import os import sys from distutils.file_util import copy_file if __name__ == "__main__": source = sys.argv[1] current_dir = os.path.abspath(os.path.dirname(__file__)) if not os.path.exists(os.path.join(current_dir, "runtimes/linux-x64/native")): os.makedirs(os.path.join(current_dir, "runtimes/linux-x64/native")) if not os.path.exists(os.path.join(current_dir, "runtimes/osx-x64/native")): os.makedirs(os.path.join(current_dir, "runtimes/osx-x64/native")) if not os.path.exists(os.path.join(current_dir, "runtimes/win-x64/native")): os.makedirs(os.path.join(current_dir, "runtimes/win-x64/native")) copy_file(os.path.join(source, "lib_lightgbm.so"), os.path.join(current_dir, "runtimes/linux-x64/native/lib_lightgbm.so")) copy_file(os.path.join(source, "lib_lightgbm.dylib"), os.path.join(current_dir, "runtimes/osx-x64/native/lib_lightgbm.dylib")) copy_file(os.path.join(source, "lib_lightgbm.dll"), os.path.join(current_dir, "runtimes/win-x64/native/lib_lightgbm.dll")) version = open(os.path.join(current_dir, '../VERSION.txt')).read().strip() nuget_str = ''' LightGBM %s Guolin Ke Guolin Ke https://github.com/Microsoft/LightGBM/blob/master/LICENSE https://github.com/Microsoft/LightGBM false A fast, distributed, high performance gradient boosting framework Copyright 2018 @ Microsoft machine-learning data-mining distributed native boosting gbdt ''' % (version) with open(os.path.join(current_dir, "LightGBM.nuspec"), "w") as nuget_file: nuget_file.write(nuget_str)