Over the last few days of headaches, I've found 3 possible methods to do this, all of which have issues.
PyGObject's pip install fails due to a lack of Cairo and probably other dependencies. While this would be my preferred method, it would probably be the hardest to fulfill.
Using MSYS2 allows me to use GObject through the mingw64 python, but using pip to get my other modulues such as pylint fails. I'd like to have an MSYS2 or similar install on my system anyways to make some windows binaries, so I'm very open to this as well.
EDIT: Got pip to work in MSYS2. Make sure to sync toolchain with pacman.
PyGObject for Windows seems messy at best and isn't up-to-date. Would require having a second python installation anyways, giving no benefit over MSYS2.
Note I'm a complete newbie to Unix and have little experience with CLI's in general, so any help regarding MSYS2 will need to be explained as if to a child. My only other experience with this stuff involved an endless cycle of hell that was installing Arch to a separate partition, breaking said install, then reinstalling again.
I also tried Cygwin, but I couldn't get that to run Python with GObject at all with my "install all the needed packages then pray" method. Creating a Gtk.Window() caused the terminal to use none of the memory it had and explode.
MSYS2 is currently the only "officially" supported way: https://pygobject.readthedocs.io/en/latest/getting_started.html#windows
pip in MSYS2 should work in general, if something doesn't please file a bug at https://github.com/Alexpux/MINGW-packages/issues .
As you said in the third alternative to install a new Python version, you can create and run multiple Python versions using pyenv. You can go through the installation section of their Github repo for installation and an overview: https://github.com/pyenv/pyenv/
For a comprehensive guide on how to use it, you read this amazing post by Real Python:
https://realpython.com/intro-to-pyenv/
Related
I am using openSUSE Leap 42.1 and do some data analysis work in python. Most of the python packages I use are available in the standard openSUSE repositories (e.g. obs://build.opensuse.org/devel:languages:python); however sometimes they aren't, whereas they are available in Anaconda. I would like to replace all of the python packages installed on my computer with those available through Anaconda.
Is it possible to just install Anaconda in parallel with the normal openSUSE packages or should I manually delete the packages I've installed? I know python is used heavily throughout the operating system so I probably don't want to deep clean the system of python before going the Anaconda route.
Has anyone done this before? I was unable to find any info on this on the Anaconda site, and I'm curious if there is a clean way to do this.
I read the anaconda documentation, and there is no evidence of anaconda packages replacing your openSUSE packages. There isn't a reason for it to do so. If I got it right, then Conda is very similar to ruby's gem and similar tools, which definitely don't replace the installed packages. I think you can feel free to install it next to your current packages. Also, you can specify the python and python package version in the anaconda envinroments, which is another thing which it allows you to do, so you can decide what you will use there. Note, I'm not a conda user, this is how I understood the docs. Hope this helps.
Our command line utility is written with Python.
On Linux/OS X this is usually not a problem since both come with Python 2.x pre installed. However on Windows, Python isn't installed by default.
Additional problem is that few of our dependencies require compiling which yet again is not a trivial problem for Windows users since it requires tinkering with MSVC/Cygwin/etc'.
Up until now we solved this issue by using Pyinstaller to create "frozen" Python package with pre-installed dependencies. This worked well, however made our utility non extendable - we cannot add additional Python modules by using utilities such as pip for example. Since our CLI depends on this ability in order to add additional usability, this limitation became a blocker for us and we would like to rethink our approach.
Searching around, I found how Rhodecode solve this. Basicly their installer brings Python and everything else (including pre-compiled dependencies).
This seem as a good idea for us, the only limitation I see here is that their installer actually installs Python from .msi which puts stuff in Windows Registry. So there can be only one Python of version X.Y installed on Windows (from .msi)
For a server application this might be reasonable since server application tends to act like it's the only thing installed on the PC, but for command line utility, this is completely unacceptable.
Looking around I found few projects that claim to make Python portable - for example Portable Python. However I'm not sure how "portable" it really is, especially after issues like this.
So questions are:
Is it possible to install same Python version multiple times on Windows without creating collisions between the instances?
Would you choose other workaround to solving this problem (please no "smart" solutions such as: drop Windows support/don't use Python)
Thanks!
Frankly I would stick with PyInstaller or something similar. That will always provide you with the correct version of Python whether or not the target machine has Python installed. It also protects you from clobbering a previously installed version of Python.
If you need to add plugins, then you should build that into your app. There are a few projects that might help you with that. Here are a couple of examples:
http://yapsy.sourceforge.net/
https://pypi.python.org/pypi/Plugins/
You might also take a look at how Django or Flask handles extensions. For example, you can add an extension to Flask to allow it to work with SQLAlchemy. You should be able to do something similar with your own application. The pip utility won't work with a frozen application after all. Alternatively, have you looked at conda? It might work for your purposes.
This is an answer for my second question, sadly I still haven't figured out a better solution for number 1.
For now here's how we changed our approach for creating setup file:
We package our code and its dependencies as set of pre-built Python wheels. It's relatively easy to create pre-built wheels on Windows since the release of Visual C++ compiler for Python2.7.
We package Python setup MSI together with Pip, Setuptools and Virtualenv wheels.
Before install starts we check whether Python, Pip and Virtualenv are already installed (by looking in the registry and \Scripts), if it's not, we install it from the packaged wheels. Pip wheel is installed by using get-pip.py script which we bundle as well.
We create separate Virtualenv and install our wheels into it.
Uninstall is done by removing the virtualenv folder. Python, Pip and Virtualenv install are left behind.
Installer created by Inno Setup.
I'm still not fully satisfied with this solution since some components are globally installed and might collide with what user had already installed before (older/newer version of python, pip, setuptools or virtualenv). This creates potential for unpredictable bugs during install or runtime. Or the possibility for user to upgrade one of the components in the future and somehow break the application.
Also, uninstall is dirty and leaves stuff behind.
I'm a front-end developer with zero server-side experience. I'm trying to learn a little python for an app I'm building, and I literally cannot find anywhere that makes it easy to install easy_install. Everything I read is full of lingo I don't get, like using homebrew or PATHs. And pypi.python.org is TERRIBLY written and designed. So far it's only sent me in circles.
I'm looking for a simple set of instructions in the following format:
Go to x website and click x link
Type x into the terminal and run
Type x to be sure it's installed properly
Please for the benefit of myself and the whole internet, can someone provide this? I'm definitely up for learning how to do some things the hard way, but Python isn't something I need to know very thoroughly right now, and I imagine that's the case for others just looking to get their feet wet.
Assume I have Python installed, but not that I know anything else about using it.
(If there really is a resource out there like this that exists, let me know... I just haven't seen anything like it yet and I've been googling around for about an hour.)
Thank you!
easy_install is part of setuptools. For a while, distribute was a separate fork of setuptools that included its own easy_install, and you had to put a bit of thought into which one you wanted, but that's no longer an issue; the two have merged back into one project. So, the question is, how do you get setuptools?
If you're using Apple's pre-installed versions of Python, you already have setuptools, with a working easy_install, for all versions. You can also use easy_install-2.5, etc., for the earlier versions of Python that Apple also pre-installs. So there's nothing to do.
If you're using a Homebrew Python, it automatically installs setuptools by default, so again, nothing to do.
If you're using a third-party package manager that doesn't automatically install setuptools (as at least was true for MacPorts last time I checked), it probably has its own package for python32-setuptools or python32-easy-install or something like that.
Most of the "extra-batteries" distributions (ActiveState, Enthought, etc.) of Python similarly include setuptools, so again, nothing to do.
If you're using a Python.org binary, a custom-built Python with default configuration, etc., the standard setuptools instructions for "Unix-based Systems including Mac OS X" work fine.
If you installed Python somewhere you don't have write access, you will need to sudo the installation step, as in the second variant.
So:
wget https://bitbucket.org/pypa/setuptools/raw/bootstrap/ez_setup.py -O - | sudo python
And that's all there is to it.
All that being said, you almost never want to use easy_install, except to install two things:
readline, to replace the fake libedit-based support with real libreadline-based support. (And any other packages that don't work with pip, but this is the only really popular one.)
pip, so you never need to use easy_install again.
Most of the cases above that include setuptools also include pip; the one exception is Apple pre-installed Python, where sudo easy_install pip is the simplest way to get pip.
For the cases that don't come with either, the standard documentation for installing pip also works:
Install or upgrade setuptools (as above) if you have a version older than 0.7.
Download get-pip.py.
python get-pip.py
Again, sudo if you need to, and replace the python with python3.3 or python2.6 or /opt/local/mypython/bin/python or whatever to install for any non-default versions.
Finally, for upgrading, once you have any version of pip, and setuptools 0.7 or later, it's as easy as you could imagine:
pip install --upgrade setuptools pip
Again, sudo if necessary, and pip-3.3 or whatever if necessary.
Note that to make easy_install or pip actually useful, you may need a compiler toolchain. The easy way to do this is to install Xcode from the Mac App Store (free as of late 2013), launch Xcode, open Preferences, go to Downloads, and install the "Command Line Tools". This is sufficient for almost everything you'd ever want to do.
The one major exception is SciPy and related packages, for which you will also need a Fortran compiler. See this blog post for Python 2.x and this one for 3.x for details. If all of that looks scary to you, you may be happier using Enthought or one of the other pre-packaged scientific distributions.
One last thing: If you installed a non-Apple Python, and then upgraded your OS X (or Homebrew or MacPorts or Enthought or …) to a newer major version (e.g., from OS X 10.8 to 10.9), you may need some extra steps. For every case but OS X itself, they should be documented on the home page for whichever package manager or Python distribution you're using. For an OS X upgrade, reinstalling your third-party Python is usually the simplest solution if you run into a problem (after first verifying that you actually need a third-party Python in the first place), even if it means you have to reinstall your site packages.
The short correct answer is don't use EasyInstall.
Use pip!
A colleague of mine wants to use my python 2 code on his OS X (10.6) machine. My code imports several built-in python packages, including Tkinter and shelve, and also uses third-party packages, including numpy, scipy, matplotlib, and ipython.
I've encountered a few problems with OS X's built-in python. (IDLE doesn't work, for example*). I suspect I should install a more recent version of python, and a different version of Tk.
My questions:
Will having two different versions of python/Tk on the same machine cause problems?
I would like to associate the terminal commands 'python', 'ipython', and 'easy_install' with the more recent version of python. How should I do this?
When I install third-party packages like numpy using a .dmg file, how do I control which version of python numpy installs into?
Is there a better way to do this?
If this process goes well, I'd consider adding OS X instructions to my code's documentation, so I'd like to boil down this process to the simplest, most general approach.
*EDIT: Also, this
EDIT: Thank you everyone for the useful answers. My colleague tried MacPorts, which seems to work well, but has a few speedbumps. First we had to install Xcode from the system install disk. This is not a fast or lightweight install (several GB). Luckily we still had the disk! Once Xcode was installed, MacPorts was easy to install. Python and the python subpackages we needed were also easy to install, but he told me this installation took several hours. Presumably this delay is due to compilation? He had an easy time setting the MacPorts python as default. However, I think we have to change the 'Python Launcher' application by hand, this seems to still default to the system python.
Even though he has a working system now, I'm tempted to ask him to try one of the other solutions. I'm not sure all of my code's potential users will tolerate a multi-hour, multi-gigabyte installation.
I use brew to install all my libraries/compilers/interpreters.
To install python try this:
brew install python
Then add Python's binaries directory to your $PATH in your ~/.profile:
export PATH=`brew --prefix python`/bin:$PATH
I'd recommend you to install pip, virtualenv and virtualenvwrapper to have better control over your environment too.
Have you tried ActivePython?
It includes a package manager (PyPM) that, by default, installs into your home directory (eg: ~/Library/Python/2.7). Main scripts get symlinked in /usr/local/bin; use the included pythonselect to set the active Python version.
You don't have to bother installing .dmg packages, as PyPM is a binary package manager ... therefore you can install non-pure Python packages like NumPy without having to compile things yourself.
ActivePython can use Apple's Tcl/Tk or, if installed, ActiveTcl.
A "simplest, most general approach" in your documentation could be:
Install ActivePython 2.7
Open Terminal and type pypm-2.7 install matplotlib ipython
Using MacPorts, you can install python 2.6, 2.7, 3.1 and 3.2 at the same time, with their own packages, without ever touching the built-in python.
numpy, scipy, matplotlib, and ipython are also available as ports for most of those python versions.
Moreover, if you install the python_select port, you'll be able:
to choose which one of those (plus the built-in python) is the "default" python;
to install python packages through easy_install/pip for the "selected" python, if they're not available as ports.
Add virtualenv to the mix, and you'll have a very, very flexible Python development environment.
As for your questions:
Q1: with MacPorts, no. while not a frequent user, I've installed and used matplotlib in 2.6 and 2.7, switching between the two using python_select.
Q2: easy_install, pip, ipython will be "linked" to the python they were installed by. (but see tip 1)
Q3: it's easier to install one of the py{26,27,xx}-numpy ports, or pip install numpy under your python_select'ed python.
Q4: well, MacPorts is the best thing I know after APT on Debian/Ubuntu... :-)
Now, two tips if you try MacPorts:
MacPorts cleanly installs ports separately from the OS X installation, in an /opt/local directory, and each python version is installed in a /opt/local/Library/Frameworks/Python.framework/Versions/{2.5,2.6,2.7,...} directory. Using python_select cleanly switch the "python" command using links. BUT... the Versions/{2.5,2.6,2.7,...}/bin directory, where python scripts are installed, is not added to the PATH. Just adding: export PATH=/opt/local/Library/Frameworks/Python.framework/Versions/Current/bin:$PATH to your ~/.profile will always give you direct access to the scripts installed for the selected python.
to avoid bad surprises, I've added a echo Selected python is \"$(python_select -s)\" line to my ~/.profile, so I always know which is my currently selected python when opening a session... :-)
Regards,
Georges
In almost all cases, the best python to use is the one from http://python.org/. It sets up the paths correctly and doesn't overwrite anything. DMG package installs usually work automatically, as does python setup.py install, and it's not too hard to get setuptools to work. If you want per-user installs, it is easy to set up .pydistutils.cfg and python automatically recognizes the path install_lib = ~/Library/Python/$py_version_short/site-packages
An addendum regarding the usage of brew:
Since some time, brew install python will install python3.
If you intend to install python2, you want to use
brew install python#2
It is perfectly fine to install both python and python3 using brew!
Here is an old post that answers your questions too.
In general it is not a problem at all to have more than one python installation on your machine. You just have to watch out which one you are calling on the command line.
>> which python
... helps to identify where your python binary is located. The original Mac OS X python is usually at "/usr/bin/python"
I personally use the MacPorts python installation. It also supports you with the installation of modules. (see link above)
I have 4 versions of python on my MacBook Pro. 2 from the original install of OS X 10.6 and a subsequent update, then self installed copies of python 2.7 and 3.2. You can update the python command to point at any of the versions. They all install in separate directories and cause no problems with each other.
I'm not sure what will happen when you install from a .dmg file. I believe it will simply use whatever version python points to.
This post on superuser.com answers your questions on changing default paths.
Fedora Core 9 includes Python 2.5.1. I can use YUM to get latest and greatest releases.
To get ready for 2.6 official testing, I wanted to start with 2.5.4. It appears that there's no Fedora 9 YUM package, because 2.5.4 isn't an official part of FC9.
I downloaded 2.5.4, did ./configure; make; make install and wound up with two Pythons. The official 2.5.1 (in /usr/bin) and the new 2.5.4. (in /usr/local/bin).
None of my technology stack is installed in /usr/local/lib/python2.5.
It appears that I have several choices for going forward. Anyone have any preferences?
Copy /usr/lib/python2.5/* to /usr/local/lib/python2.5 to replicate my environment. This should work, unless some part of the Python libraries have /usr/bin/python wired in during installation. This is sure simple, but is there a down side?
Reinstall everything by running easy_install. Except, easy_install is (currently) hard-wired to /usr/bin/python. So, I'd have to fix easy_install first, then reinstall everything.
This takes some time, but it gives me a clean, new latest-and-greatest environment. But is there a down-side? [And why does easy_install hard-wire itself?]
Relink /usr/bin/python to be /usr/local/bin/python. I'd still have to copy or reinstall the library, so I don't think this does me any good. [It would make easy_install work; but so would editing /usr/bin/easy_install.]
Has anyone copied their library? Is it that simple?
Or should I fix easy_install and simply step through the installation guide and build a new, clean, latest-and-greatest?
Edit
Or, should I
Skip trying to resolve the 2.5.1 and 2.5.4 issues and just jump straight to 2.6?
Normally, you would only have one version of a python release installed. Since 2.5.1 and 2.5.4 are from the same release, copying your libraries should work fine. What you would need to watch out for, is that you now have /usr/bin/python, and /usr/local/bin/python in your path, and some utilities may get confused.
If you need to have both micro-releases installed at once, I would keep 2.5.4 out of your path altogether, or allow it to completely clobber the other (do so at your own risk though ;)
If you go with the former, you can also point 2.5.4 to your site-packages by using the PYTHONPATH environment variable.
Ubuntu takes a different route, and this is how you can handle different major releases. The python binary is given with the version appended:
/usr/bin/python -> python2.6
/usr/bin/python2.5
/usr/bin/python2.6
Each has their own /usr/lib/python2.X directory with versions of all the modules.
And lastly, you can further customize your setup by modifying your site.py
I suggest you create a virtualenv (or several) for installing packages into.
I've had similar experiences and issues when installing Python 2.5 on an older release of ubuntu that supplied 2.4 out of the box.
I first tried to patch easy_install, but this led to problems with anything that wanted to use the os-supplied version of python. I was often fiddling with the tool chain to fix different errors that might crop up with every install. Installing any python software via apt, or installing any software from apt that had a python easy_install script as part of the install, was often amusing. I'm sure I could probably have been more vigilant in patching easy_install, but I gave up.
Instead, I copied the library, and everything worked. As you say, there may be issues depending on what you have installed, but I didn't run into issues. Double-checking Python's site.py module, I did see that it operates entirely on relative paths, building absolute paths dynamically; this gave me some confidence to try the "copy everything" approach. I double-checked any .pth files, then went for it.