1_x86_64.whl (1.2 MB view hashes)

Uploaded Oct 4, 2023 CPython 3.12 musllinux: musl 1.1+ x86-64

pyfastnoiselite-0.0.5-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (637.3 kB view hashes)

Uploaded Oct 4, 2023 CPython 3.12 manylinux: glibc 2.17+ x86-64

pyfastnoiselite-0.0.5-cp312-cp312-macosx_10_9_x86_64.whl (115.0 kB view hashes)

Uploaded Oct 4, 2023 CPython 3.12 macOS 10.9+ x86-64

pyfastnoiselite-0.0.5-cp311-cp311-win_amd64.whl (104.2 kB view hashes)

Uploaded Oct 4, 2023 CPython 3.11 Windows x86-64

pyfastnoiselite-0.0.5-cp311-cp311-musllinux_1_1_x86_64.whl (1.2 MB view hashes)

Uploaded Oct 4, 2023 CPython 3.11 musllinux: musl 1.1+ x86-64

pyfastnoiselite-0.0.5-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (648.2 kB view hashes)

Uploaded Oct 4, 2023 CPython 3.11 manylinux: glibc 2.17+ x86-64

pyfastnoiselite-0.0.5-cp311-cp311-macosx_10_9_x86_64.whl (115.2 kB view hashes)

Uploaded Oct 4, 2023 CPython 3.11 macOS 10.9+ x86-64

pyfastnoiselite-0.0.5-cp310-cp310-win_amd64.whl (104.1 kB view hashes)

Uploaded Oct 4, 2023 CPython 3.10 Windows x86-64

pyfastnoiselite-0.0.5-cp310-cp310-musllinux_1_1_x86_64.whl (1.2 MB view hashes)

Uploaded Oct 4, 2023 CPython 3.10 musllinux: musl 1.1+ x86-64

pyfastnoiselite-0.0.5-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (605.9 kB view hashes)

Uploaded Oct 4, 2023 CPython 3.10 manylinux: glibc 2.17+ x86-64

pyfastnoiselite-0.0.5-cp310-cp310-macosx_10_9_x86_64.whl (115.0 kB view hashes)

Uploaded Oct 4, 2023 CPython 3.10 macOS 10.9+ x86-64

pyfastnoiselite-0.0.5-cp39-cp39-win_amd64.whl (104.7 kB view hashes)

Uploaded Oct 4, 2023 CPython 3.9 Windows x86-64

pyfastnoiselite-0.0.5-cp39-cp39-musllinux_1_1_x86_64.whl (1.2 MB view hashes)

Uploaded Oct 4, 2023 CPython 3.9 musllinux: musl 1.1+ x86-64

pyfastnoiselite-0.0.5-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (608.3 kB view hashes)

Uploaded Oct 4, 2023 CPython 3.9 manylinux: glibc 2.17+ x86-64

pyfastnoiselite-0.0.5-cp39-cp39-macosx_10_9_x86_64.whl (115.6 kB view hashes)

Uploaded Oct 4, 2023 CPython 3.9 macOS 10.9+ x86-64

pyfastnoiselite-0.0.5-cp38-cp38-win_amd64.whl (104.7 kB view hashes)

Uploaded Oct 4, 2023 CPython 3.8 Windows x86-64

pyfastnoiselite-0.0.5-cp38-cp38-musllinux_1_1_x86_64.whl (1.2 MB view hashes)

Uploaded Oct 4, 2023 CPython 3.8 musllinux: musl 1.1+ x86-64

pyfastnoiselite-0.0.5-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (609.6 kB view hashes)

Uploaded Oct 4, 2023 CPython 3.8 manylinux: glibc 2.17+ x86-64

pyfastnoiselite-0.0.5-cp38-cp38-macosx_10_9_x86_64.whl (115.8 kB view hashes)

Uploaded Oct 4, 2023 CPython 3.8 macOS 10.9+ x86-64

pyfastnoiselite-0.0.5-cp37-cp37m-win_amd64.whl (104.4 kB view hashes)

Uploaded Oct 4, 2023 CPython 3.7m Windows x86-64

pyfastnoiselite-0.0.5-cp37-cp37m-musllinux_1_1_x86_64.whl (1.1 MB view hashes)

Uploaded Oct 4, 2023 CPython 3.7m musllinux: musl 1.1+ x86-64

pyfastnoiselite-0.0.5-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (578.9 kB view hashes)

Uploaded Oct 4, 2023 CPython 3.7m manylinux: glibc 2.17+ x86-64

pyfastnoiselite-0.0.5-cp37-cp37m-macosx_10_9_x86_64.whl (115.3 kB view hashes)

Uploaded Oct 4, 2023 CPython 3.7m macOS 10.9+ x86-64

pyfastnoiselite-0.0.5-cp36-cp36m-win_amd64.whl (117.4 kB view hashes)

Uploaded Oct 4, 2023 CPython 3.6m Windows x86-64

pyfastnoiselite-0.0.5-cp36-cp36m-musllinux_1_1_x86_64.whl (1.1 MB view hashes)

Uploaded Oct 4, 2023 CPython 3.6m musllinux: musl 1.1+ x86-64

pyfastnoiselite-0.0.5-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (571.3 kB view hashes)

Uploaded Oct 4, 2023 CPython 3.6m manylinux: glibc 2.17+ x86-64

pyfastnoiselite-0.0.5-cp36-cp36m-macosx_10_9_x86_64.whl (113.1 kB view hashes)

Uploaded Oct 4, 2023 CPython 3.6m macOS 10.9+ x86-64

Hashes for pyfastnoiselite-0.0.5.tar.gz

Hashes for pyfastnoiselite-0.0.5.tar.gz
Algorithm	Hash digest
SHA256	`1e2835087b978475be6a412e76c2fabc25039d1089579cd88d1c85ca6cf9d114`
MD5	`ba9db6f4c29f9e30e829b7170bdaea39`
BLAKE2b-256	`f92ec975e8f5a1a5fa598b3eb4e64e2e7ab0fc8049c08811f16ef6bfd9696beb`

Hashes for pyfastnoiselite-0.0.5-cp312-cp312-win_amd64.whl

Hashes for pyfastnoiselite-0.0.5-cp312-cp312-win_amd64.whl
Algorithm	Hash digest
SHA256	`fa80cee0e9ec7739214ae46e9d77b485205854b8f1b757f0ba30fa0f377ac38a`
MD5	`4209b6302f2daf7be16bf7f5dcdcbdcb`
BLAKE2b-256	`7eaafa4419986acac7d8517112bf17b26225ba0b2f95740169f742f5c24aa3c1`

Hashes for pyfastnoiselite-0.0.5-cp312-cp312-musllinux_1_1_x86_64.whl

Hashes for pyfastnoiselite-0.0.5-cp312-cp312-musllinux_1_1_x86_64.whl
Algorithm	Hash digest
SHA256	`7bec38752a231c376f7185978cd964a1be8030fe0d24388c55dd6c5b4c6f229e`
MD5	`8ad8699542343fca046e2e0964064d26`
BLAKE2b-256	`64b5feee529814c10e5996adb4dcb5a9c6888ebdd7603036dcb53462470e4625`

Hashes for pyfastnoiselite-0.0.5-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Hashes for pyfastnoiselite-0.0.5-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm	Hash digest
SHA256	`5b8785ad451d12bb85a35d3973b3647ac2202f65e07d0e892ce133f0c9360e59`
MD5	`72dc7074c679afecc1fa80f23033b42c`
BLAKE2b-256	`2b2229aaf09d6d13ae4d7becca18c95439c35ce50b19dba3077656702242fa3e`

Hashes for pyfastnoiselite-0.0.5-cp312-cp312-macosx_10_9_x86_64.whl

Hashes for pyfastnoiselite-0.0.5-cp312-cp312-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`75b159ed11b25495f742b2bd68420f4c71ca0c56c14452cf946e35387e9634df`
MD5	`03fef531e70818c911c8577573c5af45`
BLAKE2b-256	`5bb14238e7e28fea7d603183c19c98f6b7a5dce9d0faf1e9ab1896af0e58753b`

Hashes for pyfastnoiselite-0.0.5-cp311-cp311-win_amd64.whl

Hashes for pyfastnoiselite-0.0.5-cp311-cp311-win_amd64.whl
Algorithm	Hash digest
SHA256	`39e73a6190766f48f86287f239eee548f468181c1322093545395130cd24cf49`
MD5	`9f3ed5890210e4108769635945c709bf`
BLAKE2b-256	`56e5a6e440c8abfa446ade0e017320e67087700cd108c3fcb91f7186199d7322`

Hashes for pyfastnoiselite-0.0.5-cp311-cp311-musllinux_1_1_x86_64.whl

Hashes for pyfastnoiselite-0.0.5-cp311-cp311-musllinux_1_1_x86_64.whl
Algorithm	Hash digest
SHA256	`ea86584447fa29014114701c0be7da39be02822c0153b3d6981344f36b3ea5ce`
MD5	`ae155a2d10ea6a44573205617f5a205a`
BLAKE2b-256	`8ff983cab1575c5e2737b6f1d97c7bc431975e9c84f0841648961ece7df99b55`

Hashes for pyfastnoiselite-0.0.5-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Hashes for pyfastnoiselite-0.0.5-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm	Hash digest
SHA256	`7a90a27c5aca06eaf9b4d4b6a1ea393c7e2bb42909b23d969d29696d7e15b09c`
MD5	`ba24a3f585234fcfe74d625a7e7627b2`
BLAKE2b-256	`5628ed671f7aafbeecc390d8e7b7a46d8ae34ba35286bb02e7f074a9b5519c6a`

Hashes for pyfastnoiselite-0.0.5-cp311-cp311-macosx_10_9_x86_64.whl

Hashes for pyfastnoiselite-0.0.5-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`efdc1b602208271f82be26532e78947aa8ea748f18e3deec4303fe94c1270d39`
MD5	`9dcf71867e75995c435103d7fd830406`
BLAKE2b-256	`37d25f374b383701cf723839f229f35f8c250a295d50d2050c8fb632a5fa8761`

Hashes for pyfastnoiselite-0.0.5-cp310-cp310-win_amd64.whl

Hashes for pyfastnoiselite-0.0.5-cp310-cp310-win_amd64.whl
Algorithm	Hash digest
SHA256	`a70986625c736480a506f32b15a1007b1ed12d4fa9499bd13c3b667583a26ee0`
MD5	`a821caa3622631dbf21fc646290d8df9`
BLAKE2b-256	`58d4bc952c76d01783f3f623a2e1b68c9937e82209599c96568e0b1bd23c0e4a`

Hashes for pyfastnoiselite-0.0.5-cp310-cp310-musllinux_1_1_x86_64.whl

Hashes for pyfastnoiselite-0.0.5-cp310-cp310-musllinux_1_1_x86_64.whl
Algorithm	Hash digest
SHA256	`2550b4766bcc420fffdbd55c83cb2ec5049b597739f2b9c0d066a86188eb9077`
MD5	`4be0266e2a154d9dbb0864380468a4c4`
BLAKE2b-256	`535d4ce2da86150ef5a7ec0b95295ba891a9737f0c8fa6f5555e24ea3f6b34b5`

Hashes for pyfastnoiselite-0.0.5-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Hashes for pyfastnoiselite-0.0.5-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm	Hash digest
SHA256	`5f35269fb75a5c5cab0697318d5f8c0159d0187281c6c402b5a19351ef6ec817`
MD5	`6917060b5a8e9bccce662c86a1dd392e`
BLAKE2b-256	`9fec61ef79c7a7baeda9d67a2e27714c5b6cab679a58a557734ac7e21880273a`

Hashes for pyfastnoiselite-0.0.5-cp310-cp310-macosx_10_9_x86_64.whl

Hashes for pyfastnoiselite-0.0.5-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`590093b52b2f3ba8df08467850eaf0ee59509a667974e2e71b6881cc7f5a3d88`
MD5	`45333291163083746c8e269f1f7eda46`
BLAKE2b-256	`6de668fd4e179cb41d4d44dfea1c349124ed02277a74149df542bb70e3e5693f`

Hashes for pyfastnoiselite-0.0.5-cp39-cp39-win_amd64.whl

Hashes for pyfastnoiselite-0.0.5-cp39-cp39-win_amd64.whl
Algorithm	Hash digest
SHA256	`9e666722fd047d398c981d81a5329d96a20175b44a1e363a2a9a28138d3c7ad9`
MD5	`e9e0bbf58a6fbca8a5d404793f8ffb94`
BLAKE2b-256	`9e3930a195533b0adc769cfa633fa10070ccca5a844c96c287dc7bbb4bdc2fdf`

Hashes for pyfastnoiselite-0.0.5-cp39-cp39-musllinux_1_1_x86_64.whl

Hashes for pyfastnoiselite-0.0.5-cp39-cp39-musllinux_1_1_x86_64.whl
Algorithm	Hash digest
SHA256	`a2d4a600793f94d9f6759e32b5839bd096800d5275bb69a5eda36f9545d8bf8c`
MD5	`6b11f53582c4294ea68543bd90df014f`
BLAKE2b-256	`ce3683db5f2bb121ea0ed6499bafe512ea47ebe3314fbfe9348664798104c6dd`

Hashes for pyfastnoiselite-0.0.5-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Hashes for pyfastnoiselite-0.0.5-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm	Hash digest
SHA256	`2900dbeabacec92a493ce9bbce9e184bf252a4b60ec0f94e65b0273ec4a17b57`
MD5	`71288ae87d4aec0acc8c2829a7d489b4`
BLAKE2b-256	`08f46c1a97e001a71ff2119dc9b1f5fe360409f2844452dd396bb213b895f23f`

Hashes for pyfastnoiselite-0.0.5-cp39-cp39-macosx_10_9_x86_64.whl

Hashes for pyfastnoiselite-0.0.5-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`cc2aa72a897fff8feea42540bc9eb892062ee1e60ce2cfc33a7ce93a0063e0eb`
MD5	`ad77e604723255c22c3a4aa095d6e856`
BLAKE2b-256	`3bbd1d5cde623576eef1eaaa1f06b98117876285350f54fd8a60efb07fb5d797`

Hashes for pyfastnoiselite-0.0.5-cp38-cp38-win_amd64.whl

Hashes for pyfastnoiselite-0.0.5-cp38-cp38-win_amd64.whl
Algorithm	Hash digest
SHA256	`01a803a1b020bc5e3eea3e832474d3304804d41f612ee2393291d8bf42c3d06d`
MD5	`e25c5139391505bc2a24e6be95986af2`
BLAKE2b-256	`f494441564a2a39b7972091117c8e63d378f44470b123a187b9fe507b63084d9`

Hashes for pyfastnoiselite-0.0.5-cp38-cp38-musllinux_1_1_x86_64.whl

Hashes for pyfastnoiselite-0.0.5-cp38-cp38-musllinux_1_1_x86_64.whl
Algorithm	Hash digest
SHA256	`427009aa3b57af2e6f7be0f756682023cc1ac8258d0f9f2562e5011b4d9fa9c4`
MD5	`520c520364b4b50315ac4e5e25932a2a`
BLAKE2b-256	`2d66f0b66732a394f9a0d82d06258de409215ab502664a70f55e8d8e9fdb9260`

Hashes for pyfastnoiselite-0.0.5-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Hashes for pyfastnoiselite-0.0.5-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm	Hash digest
SHA256	`dc88b7190a3d9a1a5ff6e767223786c9e660ff89f158c7756c24fdc3c88e608f`
MD5	`37c8a1c7867bcc8ced36c0ecd3e350eb`
BLAKE2b-256	`23220c5f756f16662ef1e3a22e4d59c142aeac17bc5721fe6c8d21338dec3c93`

Hashes for pyfastnoiselite-0.0.5-cp38-cp38-macosx_10_9_x86_64.whl

Hashes for pyfastnoiselite-0.0.5-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`f1adfed12c48886fd5e7939da38f6ccb982a61c1adec7fe1ffe177c754b4cf05`
MD5	`81b84f85934c9815c5e802b83dc49936`
BLAKE2b-256	`9f8db902ead18cd7734c7a3965b7b9df60686c6f966bcc68c7572124b48d3ac2`

Hashes for pyfastnoiselite-0.0.5-cp37-cp37m-win_amd64.whl

Hashes for pyfastnoiselite-0.0.5-cp37-cp37m-win_amd64.whl
Algorithm	Hash digest
SHA256	`0a0016ece3edd798566811b26c5ef8d8911526df4f039e44dfcc0946edf8ceb8`
MD5	`2b15a470eeec4b088318ab7c936c81bd`
BLAKE2b-256	`c87d5f42f7eb5ce454f9a04d0e81a07f6cb41e285fb6e95ffad24b302f7adf27`

Hashes for pyfastnoiselite-0.0.5-cp37-cp37m-musllinux_1_1_x86_64.whl

Hashes for pyfastnoiselite-0.0.5-cp37-cp37m-musllinux_1_1_x86_64.whl
Algorithm	Hash digest
SHA256	`dd24f5d6e9870a6cddb92a8df314afb9d95a991fc2ed3c3d5af3817d40f7a7b6`
MD5	`1845327903a8fbc00274783b3d4dd7ca`
BLAKE2b-256	`231229b7356c693b58572a94a324a4d95449d4ad43e567db9b5439ba93011194`

Hashes for pyfastnoiselite-0.0.5-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Hashes for pyfastnoiselite-0.0.5-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm	Hash digest
SHA256	`ceadd927e1e6a05c02c9d3f50bd24c004dc71aa99f7dfa3c6ab63c535bb1d673`
MD5	`d2f58a9e1d71f10d0d12c8aa73f4cf8a`
BLAKE2b-256	`343bf16386c721b11c0afa7388f764bf3ba2c5054f355968aa5837bbec40af50`

Hashes for pyfastnoiselite-0.0.5-cp37-cp37m-macosx_10_9_x86_64.whl

Hashes for pyfastnoiselite-0.0.5-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`e8e17385486d64a483821b86f58211779b088e427677b9ffb2d0d08b57affb40`
MD5	`ec33b9abad831f45ac0f620fa781b520`
BLAKE2b-256	`706867d1c64ec2c2b77ff96b768b8f039fae2fca2e7c9cd73844aa387192bb71`

Hashes for pyfastnoiselite-0.0.5-cp36-cp36m-win_amd64.whl

Hashes for pyfastnoiselite-0.0.5-cp36-cp36m-win_amd64.whl
Algorithm	Hash digest
SHA256	`302a974c4f8639d53c522acacb3471a2c47335a09fef2f0425e1b362928b2d98`
MD5	`759ad1fa00c31e4317dea3199d33ad20`
BLAKE2b-256	`e815b35c6424c97e70654812cbbe6620482b7fb49334ef7c99aafce01e89f4c4`

Hashes for pyfastnoiselite-0.0.5-cp36-cp36m-musllinux_1_1_x86_64.whl

Hashes for pyfastnoiselite-0.0.5-cp36-cp36m-musllinux_1_1_x86_64.whl
Algorithm	Hash digest
SHA256	`4fca3c8e9484800eaeea0fb500c7d77bb3686ad833061eb6db520ec23a49c847`
MD5	`106024f5311af6065030ecb1b3c230c3`
BLAKE2b-256	`cca2d7be491c74b67039d26d2b448969b7e687eeaaa42fdc952546a44ecfa3d5`

Hashes for pyfastnoiselite-0.0.5-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Hashes for pyfastnoiselite-0.0.5-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm	Hash digest
SHA256	`bebd583767d13fc1d6808843858b9a6458d53be3cd1232e62d3ff07c71b900a2`
MD5	`994d8fff1930d86ba785a11f62849dd3`
BLAKE2b-256	`e0ac4fcbfc5fe4c953175112475146a4a4e7f0e4ff681e8658954ceb5b39286b`

Hashes for pyfastnoiselite-0.0.5-cp36-cp36m-macosx_10_9_x86_64.whl

Hashes for pyfastnoiselite-0.0.5-cp36-cp36m-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`67801e0bb112fbca03f4b507c4ef8171e54eea8dcd65a867c8514fb3ecf71263`
MD5	`51a336f478ee6351cfe664ce8cc2aa6b`
BLAKE2b-256	`8a10981b49b1be1f36961062ced604a4dcdd3fd70718922cbf55055fad6cf90a`