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A conda-smithy repository for xeus-cling.

License: BSD 3-Clause "New" or "Revised" License

Shell 12.43% Batchfile 11.81% Python 75.76%

xeus-cling-feedstock's Introduction

About xeus-cling-feedstock

Feedstock license: BSD-3-Clause

Home: https://github.com/jupyter-xeus/xeus-cling

Package license: BSD-3-Clause

Summary: Cling-based C++ kernel for Jupyter based on xeus

Development: https://github.com/jupyter-xeus/xeus-cling

Documentation: https://xeus-cling.readthedocs.io

Jupyter kernel for the C++ programming language

Current build status

Azure

Variant	Status
linux_64

Current release info

Name	Downloads	Version	Platforms

Installing xeus-cling

Installing xeus-cling 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, xeus-cling can be installed with conda:

conda install xeus-cling

or with mamba:

mamba install xeus-cling

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

conda search xeus-cling --channel conda-forge

or with mamba:

mamba search xeus-cling --channel conda-forge

Alternatively, mamba repoquery may provide more information:

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

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

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

About conda-forge

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-Cloud 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 xeus-cling-feedstock

If you would like to improve the xeus-cling 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/xeus-cling-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

xeus-cling-feedstock's People

Contributors

Stargazers

Watchers

Forkers

regro-cf-autotick-bot johanmabille wolfv dokempf chrisburr sylvaincorlay

xeus-cling-feedstock's Issues

Arm64 on OSX

Comment:

Can arm64 on OSX also be added?

Problem(s) xeus-cling C++17 not working with ubuntu 20.04

Hi.

I had problems while trying to refresh my home-made docker images for xeus-cling, starting now from ubuntu:20.04. My students which are trying to install xeus-cling directly on their ubuntu:20.04 machines reported similar problems with the C++17 kernel.

When building my docker image, I got the "clangdev-5.0.0-default_0" during installation of xeus-cling, which I solved with the trick provided by Johan for Nicolas Thiery.

Then, after starting my container and running the jupyter server, I observe that I cannot start any C++17 kernel. C++14 is fine. My students, not using docker, and trying various installation recipes on their ubuntu station, all finish with this same problem with the C++17 kernel.

My minimal Docker recipe to demonstrate the problem:

FROM ubuntu:20.04

SHELL ["/bin/bash","-c"]

RUN apt-get update \
&& apt-get install -y wget

ARG MINICONDA_ROOT=/opt/miniconda3
ENV PATH ${MINICONDA_ROOT}/bin:${PATH}
RUN wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh \
&& bash Miniconda3-latest-Linux-x86_64.sh -b -p ${MINICONDA_ROOT} \
&& rm Miniconda3-latest-Linux-x86_64.sh \
&& conda init bash

RUN conda update -y conda \
&& conda install -c conda-forge mamba \
&& mamba install -c conda-forge jupyter \
&& mamba install -c conda-forge _openmp_mutex=*=1_gnu \
&& mamba uninstall -c conda-forge llvm-openmp \
&& mamba install -c conda-forge xeus-cling

CMD bash

I start the image with docker run -it --rm -p 8888:8888 -v $PWD:/work -w /work ...

I start the server with jupyter notebook --debug --no-browser --allow-root --ip=0.0.0.0

Then I browse and experiment : a notebook wih C++14 kernel is ok, a notebokk with C++17 kernel is not.

Excerp from the log:

...
[D 12:00:52.244 NotebookApp] Starting kernel: ['/opt/miniconda3/bin/xcpp', '-f', '/root/.local/share/jupyter/runtime/kernel-fbf7653d-48ed-4c13-b081-df229b2b5dc2.json', '-std=c++17']
[D 12:00:52.253 NotebookApp] Connecting to: tcp://127.0.0.1:58631
[D 12:00:52.254 NotebookApp] Connecting to: tcp://127.0.0.1:45835
[I 12:00:52.256 NotebookApp] Kernel started: fbf7653d-48ed-4c13-b081-df229b2b5dc2, name: xcpp17
[D 12:00:52.256 NotebookApp] Kernel args: {'kernel_name': 'xcpp17', 'cwd': '/work/1-CollectiveDay/2-Reminders'}
[D 12:00:52.259 NotebookApp] 201 POST /api/sessions (172.17.0.1) 20.410000ms
[D 12:00:52.273 NotebookApp] Initializing websocket connection /api/kernels/fbf7653d-48ed-4c13-b081-df229b2b5dc2/channels
[D 12:00:52.276 NotebookApp] Requesting kernel info from fbf7653d-48ed-4c13-b081-df229b2b5dc2
[D 12:00:52.276 NotebookApp] Connecting to: tcp://127.0.0.1:57313
[I 12:00:55.255 NotebookApp] KernelRestarter: restarting kernel (1/5), new random ports
[D 12:00:55.256 NotebookApp] Starting kernel: ['/opt/miniconda3/bin/xcpp', '-f', '/root/.local/share/jupyter/runtime/kernel-fbf7653d-48ed-4c13-b081-df229b2b5dc2.json', '-std=c++17']
[D 12:00:55.261 NotebookApp] Connecting to: tcp://127.0.0.1:58631
[I 12:00:58.264 NotebookApp] KernelRestarter: restarting kernel (2/5), new random ports
[D 12:00:58.265 NotebookApp] Starting kernel: ['/opt/miniconda3/bin/xcpp', '-f', '/root/.local/share/jupyter/runtime/kernel-fbf7653d-48ed-4c13-b081-df229b2b5dc2.json', '-std=c++17']
[D 12:00:58.269 NotebookApp] Connecting to: tcp://127.0.0.1:58631
[I 12:01:01.272 NotebookApp] KernelRestarter: restarting kernel (3/5), new random ports
[D 12:01:01.273 NotebookApp] Starting kernel: ['/opt/miniconda3/bin/xcpp', '-f', '/root/.local/share/jupyter/runtime/kernel-fbf7653d-48ed-4c13-b081-df229b2b5dc2.json', '-std=c++17']
[D 12:01:01.279 NotebookApp] Connecting to: tcp://127.0.0.1:58631
[I 12:01:04.280 NotebookApp] KernelRestarter: restarting kernel (4/5), new random ports
[D 12:01:04.280 NotebookApp] Starting kernel: ['/opt/miniconda3/bin/xcpp', '-f', '/root/.local/share/jupyter/runtime/kernel-fbf7653d-48ed-4c13-b081-df229b2b5dc2.json', '-std=c++17']
[D 12:01:04.286 NotebookApp] Connecting to: tcp://127.0.0.1:58631
[W 12:01:07.289 NotebookApp] KernelRestarter: restart failed
...

cxxopts should be a runtime dependency

On a pristine conda installation of xeus-cling, running find_package(xeus-cling) from a CMake project fails, because cxxopts cannot be found. I think the reason is that the cxxopts dependency is marked PUBLIC in xeus-cling, but cxxopts is not treated as a runtime dependency in the feedstock.

FWIW, my reason to call find_package(xeus-cling) is to support installation of Doxygen tag files in this project: https://github.com/dokempf/xeus-cling-cmake-setup

Details about conda and system ( conda info ):

$ conda info

    active environment : cling
    active env location : /home/dominic/anaconda3/envs/cling
    shell level : 3
       user config file : /home/dominic/.condarc
 populated config files : 
          conda version : 4.9.2
    conda-build version : 3.20.5
         python version : 3.8.5.final.0
       virtual packages : __glibc=2.31=0
                          __unix=0=0
                          __archspec=1=x86_64
       base environment : /home/dominic/anaconda3  (writable)
           channel URLs : https://repo.anaconda.com/pkgs/main/linux-64
                          https://repo.anaconda.com/pkgs/main/noarch
                          https://repo.anaconda.com/pkgs/r/linux-64
                          https://repo.anaconda.com/pkgs/r/noarch
          package cache : /home/dominic/anaconda3/pkgs
                          /home/dominic/.conda/pkgs
       envs directories : /home/dominic/anaconda3/envs
                          /home/dominic/.conda/envs
               platform : linux-64
             user-agent : conda/4.9.2 requests/2.24.0 CPython/3.8.5 Linux/5.8.0-44-generic ubuntu/20.04.2 glibc/2.31
                UID:GID : 1001:1001
             netrc file : None
           offline mode : False

Remove broken builds from Anaconda.org

The build 0 of xeus-cling 0.8.1 is broken on both Linux and OS X.

osx-64/xeus-cling-0.8.1-h7475705_0.tar.bz2
linux-64/xeus-cling-0.8.1-he513fc3_0.tar.bz2

It would be fantastic if we could label these builds as broken.

cc @conda-forge/core

xeus-cling not available

xeus-cling package is not currently available through conda. Neither install nor the conda search xeus-cling --channel conda-forge work.

[conda relocation] Quick help not working with conda package

?std::vector

does not work with the OS X conda package, although it works fine when building locally with the same toolchain. The issue appears to be that the C runtime from the system is used (to open files) instead of the one from conda that was used to link cling. This may be a relocation issue.

I opened conda/conda-build#3025 earlier to track the relocation issue.

Can't install xeus-cling on jupyter-scipy-notebook

sudo docker run -ti jupyter/scipy-notebook bash
...
Digest: sha256:8896f1b51624f961b4a22c945c317d2471b06467845de766f3f747d8f2bd0ebf
Status: Downloaded newer image for jupyter/scipy-notebook:latest
(base) jovyan@7cf0d0e47f70:~$ mamba install xeus-cling
...
Looking for: ['xeus-cling']

WARNING conda.lock:touch(51): Failed to create lock, do not run conda in parallel processes [errno 13]
conda-forge/noarch       [====================] (00m:02s) Done
conda-forge/linux-64     [====================] (00m:03s) Done

Pinned packages:
  - python 3.9.*
  - python 3.9.6


Encountered problems while solving:
  - nothing provides system needed by clangdev-5.0.0-default_0