installing matplotlib on ubuntu? - matplotlib

I have:
Ubuntu 8.04
python 2.5.2 installed on this Ubuntu
matplotlib 0.92.0 installed
I want to upgrade to (atleast) matplotlib 0.99
so that I can do 3d plotting.
The synaptic package (also the command line apt-get)
tells me that whatever I have is the latest matplotlib (which is not true).
How can I install matplotlib 0.99 or matplotlib 1.0.1 ?

You have the latest available package version for your operating system. Given that Ubuntu is at version 11 now and you are using 8.04, the version difference in the matplotlib package might not come as very surprising.
As for installing the newest version, I'd suggest reading:
http://matplotlib.sourceforge.net/faq/installing_faq.html
...if all fails, you can always install from source.

Note that support for Desktop versions of 8.04 LTS is due to expire shortly -- if this is a desktop machine, perhaps the easiest answer is to upgrade to 10.04 LTS, 10.10, or the very-soon-upcoming 11.04 release (or whatever they'll call the next release). Maybe not "the easiest answer", but an answer that includes security updates for Mozilla, Adobe Flash, the Kernel, and so forth.
Many newer versions of packages are supported via the Ubuntu Backports facility, but I didn't spot python-matplotlib in the list of available packages. Perhaps they would provide it if you asked nicely, perhaps it would be too much work.
You can always try installing newer versions from newer releases, but newer versions of python and libraries might introduce worse problems. (But probably will work fine.) See the apt_preferences(5) manpage for details on how to configure multiple APT sources and select some specific packages from a newer distribution (pinning), and rely on the older distribution for all the other packages.
Jim's answer of building the version you need from source is probably your best second option, if installing a newer version of the distribution is too daunting / otherwise impossible at this point.

Related

How to upgrade gcc compiler to latest version

I have gcc 6.3.0 and to run tensorflow 2.11.0 along with cuda 11.2, I require gcc version 9.3.1, but I just cannot find a simple and straightforward way to do that. Some people say install mysys, other sites point to sourceforge download link, while download links on mingw site point to github repos, I just don't understand how to upgrade this thing.
It would be really helpful if someone could explain it like you are explaining it to complete newbie, step by step.
Last time, I downloaded mysys2 because someone told that it will automatically upgrade gcc to latest version, mysys2 came with a python 3.10, and I was working with python 3.9, and it created a lot of issues, later I had to reset my pc. That's way I just want to know the direct way to upgrade this thing instead of upgrading other software. I also tried by downloading mingw, but the installer available on sourceforge gives gcc 6.3.0 and not the latest gcc.
And what is this cygwin which gives unix like environment, why do i require unix like environment. Even if cygwin can do it easily, I am hesitant to download cygwin, cause i don't want another repeat of tragedy that happened due to mysys2, afterall, installing a complete set of programs that i don't know anything about and will probably never use will only create additional errors.

How to install specific version of Cap'n Proto (v0.8.0)?

sudo apt install capnproto
This installs v0.7.0 in my ubuntu 20.04. However, i require v0.8.0 to be installed.
Also, i need v0.6.1 to be installed additionally for backward compatibility.
Any solution for these two cases ?
You will probably need to install from source rather than use a distro package. Unfortunately, it sounds like the Ubuntu distro package hasn't been updated in a while.
Instructions for building and installing from source can be found here: https://capnproto.org/install.html
Old versions are available by changing the version number in the download URL to whichever version you need.
Note that all versions of Cap'n Proto are backwards-compatible, so there should be no need to install older versions, unless you need to run a specific complied binary that was linked against a specific old version.

Python Packaging Fix: Understand Differences between Wheel and Egg; How to get local fix to wider audience?

I'm trying to understand why the easy_install of pyicu works and pip install doesn't (see below). also trying to understand "What is the difference between a PyPi project with a universal wheel and one without?" Will installs be "easier?". If so, will this merge request solve the problem of polyglot not installing on an Anaconda machine?
Need help/advice/solutions on how to best resolve python project install issue that is tied to underlying dependencies. I have two local fixes in GitHub Gists but would like to know the best way to have this fix "out there" so people like me can find it. What is the normal Python Community approach? The problem centers around three projects:
polyglot - a python multilingual NLP toolkit
pyicu - Python extension wrapping IBM's International Components for Unicode C++ library (ICU).
pycld2 - CLD (Compact Language Detection) library as maintained by Dick Sites
The goal:
Install polyglot on a MacOSX computer running Python Anaconda Distribution
Make the fix I found available to everyone; lots of issues published about the problem.
Here's the error trace:
The Problem (Lots of them):
Core polyglot dependency, pyicu, does not properly install when you use pip install. Discovered you must use easy_install for it build properly and work on MacOSX. If you don't use the easy_install, you get:
polyglot requires icu 54.1.1 to run in Anaconda, but...
Homebrew, the MacOSX tool to install icu, only installs version 58.1. That version is too new. Old stackoverflows advise brew install icu4c to fix problem, but Homebrew evolution makes that advice obsolete now.
pyicu does not have a universal wheel; but I created a merge request to add one to pyicu. Only way to fix this is with this channel's icu, https://anaconda.org/ccordoba12/icu. conda install icu will not work, but that's the normal conda way of doing things.
*pycld2 - CLD (Compact Language Detection) becomes a problem because after I build the wheel file locally, have to download the project and run setup.py install locally. There has to be a better way to do this right?
What I've Done to Solve the problem (should I do more, what should I do next?)
Created two Gists that can successfully install polyglot on a Mac running Anaconda for Python 2.7 or Python 3.5
Python 2.7 fix
Python 3.5 fix
created the merge request for pyicu
Both Gist fixes work. But, is this error in install tied to the wheel? If I installed pyicu with easy_install, the install works. But, with pip, it doesn't?
What are the steps to take in the Python community to fix it so people can find the solution or just pip install with no problems?
I did a test, and if the wheel file is built, the pip works with no issues.

Why do Linux distributions ship outdated CMake versions?

Ubuntu shipped CMake 2.8 when version 3.3 was the current version. Other Linux distributions do it similar. Is there a reason like backwards-compatibility issues with CMake 3.0?
I found plenty of people willing to explain how to upgrade CMake to the latest version, but couldn't figure out why it wasn't done by default. I'd like to understand the mentality of keeping it back before I decide to override the decision and upgrade it myself.
Depends on the Linux distribution you're using. A distribution's maintainers cannot ship future versions and often they don't upgrade version with updates as it might break existing applications.
CMake 3.0 has some minor incompatibilities. More important, it got new features and some bugs were fixed. If software relys on these, you'll need a new version.
Btw: With CMake 2.8 the third part of the version number is relevant. They stayed a long time with 2.8.x and added features with increasing x. Then they could not update to 2.9 or 2.10, thus they decided to change the version scheme and increase y in 3.y.
Your question applies to a wider range of software. It is a general question, whether a distribution should stick to defined versions of software they provide or whether they should update it and potentially break the costumers' setup. Enterprise distributions like RHEL or SLE are very conservative and fix bugs for at least a decade. Ubuntu updates it distribution every six month but you can stick to the LTS for three years. Fedora even updates some key components like the kernel after the release. Arch Linux and openSuse Tumbleweed are rolling releases, the update their software almost on a daily bases, when the upstream updates publish new versions.

Pharo 2.0 not running on CentOS 6.6

I am trying to run my pharo2.0 application on CentoOS which was previously been installed in a mac. The original version is pharo2.0 so I need to run the same image CentoOS too, but I get an error which says this below :
/lib/libc.so.6: version `GLIBC_2.15' not found (required by xxxxx)
Should I be trying to upgrade the CentoOS and see if pharo2.0 works or port my whole application to a later version of pharo?
There is now a VM build especially for systems with an older libc version. In fact there is a build for Centos specifically (which has a slight variation in linkages from Debian), the latest version of which is permalinked here. See http://pharo.org/download#custom for more info.