Well, in the meantime I can just use the conda-forge packages. (though there are regular issues when updating packages where conda switches back and forth from Anaconda and conda-forge packages)
Regards Antoine. Le 18/03/2019 à 13:59, Uwe L. Korn a écrit : > Hello Antoine, > > you're running into > https://github.com/ContinuumIO/anaconda-issues/issues/10731 I would rather > have Anaconda fix this but we can also add alternative detection for this. > I've opened https://issues.apache.org/jira/browse/ARROW-4946, I can then > look into this the next hours/tomorrow. As with double-conversion, > `-DFlatbuffers_SOURCE=BUNDLED` is a possible workaround until then. > > Uwe > > On Mon, Mar 18, 2019, at 1:55 PM, Antoine Pitrou wrote: >> >> Ah, apparently I can do it through `-Ddouble-conversion_SOURCE=BUNDLED`. >> >> Now there's another issue: the CMake configuration fails to find flatbuffers, >> even though I have flatbuffers 1.7.1 installed from Anaconda. >> >> >> CMake Error at cmake_modules/ThirdpartyToolchain.cmake:152 (find_package): >> By not providing "FindFlatbuffers.cmake" in CMAKE_MODULE_PATH this project >> has asked CMake to find a package configuration file provided by >> "Flatbuffers", but CMake did not find one. >> >> Could not find a package configuration file provided by "Flatbuffers" with >> any of the following names: >> >> FlatbuffersConfig.cmake >> flatbuffers-config.cmake >> >> Add the installation prefix of "Flatbuffers" to CMAKE_PREFIX_PATH or set >> "Flatbuffers_DIR" to a directory containing one of the above files. If >> "Flatbuffers" provides a separate development package or SDK, be sure it >> has been installed. >> Call Stack (most recent call first): >> cmake_modules/ThirdpartyToolchain.cmake:1485 (resolve_dependency) >> CMakeLists.txt:544 (include) >> >> >> >> Regards >> >> Antoine. >> >> >> Le 18/03/2019 à 13:51, Antoine Pitrou a écrit : >>> >>> Ok, so I have a problem. I had the following line: >>> >>> export DOUBLE_CONVERSION_HOME= >>> >>> which was used to force double-conversion to be built from source >>> despite other dependencies being taken from the Conda environment. Now >>> it doesn't work anymore, and I haven't found how to emulate it. >>> >>> Regards >>> >>> Antoine. >>> >>> >>> >>> Le 15/03/2019 à 15:38, Uwe L. Korn a écrit : >>>> Hello fellow Arrow Devs, >>>> >>>> we have merged the CMake refactor yesterday >>>> https://github.com/apache/arrow/pull/3688 and this means that the build >>>> system behaves a bit different. The main differences are: >>>> >>>> * If you're in a conda environment, we automatically detect this using the >>>> environment variable $CONDA_PREFIX and expect that all dependencies >>>> (except jemalloc and ORC) are installed via conda. >>>> * Otherwise, we will look in the standard system paths for a dependency. >>>> If it isn't found, we use CMake's ExternalProject mechanism to build it. >>>> * The *_HOME variables are not longer use and are replaced by *_ROOT >>>> variables to use CMake's standard detection features. Be aware that >>>> dependencies are no longer written in all caps but their preferred casing >>>> as seen in >>>> https://github.com/apache/arrow/blob/0d302125abb4b514dba210f496c574a77ce4cd1d/cpp/cmake_modules/ThirdpartyToolchain.cmake#L41-L59 >>>> * You can manually select the way we detect dependencies via >>>> ARROW_DEPENDENCY_SOURCE >>>> https://github.com/apache/arrow/blob/0d302125abb4b514dba210f496c574a77ce4cd1d/cpp/CMakeLists.txt#L189-L207 >>>> The hope is that you as a developer should not normally need to change >>>> this and as packager for distributions, you can use >>>> `ARROW_DEPENDENCY_SOURCE=SYSTEM` to ensure that ExternalProject is not >>>> used but only packages from the package manager. If your system is in a >>>> non-default prefix, you can indicate this by setting ARROW_PACKAGE_PREFIX. >>>> >>>> Also, please clear your existing CMake directories and do a fresh built to >>>> avoid any problems. As well when you're using conda packages, please >>>> update them all using `conda update --all` as I have errors in the >>>> packaging directly on conda-forge instead of doing workarounds in our >>>> CMake code. A helpful information is here that conda-forge now provides a >>>> `compilers` package that provides the whole build toolchain. >>>> >>>> Uwe >>>> >>
