It is possible to install a package in Julia 1.0 without updating other packages? For instance if a install ClusterManagers, the package IJulia (among others) gets updated. The package ClusterManagers has no dependencies.
(v1.0) pkg> add ClusterManagers
Resolving package versions...
Installed IJulia ───────────── v1.12.0
Installed ClusterManagers ──── v0.3.2
Installed ColorTypes ───────── v0.7.5
Installed OrderedCollections ─ v1.0.1
Updating `~/.julia/environments/v1.0/Project.toml`
[34f1f09b] + ClusterManagers v0.3.2
[7073ff75] ↑ IJulia v1.11.1 ⇒ v1.12.0
Updating `~/.julia/environments/v1.0/Manifest.toml`
[34f1f09b] + ClusterManagers v0.3.2
[3da002f7] ↑ ColorTypes v0.7.4 ⇒ v0.7.5
[7073ff75] ↑ IJulia v1.11.1 ⇒ v1.12.0
[bac558e1] ↑ OrderedCollections v1.0.0 ⇒ v1.0.1
Building IJulia → `~/.julia/packages/IJulia/4VL8h/deps/build.log`
I use Julia 1.0.0 (official https://julialang.org/ release) on Linux.
Yes, the intention is that adding a package should not update the other ones. This is a bug (https://github.com/JuliaLang/Pkg.jl/issues/607) that has been fixed (https://github.com/JuliaLang/Pkg.jl/pull/642) and will be included in Julia v1.0.1.
Related
I created an environment using miniconda3 with the following commands:
conda create -n r_ngs r-essentials r-base
source activate r_ngs
I needed to download some extra packages and I managed to download biomart and tximport with the following commands.
conda install -c bioconda bioconductor-tximport
conda install -c bioconda bioconductor-biomart
However, then I tried to install DESeq2 but I am getting errors. The command and errors are shown below.
conda install -c bioconda bioconductor-deseq2
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: \
Found conflicts! Looking for incompatible packages. failed
UnsatisfiableError: The following specifications were found to be incompatible with each other:
Output in format: Requested package -> Available versions
Package libgcc-ng conflicts for:
bioconductor-deseq2 -> libgcc-ng[version='>=10.3.0|>=12|>=9.4.0|>=9.3.0|>=7.5.0|>=7.3.0|>=4.9']
bioconductor-deseq2 -> r-base[version='>=4.2,<4.3.0a0'] -> libgcc-ng[version='7.2.0.*|>=11.2.0|>=7.2.0']
Package libstdcxx-ng conflicts for:
bioconductor-deseq2 -> r-base[version='>=4.2,<4.3.0a0'] -> libstdcxx-ng[version='7.2.0.*|>=11.2.0|>=7.2.0']
bioconductor-deseq2 -> libstdcxx-ng[version='>=10.3.0|>=12|>=9.4.0|>=9.3.0|>=7.5.0|>=7.3.0|>=4.9']
Package xz conflicts for:
python=3.10 -> xz[version='>=5.2.5,<6.0a0|>=5.2.6,<6.0a0']
bioconductor-deseq2 -> r-base[version='>=4.2,<4.3.0a0'] -> xz[version='5.2.*|>=5.2.4,<6.0a0|>=5.2.5,<6.0a0']The following specifications were found to be incompatible with your system:
- feature:/linux-64::__glibc==2.35=0
- feature:|#/linux-64::__glibc==2.35=0
- python=3.10 -> libgcc-ng[version='>=11.2.0'] -> __glibc[version='>=2.17']
Your installed version is: 2.35
The R version I have in the environment is R version 3.6.1 (2019-07-05).
How can I fix this?
Thank you
Bioconda has very specific channel requirements, namely:
conda-forge > bioconda > defaults
The best way to manage Conda environments is with YAMLs. One to use DESeq2 might look something like:
r_ngs.yaml
name: r_ngs
channels:
- conda-forge
- bioconda
- defaults
dependencies:
- r-base=4.2
- bioconductor-deseq2
## additional packages...
and create it with
conda env create -n r_ngs -f r_ngs.yaml
Note, it is almost always preferable to declare all dependencies at time of creation of the environment.
Need to install Azure cosmos-db python sdk via conda. But I can only install up to version 3.1.2 and 4.2.0 is needed in the project. I wonder how can I manually load the prebuild cosmo sdk in to the conda environment?
I have a env.yml file shown as follow, the enviroment is created via conda env create -f <path_to_env.yml>
name: cco_1410
channels:
- conda-forge
dependencies:
- azure-cosmos=4.2.0 (this would lead to fail)
- python=3
- fastapi=0.65.0
- pytest
install 4.2.0 version via conda is not possible. Conda is only able to install up to 3.1.2 version
conda search azure-cosmos
returns
/opt/miniconda3/lib/python3.9/site-packages/requests/__init__.py:89: RequestsDependencyWarning: urllib3 (1.26.2) or chardet (4.0.0) doesn't match a supported version!
warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "
Loading channels: done
# Name Version Build Channel
azure-cosmos 3.0.2 py_0 conda-forge
azure-cosmos 3.1.0 py_0 conda-forge
azure-cosmos 3.1.1 py_0 conda-forge
azure-cosmos 3.1.2 py_0 conda-forge
azure-cosmos 3.1.2 py_0 pkgs/main
In lieu of someone fixing the Conda Forge feedstock so that the newer versions are available on Conda, it is a PyPI package, so one can also install it through Pip:
name: cco_1410
channels:
- conda-forge
dependencies:
- python=3
- fastapi=0.65.0
- pytest
- pip
- pip:
- azure-cosmos==4.2.0
Please read the Conda documentation on installing non-Conda packages.
Microsoft releases Azure SDK packages for conda every three months in Microsoft channel (https://anaconda.org/microsoft).
azure-cosmos 4.2.0 was included in Sep. release.
You can find it from https://anaconda.org/microsoft/azure-cosmos.
(I work in MS in the SDK team)
I need to use the RequestsLibrary library and when I import it:
*** Settings ***
Library SeleniumLibrary
Library RequestsLibrary
I get an error module not found. When I run pipenv graph I can clearly see it's installed:
(marek) bash-3.2$ pipenv graph
robotframework-requests==0.5.0
- requests [required: Any, installed: 2.22.0]
- certifi [required: >=2017.4.17, installed: 2019.6.16]
- chardet [required: >=3.0.2,<3.1.0, installed: 3.0.4]
- idna [required: >=2.5,<2.9, installed: 2.8]
- urllib3 [required: >=1.21.1,<1.26,!=1.25.1,!=1.25.0, installed: 1.25.3]
- robotframework [required: Any, installed: 3.1.2]
What am I doing wrong ?
As turned out the issue was the fact that I installed the library using pipenv install xyz and that creates brand new virtual environment prior to library installation. So I basically ended up with a virtual environment within virtual environment and Robot couldn't access it. As soon as I got rid off the extra virtual environment, exited out and ran pipenv install robotframework-requests outside of any venv, it ran.
I'm trying to install an R package called rcdd using conda build and there is a problem with the C compiler. Note that this problem looks very similar to
Conda build R package fails at C compiler issue on MacOS Mojave however as (i) that question remains unanswered, and (ii) this relates to different package, I think this is not a duplicate question.
I'm using MacOS Mojave, conda 4.6.8. In a new conda environment with r-base and r-essentials
installed, I try
conda install conda-build
conda skeleton cran --recursive rcdd
conda build r-rcdd
and get the following error
* installing *source* package ‘rcdd’ ...
** package ‘rcdd’ successfully unpacked and MD5 sums checked
checking for gcc... x86_64-apple-darwin13.4.0-clang
checking whether the C compiler works... no
configure: error: in `/Users/pjethwa/miniconda3/envs/r_env/conda-bld/r-rcdd_1553173041138/work':
configure: error: C compiler cannot create executables
See `config.log' for more details
ERROR: configuration failed for package ‘rcdd’
The config.log file contains the same error message. This same error also appears when I try to install directly from R - i.e. using install.packages('rcdd'). I am able, however, to install this package using a version of R which was not installed by conda. This solution is unsatisfactory as I would like to use rpy2 to interface python and R, which seems to require that R be installed by conda (e.g. see Getting Segmentation fault Core dumped error while importing robjects from rpy2)
My clang/gcc versions are:
(r_env) myusername:~ clang --version
clang version 4.0.1 (tags/RELEASE_401/final)
Target: x86_64-apple-darwin18.2.0
Thread model: posix
InstalledDir: /Users/myusername/miniconda3/envs/r_env/bin
(r_env) myusername:~ gcc --version
Configured with: --prefix=/Library/Developer/CommandLineTools/usr --with-gxx-include-dir=/usr/include/c++/4.2.1
Apple LLVM version 10.0.0 (clang-1000.10.44.4)
Target: x86_64-apple-darwin18.2.0
Thread model: posix
InstalledDir: /Library/Developer/CommandLineTools/usr/bin
One of the main features of Anaconda is that it is language agnostic as stated in their blog:
You can create environments of any binary dependency tree (different
versions of Python, R, Julia, etc.).
Recently I switched from using virtualenv to Anaconda in Python, so I was curious to try Julia in an Anaconda environment. However, I couldn't find instructions explicit enough to install Julia successfully. First, I tried naively conda create -n julia-test julia. Obviously, it didn't work. Then I found at binstar.org a Julia package (version 0.3) with the code
conda install -c https://conda.binstar.org/wakari1 julia
However, I don't want to install Julia outside of a specific virtual environment, so I changed it to:
conda create -n julia-test -c https://conda.binstar.org/wakari1 julia
It didn't throw errors but ultimately failed to start the Julia interpreter.
So, what is the correct way of installing Julia (0.2, preferably) in an anaconda environment?
UPDATE
As of March 2018, Julia v0.6.1 is available for linux-64 on the conda-forge channel:
https://anaconda.org/conda-forge/julia
It has been set up to install packages inside <env_prefix>/share/julia/site, to maintain isolation from the user's ~/.julia user's home directory.
conda create -n julia -c conda-forge julia
As of August 2017, Julia v0.5.2 is available on the conda-forge channel:
https://anaconda.org/conda-forge/julia
It has been set up to install packages inside <env_prefix>/share/julia/site, to maintain isolation from the user's ~/.julia user's home directory.
conda create -n julia -c conda-forge julia
The blog post was indicating that conda is general enough to allow packages of any type. There are no packages for Julia yet (except for the one you found in the Wakari channel, which is specific to Wakari).
Building a conda package for Julia and probably isn't difficult. Building a streamlined way to convert Julia packages into conda packages is a bit more work.
Julia 0.4.5 (not the current latest 0.5.0) is now available from the bioconda channel.
Using anaconda (python 3.6 version) and following instructions in bioconda :
# In this order
conda config --add channels conda-forge
conda config --add channels defaults
conda config --add channels r
conda config --add channels bioconda
conda install julia
So to create the corresponding virtual environment:
conda create -n julia-env julia
Nonetheless, I did not see any additional julia libraries available yet.
As of Jan 2022, Anaconda suggests using;
conda install -c conda-forge julia
See: https://anaconda.org/conda-forge/julia