From 24f9327369c7e0f8f7e92b64f541fc9e903ed857 Mon Sep 17 00:00:00 2001 From: Nikita Titov Date: Fri, 2 Aug 2024 20:47:06 +0300 Subject: [PATCH] Bump required CMake version and fix urls (#61) * Bump required CMake version and fix urls * Sync docs version * MNT: Re-rendered with conda-build 24.7.1, conda-smithy 3.37.2, and conda-forge-pinning 2024.08.02.08.34.06 --------- Co-authored-by: conda-forge-webservices[bot] <91080706+conda-forge-webservices[bot]@users.noreply.github.com> --- .azure-pipelines/azure-pipelines-win.yml | 2 +- .scripts/run_osx_build.sh | 2 +- README.md | 6 +++--- build-locally.py | 4 ++-- recipe/meta.yaml | 10 +++++----- 5 files changed, 12 insertions(+), 12 deletions(-) diff --git a/.azure-pipelines/azure-pipelines-win.yml b/.azure-pipelines/azure-pipelines-win.yml index b4ec9c0..c3360e7 100755 --- a/.azure-pipelines/azure-pipelines-win.yml +++ b/.azure-pipelines/azure-pipelines-win.yml @@ -37,7 +37,7 @@ jobs: scriptSource: inline script: | import urllib.request - url = 'https://github.com/conda-forge/miniforge/releases/latest/download/Mambaforge-Windows-x86_64.exe' + url = 'https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-Windows-x86_64.exe' path = r"$(Build.ArtifactStagingDirectory)/Miniforge.exe" urllib.request.urlretrieve(url, path) diff --git a/.scripts/run_osx_build.sh b/.scripts/run_osx_build.sh index ba0c879..420f051 100755 --- a/.scripts/run_osx_build.sh +++ b/.scripts/run_osx_build.sh @@ -11,7 +11,7 @@ MINIFORGE_HOME=${MINIFORGE_HOME:-${HOME}/miniforge3} ( startgroup "Installing a fresh version of Miniforge" ) 2> /dev/null MINIFORGE_URL="https://github.com/conda-forge/miniforge/releases/latest/download" -MINIFORGE_FILE="Mambaforge-MacOSX-$(uname -m).sh" +MINIFORGE_FILE="Miniforge3-MacOSX-$(uname -m).sh" curl -L -O "${MINIFORGE_URL}/${MINIFORGE_FILE}" rm -rf ${MINIFORGE_HOME} bash $MINIFORGE_FILE -b -p ${MINIFORGE_HOME} diff --git a/README.md b/README.md index 6e23233..c290b3b 100644 --- a/README.md +++ b/README.md @@ -3,15 +3,15 @@ About lightgbm-feedstock Feedstock license: [BSD-3-Clause](https://github.com/conda-forge/lightgbm-feedstock/blob/main/LICENSE.txt) -Home: https://github.com/Microsoft/LightGBM +Home: https://github.com/microsoft/LightGBM Package license: MIT Summary: LightGBM is a gradient boosting framework that uses tree based learning algorithms. -Development: https://github.com/Microsoft/LightGBM +Development: https://github.com/microsoft/LightGBM -Documentation: http://lightgbm.readthedocs.io/en/latest/ +Documentation: https://lightgbm.readthedocs.io/en/v4.5.0/ A fast, distributed, high performance gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks. diff --git a/build-locally.py b/build-locally.py index e0d408d..d78427b 100755 --- a/build-locally.py +++ b/build-locally.py @@ -3,11 +3,11 @@ # This file has been generated by conda-smithy in order to build the recipe # locally. # -import os import glob +import os +import platform import subprocess from argparse import ArgumentParser -import platform def setup_environment(ns): diff --git a/recipe/meta.yaml b/recipe/meta.yaml index 0d2798d..be3335c 100644 --- a/recipe/meta.yaml +++ b/recipe/meta.yaml @@ -12,7 +12,7 @@ source: - boost_shared.diff build: - number: 0 + number: 1 string: cuda_py{{ PY_VER }}h{{ PKG_HASH }}_{{ PKG_BUILDNUM }} # [cuda_compiler_version != "None"] string: cpu_py{{ PY_VER }}h{{ PKG_HASH }}_{{ PKG_BUILDNUM }} # [cuda_compiler_version == "None"] # CUDA is not supported in windows @@ -32,7 +32,7 @@ requirements: build: - python # [build_platform != target_platform] - cross-python_{{ target_platform }} # [build_platform != target_platform] - - cmake >=3.18 + - cmake >=3.28 - make # [not win] - ninja # [win] - {{ compiler('c') }} @@ -73,7 +73,7 @@ test: about: - home: https://github.com/Microsoft/LightGBM + home: https://github.com/microsoft/LightGBM license: MIT license_family: MIT license_file: LICENSE @@ -81,8 +81,8 @@ about: description: | A fast, distributed, high performance gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks. - doc_url: http://lightgbm.readthedocs.io/en/latest/ - dev_url: https://github.com/Microsoft/LightGBM + doc_url: https://lightgbm.readthedocs.io/en/v{{ version }}/ + dev_url: https://github.com/microsoft/LightGBM extra: recipe-maintainers: