Skip to content
Conda package using conda-forge

Speed up randint array-bounds via chunking Lemire #485

Sign in to view logs

Speed up randint array-bounds via chunking Lemire

Speed up randint array-bounds via chunking Lemire #485

Triggered via pull request September 4, 2026 13:31
@vlad-perevezentsevvlad-perevezentsev
opened #173
chunk-randint-broadcast-words
Status Success
Total duration 12m 23s
Artifacts 15

conda-package-cf.yml

on: pull_request
Matrix: build_linux
Matrix: build_osx
Matrix: build_windows
Matrix: test_linux
Matrix: test_osx
Matrix: test_windows
Fit to window
Zoom out
Zoom in

Artifacts

Produced during runtime
Name Size Digest
mkl_random Linux Python 3.10
409 KB
sha256:b54d4dee31d61486650059d3983f74f55217639b43b68100753af2bdca1fb7ee
mkl_random Linux Python 3.11
432 KB
sha256:4f4d3effe4eee5fba1275632fff83949f3262e502b5d0f2e84d532a98afac6f0
mkl_random Linux Python 3.12
419 KB
sha256:53a14eeae3fcb0278986f9fd8a2ba72674cb2cae2b705463f0889bd6a8c1b4f0
mkl_random Linux Python 3.13
420 KB
sha256:7cb846d52718025577aba205f8c71f1d49f5e3fa26adf8f581758db6319d2f02
mkl_random Linux Python 3.14
422 KB
sha256:f757fea3bd7702ea6171d6f3fdab1709fc0701b851a7d98865220fc6f69cb68a
mkl_random Windows Python 3.10
337 KB
sha256:a6daf497e61c415950e11ba92bd19e128fb0ad19dc2c896a502f6180c9d6f5c4
mkl_random Windows Python 3.11
361 KB
sha256:3dc7e8fd5ed81cdc64c2248b3dc3c44c26587f3a9da4e29f486620a8d03af280
mkl_random Windows Python 3.12
333 KB
sha256:43e0a1bca0400a02a7da59356b3abf50838206633ef6a92629264f990939f2e6
mkl_random Windows Python 3.13
332 KB
sha256:45e556978207a8739bcc4ee5de9f6abf6467c7e82a81ae37b1fddcfc2989160e
mkl_random Windows Python 3.14
335 KB
sha256:4f9194d4e64cfbc86bfc2ad2b78e938ae68b6a63c2045d195e2c1650756b6b42
mkl_random macOS Python 3.10
357 KB
sha256:893f8e50d56de8ba2c8f30cb9286b4bdc537ea894f611a1e0e7b467e0fe7c488
mkl_random macOS Python 3.11
377 KB
sha256:46c99b745316bfaef5a76532e3f84254c547b285b278771b02e46f6a5cc3359b
mkl_random macOS Python 3.12
366 KB
sha256:d266c7a04ca4515609ebae04e82619a771cea48727f80b8acc13198f7b2024a9
mkl_random macOS Python 3.13
366 KB
sha256:e274ea0795ee6562892168ce44ae4cbe9d12e80929d12f9dffc54e96704f70c6
mkl_random macOS Python 3.14
369 KB
sha256:32283083586314ef02742515e216bdb1404684db9a9aaf12b9b0c7f968329b7f