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capnproto-feedstock's Introduction

About capnproto-feedstock

Feedstock license: BSD-3-Clause

Home: http://capnproto.org

Package license: MIT

Summary: An insanely fast data interchange format and capability-based RPC system.

Current build status

Azure
VariantStatus
linux_64 variant
osx_64 variant
win_64 variant

Current release info

Name Downloads Version Platforms
Conda Recipe Conda Downloads Conda Version Conda Platforms

Installing capnproto

Installing capnproto from the conda-forge channel can be achieved by adding conda-forge to your channels with:

conda config --add channels conda-forge
conda config --set channel_priority strict

Once the conda-forge channel has been enabled, capnproto can be installed with conda:

conda install capnproto

or with mamba:

mamba install capnproto

It is possible to list all of the versions of capnproto available on your platform with conda:

conda search capnproto --channel conda-forge

or with mamba:

mamba search capnproto --channel conda-forge

Alternatively, mamba repoquery may provide more information:

# Search all versions available on your platform:
mamba repoquery search capnproto --channel conda-forge

# List packages depending on `capnproto`:
mamba repoquery whoneeds capnproto --channel conda-forge

# List dependencies of `capnproto`:
mamba repoquery depends capnproto --channel conda-forge

About conda-forge

Powered by NumFOCUS

conda-forge is a community-led conda channel of installable packages. In order to provide high-quality builds, the process has been automated into the conda-forge GitHub organization. The conda-forge organization contains one repository for each of the installable packages. Such a repository is known as a feedstock.

A feedstock is made up of a conda recipe (the instructions on what and how to build the package) and the necessary configurations for automatic building using freely available continuous integration services. Thanks to the awesome service provided by Azure, GitHub, CircleCI, AppVeyor, Drone, and TravisCI it is possible to build and upload installable packages to the conda-forge anaconda.org channel for Linux, Windows and OSX respectively.

To manage the continuous integration and simplify feedstock maintenance conda-smithy has been developed. Using the conda-forge.yml within this repository, it is possible to re-render all of this feedstock's supporting files (e.g. the CI configuration files) with conda smithy rerender.

For more information please check the conda-forge documentation.

Terminology

feedstock - the conda recipe (raw material), supporting scripts and CI configuration.

conda-smithy - the tool which helps orchestrate the feedstock. Its primary use is in the construction of the CI .yml files and simplify the management of many feedstocks.

conda-forge - the place where the feedstock and smithy live and work to produce the finished article (built conda distributions)

Updating capnproto-feedstock

If you would like to improve the capnproto recipe or build a new package version, please fork this repository and submit a PR. Upon submission, your changes will be run on the appropriate platforms to give the reviewer an opportunity to confirm that the changes result in a successful build. Once merged, the recipe will be re-built and uploaded automatically to the conda-forge channel, whereupon the built conda packages will be available for everybody to install and use from the conda-forge channel. Note that all branches in the conda-forge/capnproto-feedstock are immediately built and any created packages are uploaded, so PRs should be based on branches in forks and branches in the main repository should only be used to build distinct package versions.

In order to produce a uniquely identifiable distribution:

  • If the version of a package is not being increased, please add or increase the build/number.
  • If the version of a package is being increased, please remember to return the build/number back to 0.

Feedstock Maintainers

capnproto-feedstock's People

Contributors

beckermr avatar conda-forge-admin avatar conda-forge-curator[bot] avatar frol avatar ihnorton avatar jaimergp avatar lehmaxence avatar regro-cf-autotick-bot avatar wolfv avatar

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capnproto-feedstock's Issues

conda build error on osx

Issue:
Error while building package on osx as shown below:

+ cmake -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX=/Users/spalani/anaconda2/conda-bld/capnproto_1611111171629/_h_env_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold -DCMAKE_INSTALL_LIBDIR=lib -DBUILD_TESTING=OFF -DCMAKE_CXX_COMPILE_FEATURES=cxx_constexpr ../c++
-- The CXX compiler identification is Clang 10.0.0
-- Detecting CXX compiler ABI info
-- Detecting CXX compiler ABI info - done
-- Check for working CXX compiler: $BUILD_PREFIX/bin/x86_64-apple-darwin13.4.0-clang++ - skipped
-- Detecting CXX compile features
-- Detecting CXX compile features - done
-- Looking for C++ include initializer_list
-- Looking for C++ include initializer_list - found
CMake Error at src/kj/CMakeLists.txt:75 (target_compile_features):
  target_compile_features The compiler feature "cxx_generic_lambdas" is not
  known to CXX compiler

  "Clang"

  version 10.0.0.


Environment (conda list):
$ conda list
# packages in environment at /Users/spalani/anaconda2/envs/tmubuild:
#
# Name                    Version                   Build  Channel
blas                      1.0                         mkl
ca-certificates           2020.12.8            hecd8cb5_0
certifi                   2020.12.5        py37hecd8cb5_0
intel-openmp              2019.4                      233
libcxx                    10.0.0                        1
libedit                   3.1.20191231         h1de35cc_1
libffi                    3.3                  hb1e8313_2
mkl                       2019.4                      233
mkl-service               2.3.0            py37h9ed2024_0
mkl_fft                   1.2.0            py37hc64f4ea_0
mkl_random                1.1.1            py37h959d312_0
ncurses                   6.2                  h0a44026_1
numpy                     1.19.2           py37h456fd55_0
numpy-base                1.19.2           py37hcfb5961_0
openssl                   1.1.1i               h9ed2024_0
pip                       20.3.3           py37hecd8cb5_0
python                    3.7.9                h26836e1_0
readline                  8.0                  h1de35cc_0
setuptools                51.1.2           py37hecd8cb5_4
six                       1.15.0           py37hecd8cb5_0
sqlite                    3.33.0               hffcf06c_0
tk                        8.6.10               hb0a8c7a_0
wheel                     0.36.2             pyhd3eb1b0_0
xz                        5.2.5                h1de35cc_0
zlib                      1.2.11               h1de35cc_3

Details about conda and system ( conda info ):
$ conda info

     active environment : tmubuild
    active env location : /Users/spalani/anaconda2/envs/tmubuild
            shell level : 2
       user config file : /Users/spalani/.condarc
 populated config files : /Users/spalani/.condarc
          conda version : 4.9.2
    conda-build version : 3.19.2
         python version : 3.7.2.final.0
       virtual packages : __osx=10.14.6=0
                          __unix=0=0
                          __archspec=1=x86_64
       base environment : /Users/spalani/anaconda2  (writable)
           channel URLs : https://repo.anaconda.com/pkgs/main/osx-64
                          https://repo.anaconda.com/pkgs/main/noarch
                          https://repo.anaconda.com/pkgs/r/osx-64
                          https://repo.anaconda.com/pkgs/r/noarch
          package cache : /Users/spalani/anaconda2/pkgs
                          /Users/spalani/.conda/pkgs
       envs directories : /Users/spalani/anaconda2/envs
                          /Users/spalani/.conda/envs
               platform : osx-64
             user-agent : conda/4.9.2 requests/2.22.0 CPython/3.7.2 Darwin/18.7.0 OSX/10.14.6
                UID:GID : 1013275011:1785187213
             netrc file : None
           offline mode : False

Seems to be resolved if -DCMAKE_CXX_COMPILE_FEATURES=cxx_generic_lambdas is added to the EXTRA_CMAKE_ARGS flag in build script. Is this right approach ?

Default imports are not imported by default

capnproto sets the default imports location at build time through the CAPNP_INCLUDE_DIR symbol definition. This symbol is set by autotool (and cmake) to the absolute path $PREFIX/include, this hampers the relocatability of the capnp binary.

Current workaround is to re-include the default imports location when needed, e.g.:
capnpc -I"$CONDA_PREFIX/include" <..>

Note:
conda-build replaces the $PREFIX in files by a placeholder so that it gets replace by the correct value at install time, but this doesn't work for the binary as it created string length issues.

This issue is related to the one here: capnproto/capnproto#1062

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