I need libv8-3.14 to run some R packages on linux, but I don't have root access/sudo access on the linux computer I'm using so I'd like to install an external folder instance of libv8-3.14. I've seen R packages reference this as external as CDFLAG="folder/v8-3.14" so I know it is possible.
I'm new(ish) to linux but I've installed external libraries before with tar.gz files which then have a configure file in them, which I set the external folder with ./configure --prefix==/folder/loc, but the only downloads I can find of libv8 are .git (which I can't get to work either).
How can I install an libv8-3.14 to a folder and install so I can set:
export PATH=$PATH:/path/to/install/
and
export `LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/path/to/install/`
I had the exact same problem. In case somebody in the future comes across this post, I will leave my suggestions and how it worked out in the end. Also, all credits go to an experienced colleague of mine.
The most sure thing to do is to consult IT, or someone who has already had the same problem, there is usually a workaround these issues.
A way you can do it yourself:
Create an anaconda environment, you can name it 'V8' or something (make sure the environment is based on the latest python version, or recent enough for r-v8).
activate it
install the conda version of the V8 R interface with conda install -c conda-forge r-v8
That's it. Whenever you need V8, fire up your environment beforehand, and it should be A-OK.
Further advice: If you run into errors when installing r-v8, it may be a good idea to update your conda and all the packages. However, depending on your conda version conda update conda and conda upgrade --all MAY BREAK your conda installation, so be careful. (For further information on this problem, see the endless complaints of people in this issue: https://github.com/conda/conda/issues/8920).
V8 doesn't use autotools, so it has no ./configure. In fact, it provides no installation facilities at all, because it is meant for embedding, not installing.
What I would try is to download the Ubuntu package (guessing from your other question, you are on Ubuntu, right?) for the right architecture from https://packages.ubuntu.com/trusty/libv8-3.14.5, and extracting it manually. .deb files are just ZIP archives.
As a side note, there's no point in setting PATH, because libv8, being a library, provides no executables. LD_LIBRARY_PATH is all you need.
Related
I am using Conda on a shared compute cluster where numerical and io libraries have been tune for the system.
How can I tell Conda to use these and only worry about the libraries and packages which are not already there on path?
For example:
There is a openmpi library installed and the package which I would like to install and mange with Conda has it also as a dependency.
How can I tell Conda to just worry about what is not there?
One trick is to use a shell package - an empty package whose only purpose is to satisfy constraints for the solver. This is something that Conda Forge does with mpich, as mentioned in this section of the documentation. Namely, for every version, they include an external build variant, that one could install like
conda install mpich=3.4.2=external_*
signaling that it will be supplied by the host. One can consult the recipe's meta.yaml for a concrete example.
I don't think this is great (seems like a lot of work), but I also don't know of a better alternative.
I use Pycharm to create and manage my virtualenvs in my projects.
The problem is that after adding a library with pycharm, when I type the command (pip3 freeze --user), the library does not appear in the command result.
I have to manually type the pip install command each time so that the library is visible.
What manipulation should I do in PyCharm to solve this problem?
For what you are saying, the first thing that comes to mind is that you should use:
pip freeze
And not
pip3 freeze
Because the command mapped to the pip version when you have virtualenv activated is the first. Note that for installing you seem to use pip, and not pip3
Moreover, the --user option afaik is related to the packages installed in the user folder:
--user Install to the Python user install directory for your platform. Typically
~/.local/, or %APPDATA%\Python on
Windows. (See the Python documentation for site.USER_BASE for full details.)
If your packages are installed in the virtualenv folder, I would tell you to not use that option.
Also please make sure you have your virtualenv activated. In linux you can do so by source path/to/virtualenv/activate
Edit
I understand that the reason you are using pip3 is because you may have different versions of Python in your machine. Let me explain you a bit further how it works, because version management is usually a headache for many programmers and it is common to find problems when doing so.
If you install different versions of Python in your linux machine, and you do that as root, then the installation will proceed for the whole system. Usually Python2 installation folder for Linux machines is /usr/bin/python. However, I am uncertain of which directory is used for Python3 installations. You can check that easily by doing whereis python3. You can serach the path to binary of any command by doing whereis command. Note that this works also for whereis python as far as you don't have virtualenv activated.
Aditionally, the link to the binary of a command (or the set of instructions to be exectued, more broadly) is defined in certain folders in Linux, depending on whether you created the command as root or as a user, and possibly also on the distro. This works differently in Windows, that uses the Registry Edit utility to handle command mappings. When you enable your virtualenv, what you are doing is creating an environment that enables mapping system commands such as python to the Python installation in your virtualenv folder.
When you disable the virtualenv, the command points again to the default installation path. Same happens with pip, so incorrect usage of this tool may result in different packages being installed in different locations, and therefore not appearing available for the right Python version at any given circumstance.
In Linux, environment variables are shell dependent, though you can write them out with echo $variable and set them with variable=value (from bash). The search path is simply called PATH and you can get yours by typing echo $PATH.
Source: https://askubuntu.com/a/262073/426469
I encourage you to check other questions in SE network such as this: https://unix.stackexchange.com/a/42211/96121, to learn more about this.
Addendum
Quick tip: it is common to use the pip freeze command as follows:
pip freeze > requirements.txt
It is a standard that leads to understanding that modules in such file are required for the correct functioning of your application. That lets you easily exclude the virtualenv folder when you install the program in another computer, since you can readily know the requriments for a fresh installation. However, you can use the command as you want.
I am trying to install pysam.
After excecuting:
python path/to/pysam-master/setup.py build
This error is produced:
unable to execute 'x86_64-conda_cos6-linux-gnu-gcc': No such file or directory
error: command 'x86_64-conda_cos6-linux-gnu-gcc' failed with exit status 1
There are similar threads, but they all seem to address the problem assumig administriator rights, which I do not have. Is there a way around to install the needed files?
DISCLAIMER: This question derived from a previous post of mine.
manually installing pysam error: "ImportError: No module named version"
But since it might require a different approach, I made it a question of its own.
You can also receive the same error while installing some R packages if R was installed using conda (as I had).
Then just install the package by executing: conda install gxx_linux-64 to have that command available.
Source:
https://github.com/RcppCore/Rcpp/issues/770#issuecomment-346716808
It looks like Anaconda had a new release (4.3.27) that sets the C compiler path to a non-existing executable (quite an embarrassing bug; I'm sure they'll fix it soon). I had a similar issue with pip installing using the latest Miniconda, which I fixed by using the 4.3.21 version and ensuring I was not doing something like conda update conda.
See https://repo.continuum.io/miniconda/ which has release dates and versions.
It should now be safe to update conda. This is fixed in the following python packages for linux-64:
python-3.6.2-h0b30769_14.tar.bz2
python-2.7.14-h931c8b0_15.tar.bz2
python-2.7.13-hac47a24_15.tar.bz2
python-3.5.4-hc053d89_14.tar.bz2
The issue was as Jon Riehl described - we (Anaconda, formerly Continuum) build all of our packages with a new GCC package that we created using crosstool-ng. This package does not have gcc, it has a prefixed gcc - the missing command you're seeing, x86_64-conda_cos6-linux-gnu-gcc. This gets baked into python, and any extension built with that python goes looking for that compiler. We have fixed the issue using the _PYTHON_SYSCONFIGDATA_NAME variable that was added to python 3.6. We have backported that to python 2.7 and 3.5. You'll now only ever see python using default compilers (gcc), and you must set the _PYTHON_SYSCONFIGDATA_NAME to the appropriate filename to have the new compilers used. Setting this variable is something that we'll put into the activate scripts for the compiler package, so you'll never need to worry about it. It may take us a day or two to get new compiler packages out, though, so post issues on the conda-build issue tracker if you'd like to use the new compilers and need help getting started.
Relevant code changes are at:
py27: https://github.com/anacondarecipes/python-feedstock/tree/master-2.7.14
py35: https://github.com/anacondarecipes/python-feedstock/tree/master-3.5
py36: https://github.com/anacondarecipes/python-feedstock
The solution that worked for me was to use the conda to install the r packages:
conda install -c r r-tidyverse
or r-gggplot2, r-readr
Also ensure that the installation is not failing because of admin privileges.
It will save you a great deal of pain
After upgrading Golang to 1.19.1, I started to get:
# runtime/cgo
cgo: C compiler "x86_64-conda-linux-gnu-cc" not found: exec: "x86_64-conda-linux-gnu-cc": executable file not found in $PATH
Installing gcc_linux-64 from the same channel, has resolved it:
conda install -c anaconda gcc_linux-64
Somewhere in your $PATH (e.g., ~/bin), do
ln -sf $(which gcc) x86_64-conda_cos6-linux-gnu-gcc
Don't put this in a system directory or conda's bin directory, and remember to remove the link when the problem is resolved upstream. gcc --version should be version 6.
EDIT: I understand the sentiment in the comments against manipulating system paths, but maybe we can use a little critical thinking for the actual case in hand before reciting doctrine. What actually have we done with the command above? Nothing more than putting an executable (symlink) called x86_64-conda_cos6-linux-gnu-gcc in one's personal ~/bin directory.
If putting something in one's personal ~/bin directory broke future conda (after it fixes the C compiler path to point to gcc it embeds), then that would be a bug with conda. Would the existence of this verbosely named compiler mess with anything else? Unlikely either. Even if something did pick it up, it's just your system gcc after all...
This post summarize my painful but finally successful (just by chance) way to build own conda package for the
netgen meshing tool with Python interface. I found the recipe for the netgen build due to tpaviot.
After cloning the repository into 'netgen-conda' folder I ran:
conda build netgen-conda/netgen-6.2-dev
Which reports "Unsatisfiable dependencies": 'oce', 'gcc-5', 'binutils'.
So I tried to install these packages myself. Unfortunately the documentation do not emphasize the important fact that 'conda build' use its own temporary environment so it doesn't matter what you have installed (see). Nevertheless even installing 'gcc-5' together with 'binutils' manually turns out to be nearly impossible.
Hint for other newbies: Lot of my problems disappear after I learned details about channels.
First try was installing 'gcc-5' with 'binutils' from the 'salford_systems' channel suggested by anaconda:
conda install -c salford_systems binutils gcc-5
But it results in:
ERROR conda.core.link:_execute_actions(337): An error occurred while installing package 'salford_systems::gcc-5-5.3.0-0'.
LinkError: post-link script failed for package salford_systems::gcc-5-5.3.0-0
running your command again with-vwill provide additional information
location of failed script: /home/jb/miniconda3/envs/test/bin/.gcc-5-post-link.sh
Using verbose output ('-v') provides no more info. I was also confused by the fact that the script does not exist on the given path (probably automatically deleted).
With current experience I admit that the reason of problem can be dug out from the '-vv' output (reported issue). After some trying I found that only way to
install both is to first install 'gcc-5' into a clean environment and then install 'binutils'. Since 'conda build' installs everything
from scratch and there is no way to specify order of installed packages I was stuck.
Another issue that puzzled me is the 'conda build' long prefix hack. For unknown reason they use extremely long prefix for an auxiliary folder
which result in various kind of issues. I have faced to three such problems:
As is usual today, I have encrypted HOME causing a known issue.
Using a workaround '--croot /tmp' prevents creating the hard links from '/tmp' into 'HOME/miniconda3' since they are on different filesystems.
There is a fallback to use the copy. I even thought that the fallback doesn't work for a while, but it worked, just making the build running longer.
Trying to install 'gcc' (4.x) from 'default' channel complained about too short prefix. So ultimate workaroud was to set the length of the prefix manually
'--prefix-length 70'.
Finally, I found that the dependency on 'binutils' is not necessary and successfully build the package with:
conda build --prefix-length 70 -c salford_systems -c conda-forge -c dlr-sc netgen-conda/netgen-6.2-dev
Summary (of open questions):
Conda channels introduce a new kind of dependency hell already forgotten when using 'apt-get'. Is there a way to figure out what is a canonical channel for a package.
Does anyone succeed to build with combination 'gcc-5' and 'binutils'?
There is still lack of documentation about internal conda mechanisms and error messages do not provide clue to the problem.
Conda-build use a problematic prefix hack and lack ability to control order of installed packages. Does anybody know the reason for this hack?
I am trying to install python2.7 over given python2.6 on a web server. I am stuck at the last step trying to link new python install over the old one.
The steps I have done:
Downloaded and extracted Python 2.7
configured with --prefix=$HOME/.local
make install
What I don't get is how to link by making changes in .bashrc (and what changes to make). I looked over all the places but most the answers are not generic.
Also, I have to install couple of other lovely python stuff, like pip virtualenv, django, nltk over this. A little help on that would be too great.
Ok, without root privileges you will have to have all the python stuff and your code in your home folder. And also you won't be able to configure your nginx/apache/whatever http server you use. Does not seem like a good idea for production, but for development - sure, why not.
This means you will need to install python in your home folder. You can download and compile, but probably the simplest way to do so is pyenv - https://github.com/yyuu/pyenv. Some reading is required to understand its concepts, but it is much simpler than fiddling with manual compiling if you are not sure what you're doing.
Also it kinda replaces virtualenv, but you can still have it if you want. And of course, it all works with your non-root user. There is an installer that doesn't require root either.