Skip to main content

No project description provided

Project description

Rule30

Installation

pip install rule30py

Usage

from rule30 import random, Rule30Random

print(random())

# to use the Psuedo-Random Number Generator
rng = Rule30Random()
print(rng.random())
print(rng.getrandbits(8))
# all the methods of random.Random are available, such as:
print(rng.randint(0, 100))
print(rng.uniform(0, 1))
print(rng.choice(range(10))
print(rng.sample(range(10), 3))

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

rule30py-0.2.1.tar.gz (16.8 kB view details)

Uploaded Source

Built Distributions

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

rule30py-0.2.1-cp39-abi3-win_amd64.whl (126.2 kB view details)

Uploaded CPython 3.9+Windows x86-64

rule30py-0.2.1-cp39-abi3-win32.whl (120.5 kB view details)

Uploaded CPython 3.9+Windows x86

rule30py-0.2.1-cp39-abi3-musllinux_1_2_x86_64.whl (430.8 kB view details)

Uploaded CPython 3.9+musllinux: musl 1.2+ x86-64

rule30py-0.2.1-cp39-abi3-musllinux_1_2_i686.whl (456.7 kB view details)

Uploaded CPython 3.9+musllinux: musl 1.2+ i686

rule30py-0.2.1-cp39-abi3-musllinux_1_2_armv7l.whl (528.6 kB view details)

Uploaded CPython 3.9+musllinux: musl 1.2+ ARMv7l

rule30py-0.2.1-cp39-abi3-musllinux_1_2_aarch64.whl (437.2 kB view details)

Uploaded CPython 3.9+musllinux: musl 1.2+ ARM64

rule30py-0.2.1-cp39-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (263.7 kB view details)

Uploaded CPython 3.9+manylinux: glibc 2.17+ x86-64

rule30py-0.2.1-cp39-abi3-manylinux_2_17_s390x.manylinux2014_s390x.whl (302.7 kB view details)

Uploaded CPython 3.9+manylinux: glibc 2.17+ s390x

rule30py-0.2.1-cp39-abi3-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl (321.6 kB view details)

Uploaded CPython 3.9+manylinux: glibc 2.17+ ppc64le

rule30py-0.2.1-cp39-abi3-manylinux_2_17_armv7l.manylinux2014_armv7l.whl (269.7 kB view details)

Uploaded CPython 3.9+manylinux: glibc 2.17+ ARMv7l

rule30py-0.2.1-cp39-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (263.0 kB view details)

Uploaded CPython 3.9+manylinux: glibc 2.17+ ARM64

rule30py-0.2.1-cp39-abi3-manylinux_2_5_i686.manylinux1_i686.whl (279.6 kB view details)

Uploaded CPython 3.9+manylinux: glibc 2.5+ i686

rule30py-0.2.1-cp39-abi3-macosx_11_0_arm64.whl (231.0 kB view details)

Uploaded CPython 3.9+macOS 11.0+ ARM64

rule30py-0.2.1-cp39-abi3-macosx_10_12_x86_64.whl (235.6 kB view details)

Uploaded CPython 3.9+macOS 10.12+ x86-64

File details

Details for the file rule30py-0.2.1.tar.gz.

File metadata

  • Download URL: rule30py-0.2.1.tar.gz
  • Upload date:
  • Size: 16.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: maturin/1.8.2

File hashes

Hashes for rule30py-0.2.1.tar.gz
Algorithm Hash digest
SHA256 e3e32cc7f2323c504b8b3c381ddf8401d0a818d44b8562cb13d0fae952d8e4ef
MD5 dee5c978094397dd736b0bf878f5d1f1
BLAKE2b-256 5aa346ce10a1a524b38b5813d4513c5e93c946223e0e9271f4d66ea57aa748f9

See more details on using hashes here.

File details

Details for the file rule30py-0.2.1-cp39-abi3-win_amd64.whl.

File metadata

  • Download URL: rule30py-0.2.1-cp39-abi3-win_amd64.whl
  • Upload date:
  • Size: 126.2 kB
  • Tags: CPython 3.9+, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: maturin/1.8.2

File hashes

Hashes for rule30py-0.2.1-cp39-abi3-win_amd64.whl
Algorithm Hash digest
SHA256 a7dce0140164a8e3f6d180bd76114445d317c6b127ab098eb8d2a3b2620da2fc
MD5 717196b7692d2fc6d2dcf09a5ce6e92e
BLAKE2b-256 3d5e19f347846faf109efe1d983ffd857bd80c56e16488e108afe639b159ca09

See more details on using hashes here.

File details

Details for the file rule30py-0.2.1-cp39-abi3-win32.whl.

File metadata

  • Download URL: rule30py-0.2.1-cp39-abi3-win32.whl
  • Upload date:
  • Size: 120.5 kB
  • Tags: CPython 3.9+, Windows x86
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: maturin/1.8.2

File hashes

Hashes for rule30py-0.2.1-cp39-abi3-win32.whl
Algorithm Hash digest
SHA256 0fb9171375978a1559c18bf45ebc594761c4f51daa5066cb421efd1a598ea93e
MD5 09f03afe868ec6d93af552fc73bac854
BLAKE2b-256 f92d127a808673a98612a470a92cb7395729840515c97335cd43b36158c2be6e

See more details on using hashes here.

File details

Details for the file rule30py-0.2.1-cp39-abi3-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for rule30py-0.2.1-cp39-abi3-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 7222eae47d1b75f8c184fef0c35c5e77c9516cae5f253de37a17e7657a03b4fb
MD5 1e70af80b8bb12cf67b5af41660f18da
BLAKE2b-256 8ef4118fd47c2e0d94a62491c35b6447722bbd8a4bef903154cb044e113aa0d3

See more details on using hashes here.

File details

Details for the file rule30py-0.2.1-cp39-abi3-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for rule30py-0.2.1-cp39-abi3-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 7929d06d9031c25bfa4a0ca12a6f4ad3e7cf59d10654531e96c2f7bbcd3f4f58
MD5 e3b7d1199965b4aba6e0ad198c26ed18
BLAKE2b-256 6fd79f8871aa42a495ffd3040bfefe562e7bf5906441812226fc6eff4dab7fa4

See more details on using hashes here.

File details

Details for the file rule30py-0.2.1-cp39-abi3-musllinux_1_2_armv7l.whl.

File metadata

File hashes

Hashes for rule30py-0.2.1-cp39-abi3-musllinux_1_2_armv7l.whl
Algorithm Hash digest
SHA256 504437d949b846ec8c4c45b49f102f64023d107b9f14189d5742c5132f5a9049
MD5 d440ea2ff5c8507aa6245916f05fe1ab
BLAKE2b-256 3c76a3ad36f8f54283d44a837bfa61774a8f3acf6b988cd48acb011d45faefb2

See more details on using hashes here.

File details

Details for the file rule30py-0.2.1-cp39-abi3-musllinux_1_2_aarch64.whl.

File metadata

File hashes

Hashes for rule30py-0.2.1-cp39-abi3-musllinux_1_2_aarch64.whl
Algorithm Hash digest
SHA256 126cf2417a55e81e743a517412e5c7df66bf0e878ed58bd7117ff0f90abf052c
MD5 7079142981d68bfda1503cbc5a003a4b
BLAKE2b-256 9d27c91ed2a97d30686834f98792cc192c8618c6ca20b68e969a8b5fe98e7aa0

See more details on using hashes here.

File details

Details for the file rule30py-0.2.1-cp39-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for rule30py-0.2.1-cp39-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 a5612253a0611c76a1542ec8082e290640ebb112a375bb739ea0f41615c1eae9
MD5 021dabaf4943e162caa2ace300f741c4
BLAKE2b-256 8e5823b1abf7bc4ee010be68b11a4a0ec2e62c8338f5afe87fac3b8048342350

See more details on using hashes here.

File details

Details for the file rule30py-0.2.1-cp39-abi3-manylinux_2_17_s390x.manylinux2014_s390x.whl.

File metadata

File hashes

Hashes for rule30py-0.2.1-cp39-abi3-manylinux_2_17_s390x.manylinux2014_s390x.whl
Algorithm Hash digest
SHA256 ef4933053c2f0476de23c9814d4ab05b272af26d19364b488abcb6e2c9cb426f
MD5 18d13944e3ea798f5022600c92b0d421
BLAKE2b-256 1a8c7cbdecc57fe8f8182821b6e17f9bb7def1e6bb93c460d6de722922de0cee

See more details on using hashes here.

File details

Details for the file rule30py-0.2.1-cp39-abi3-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl.

File metadata

File hashes

Hashes for rule30py-0.2.1-cp39-abi3-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl
Algorithm Hash digest
SHA256 060c6b97c56bf5c4ec9cba5e78785263950289ec5128b3569a48fcce415f3093
MD5 15df011cccaeb9d5dafd30187d31f26b
BLAKE2b-256 fc06069754932389358f9e3d5e68edb320c942cc3e799743cc36837fbb1e090e

See more details on using hashes here.

File details

Details for the file rule30py-0.2.1-cp39-abi3-manylinux_2_17_armv7l.manylinux2014_armv7l.whl.

File metadata

File hashes

Hashes for rule30py-0.2.1-cp39-abi3-manylinux_2_17_armv7l.manylinux2014_armv7l.whl
Algorithm Hash digest
SHA256 99f38626b2a8ae70494cd52dd8f0c838426f7d1b37ef76aecbf89abb80a8a74b
MD5 5b42369784a974e0c84a1f89501442bf
BLAKE2b-256 6dca2c32df94c7bc669aae73df5d64dc0f4c541f2dabb51215fa048e3e24d501

See more details on using hashes here.

File details

Details for the file rule30py-0.2.1-cp39-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for rule30py-0.2.1-cp39-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 846968d1105e7b6bfd304ce4782b6a42dcaf90ad62ae0ccedeb872153c67da02
MD5 5621cbb1d5ffed2a1450cc40285388da
BLAKE2b-256 9c213834ed50f934a4fbabc80ee23e68be515394542410adfc029e5052e99e2f

See more details on using hashes here.

File details

Details for the file rule30py-0.2.1-cp39-abi3-manylinux_2_5_i686.manylinux1_i686.whl.

File metadata

File hashes

Hashes for rule30py-0.2.1-cp39-abi3-manylinux_2_5_i686.manylinux1_i686.whl
Algorithm Hash digest
SHA256 27792c2b0cacc7527ab8b72861850cf5be82de1aef6cc17449888f7724a6fdab
MD5 e823a070b0f00a99203d090e9dc9fa8a
BLAKE2b-256 8ece29d483efed1942dd80d9bc10c0bb4c60e3075178dc78a05c251f194c21db

See more details on using hashes here.

File details

Details for the file rule30py-0.2.1-cp39-abi3-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for rule30py-0.2.1-cp39-abi3-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 7f2e8bed15ab4b326f9e940fbfc2f25e81744218e87aae3c61f7d2e7dab30d22
MD5 646f85989f78caf6517af7a345697da3
BLAKE2b-256 24394c1bf4c9eca5e2812b616b4b9ce19ec9b6deb495d7856b38fe75e2c09059

See more details on using hashes here.

File details

Details for the file rule30py-0.2.1-cp39-abi3-macosx_10_12_x86_64.whl.

File metadata

File hashes

Hashes for rule30py-0.2.1-cp39-abi3-macosx_10_12_x86_64.whl
Algorithm Hash digest
SHA256 7370b5d4955b7931879e0a9195e81df2bdd7738f789c21f154dcba368dd99e66
MD5 a97470e7c50b31ed8e8cf38115c63d00
BLAKE2b-256 bfb8ba30e52bc48f5c45054161bc1f084897dd3b5ac1b637f70ff72ac0a52fa0

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