I want to install PyPy on my Ubuntu and I want it to be installed system-wide so I could call PyPy in terminal everywhere like: pypy main.py. I also want to have standard python and pip available.
I'm not a very experienced Linux user yet so I'm lost.
As #keith-thompson says, you can do sudo apt install pypy pypy-dev. If you want a more up-to-date version you can do snap install pypy pypy-dev. Another way to get a working environment is to use conda, as per this link. The advantage of conda is that you can easily install pre-built packages such as numpy, sciy (coming soon), and more. If you use the first recipes, pip install will currently have to build many packages from source.
Note that pip is never "available anywhere", it is tied to the particular python instance, and installs packages into a path for that specific instance. Thus the pip you use for python2 is different than the pip you use for python3, likewise for pypy.
This is probably a really dumb question but I am stuck and wasting too much time on this so I would SO appreciate any help.
I am using a RHEL 7 box and installed Apache Zeppelin on it. Everything works except for the life of me I can't import Python packages such as Pandas.
I realized I didn't have PIP so I installed it with these steps: https://pip.pypa.io/en/stable/installing/ (notice I had to use the "--user" argument for the command "python get-pip.py").
Finally, I did "pip install pandas --user" which worked perfectly. I then go into my Zeppelin notebook and I cannot import pandas, even after restarting the Python interpreter.
I did some research and I think the problem is that "which python" and "which pip" are installed in different directories as the former results in "/usr/bin/python" while the latter in "~/.local/bin/pip".
So I suspect the packages installed with pip are basically getting loaded into a different version of python? If it helps, when I do "whereis python" I get 5 different results such as "/usr/bin/python" and "/usr/bin/python2.7" etc.
First thing to understand is: Python packages aren't installed globally, every installed Python has its own set of packages. BTW, pip being a Python package with a script is also not global. If you have a few different pythons you need different pips for them. I don't know Apache Zeppelin so I cannot guess if it uses the system Python (/usr/bin/python) or has its own Python; in the latter case you need to install pip specifically for Zeppelin so its pip install packages available for Zeppelin.
To investigate to what Python pip installs packages you need to find out under what python it runs. Start with shebang:
head -1 `which pip`
The command will prints something like ~/.local/bin/python. If it's not the version of Python you need to install packages for you need to install a different pip using that Python.
The most complex case would be if the shebang is PATH-dependent, something like #!/usr/bin/env python. In that case pip runs Python that you can find with which python.
PS. AFAIK the simplest way to install pip at RedHat is dnf install python-pip.
phd's answer was very helpful but I found that it was just a matter of using the root account to install the python packages. Then my Zeppelin was able to see any packages.
I have a variety of different Python versions installed on my Windows system- a 2.7 version, a 3.5 version, and a 3.6 version (there are a bunch of different packages that only work with one version, or are too buggy in the 3.6 version, etc.).
Long story short, I'm trying to keep my all my pips and python.exes in order. I've added my C:/Python35 and C:/Python36 and their Scripts folders to my path, but I also want to make sure that I am using the right pip from my command line (for example, I don't want to pip install pyinstaller to the 3.6 version, since Python 3.6 doesn't play well with pyinstaller as of right now.
I see that inside my Python3x/Scripts/ folder, there are three different pips available: pip, pip3.5, and pip3.
So whenever I want to install a module for 3.5, I plan to issue the following command pip3.5 install package_name. Whenever I want to install something for 3.6, I'd use pip or pip3. Seems like a decent enough plan to me.
However, can anyone confirm if the three pips are all the same executable? If so, I'd like to delete pip and pip3 so that I don't accidentally confuse it with my Python 3.6 pip- is this acceptable practice or am I missing something? This SO post provides some insights but doesn't explain why there's multiple pips in the same folder. Also, why are three separate pips provided? Is it simply for convenience from the command line?
Within the same python installation all the different pip files you find should be the same executable, there is the multiple versions simply to help keep everything in order if there are multiple installs of python on a single computer.
I personally only have the main version of python I use for development set to my PATH variable on my windows laptop and then if I need to do anything to a different python I instead link directly to the necessary file with something like C:\Python36\Scripts\pip3 install natsort but that is simply personal preference and my way of organizing.
If you do have them all on path you can then simply call out pip3.6 install <package name> or whatever python version you are using
The difference between them is that each one install the package in its own folder, for example if i type pip install Django, it will be placed for python 2 version, but is a little bit complex when you have multiple version of python3 like you showed, the solution: Don't delete the files and makevirtualenv when you're working, that avoid problems.
This prevents dependency issues with different versions of Python. You also check out virtualenvwrapper which is a convenient way to manage your virtual environments
If you want to manage the version with virtualenv
virtualenv python2_project -p usr/bin/python2.7
virtualenv p35_project -p usr/bin/python3.5
virtualenv p3x_project -p usr/bin/python3.x
I'm new to python. I installed python3.4 on OsX some time ago and now I installed python3.5 using the installer you can download from the site.
I noticed that in /Library/Frameworks/Python.framework/Versions/ I have both 3.4 and 3.5. I wasn't expecting that - I was expecting an upgrade where 3.5 replaced 3.4
So, if I run python3.5 and I try to import the packages I installed when using 3.4, they are not found. Furthermore if I use pip install to reinstall them, it says the packages are already installed, therefore I can see that it's pointing to the 3.4 version.
What I'm doing wrong? I supposed that installing the new python should upgrade my existing installation (bringing installed packages with it) rather than add a completely new install.
I'm not sure what to do now:
Should I keep every old version?
Should I manually change which pip
is used every time?
(is there a more streamlined update procedure
for next time?)
A lot of Python packages are 3rd party. The community is always moving forward and this may take some getting used to!
That said, my recommendation is to start using venv. It gives you (mostly) isolated Python virtual environments in which you can install whatever packages you like (via pip) without polluting the global installation. This also allows you to configure various virtual environments with varying packages and versions. It's really handy!
Link:
https://docs.python.org/3.4/library/venv.html
I'm starting to learn python and loving it. I work on a Mac mainly as well as Linux. I'm finding that on Linux (Ubuntu 9.04 mostly) when I install a python module using apt-get it works fine. I can import it with no trouble.
On the Mac, I'm used to using Macports to install all the Unixy stuff. However, I'm finding that most of the python modules I install with it are not being seen by python. I've spent some time playing around with PATH settings and using python_select . Nothing has really worked and at this point I'm not really understanding, instead I'm just poking around.
I get the impression that Macports isn't universally loved for managing python modules. I'd like to start fresh using a more "accepted" (if that's the right word) approach.
So, I was wondering, what is the method that Mac python developers use to manage their modules?
Bonus questions:
Do you use Apple's python, or some other version?
Do you compile everything from source or is there a package manger that works well (Fink?).
The most popular way to manage python packages (if you're not using your system package manager) is to use setuptools and easy_install. It is probably already installed on your system. Use it like this:
easy_install django
easy_install uses the Python Package Index which is an amazing resource for python developers. Have a look around to see what packages are available.
A better option is pip, which is gaining traction, as it attempts to fix a lot of the problems associated with easy_install. Pip uses the same package repository as easy_install, it just works better. Really the only time use need to use easy_install is for this command:
easy_install pip
After that, use:
pip install django
At some point you will probably want to learn a bit about virtualenv. If you do a lot of python development on projects with conflicting package requirements, virtualenv is a godsend. It will allow you to have completely different versions of various packages, and switch between them easily depending your needs.
Regarding which python to use, sticking with Apple's python will give you the least headaches, but If you need a newer version (Leopard is 2.5.1 I believe), I would go with the macports python 2.6.
Your question is already three years old and there are some details not covered in other answers:
Most people I know use HomeBrew or MacPorts, I prefer MacPorts because of its clean cut of what is a default Mac OS X environment and my development setup. Just move out your /opt folder and test your packages with a normal user Python environment
MacPorts is only portable within Mac, but with easy_install or pip you will learn how to setup your environment in any platform (Win/Mac/Linux/Bsd...). Furthermore it will always be more up to date and with more packages
I personally let MacPorts handle my Python modules to keep everything updated. Like any other high level package manager (ie: apt-get) it is much better for the heavy lifting of modules with lots of binary dependencies. There is no way I would build my Qt bindings (PySide) with easy_install or pip. Qt is huge and takes a lot to compile. As soon as you want a Python package that needs a library used by non Python programs, try to avoid easy_install or pip
At some point you will find that there are some packages missing within MacPorts. I do not believe that MacPorts will ever give you the whole CheeseShop. For example, recently I needed the Elixir module, but MacPorts only offers py25-elixir and py26-elixir, no py27 version. In cases like these you have:
pip-2.7 install --user elixir
( make sure you always type pip-(version) )
That will build an extra Python library in your home dir. Yes, Python will work with more than one library location: one controlled by MacPorts and a user local one for everything missing within MacPorts.
Now notice that I favor pip over easy_install. There is a good reason you should avoid setuptools and easy_install. Here is a good explanation and I try to keep away from them. One very useful feature of pip is giving you a list of all the modules (along their versions) that you installed with MacPorts, easy_install and pip itself:
pip-2.7 freeze
If you already started using easy_install, don't worry, pip can recognize everything done already by easy_install and even upgrade the packages installed with it.
If you are a developer keep an eye on virtualenv for controlling different setups and combinations of module versions. Other answers mention it already, what is not mentioned so far is the Tox module, a tool for testing that your package installs correctly with different Python versions.
Although I usually do not have version conflicts, I like to have virtualenv to set up a clean environment and get a clear view of my packages dependencies. That way I never forget any dependencies in my setup.py
If you go for MacPorts be aware that multiple versions of the same package are not selected anymore like the old Debian style with an extra python_select package (it is still there for compatibility). Now you have the select command to choose which Python version will be used (you can even select the Apple installed ones):
$ port select python
Available versions for python:
none
python25-apple
python26-apple
python27 (active)
python27-apple
python32
$ port select python python32
Add tox on top of it and your programs should be really portable
Please see Python OS X development environment. The best way is to use MacPorts. Download and install MacPorts, then install Python via MacPorts by typing the following commands in the Terminal:
sudo port install python26 python_select
sudo port select --set python python26
OR
sudo port install python30 python_select
sudo port select --set python python30
Use the first set of commands to install Python 2.6 and the second set to install Python 3.0. Then use:
sudo port install py26-packagename
OR
sudo port install py30-packagename
In the above commands, replace packagename with the name of the package, for example:
sudo port install py26-setuptools
These commands will automatically install the package (and its dependencies) for the given Python version.
For a full list of available packages for Python, type:
port list | grep py26-
OR
port list | grep py30-
Which command you use depends on which version of Python you chose to install.
I use MacPorts to install Python and any third-party modules tracked by MacPorts into /opt/local, and I install any manually installed modules (those not in the MacPorts repository) into /usr/local, and this has never caused any problems. I think you may be confused as to the use of certain MacPorts scripts and environment variables.
MacPorts python_select is used to select the "current" version of Python, but it has nothing to do with modules. This allows you to, e.g., install both Python 2.5 and Python 2.6 using MacPorts, and switch between installs.
The $PATH environment variables does not affect what Python modules are loaded. $PYTHONPATH is what you are looking for. $PYTHONPATH should point to directories containing Python modules you want to load. In my case, my $PYTHONPATH variable contains /usr/local/lib/python26/site-packages. If you use MacPorts' Python, it sets up the other proper directories for you, so you only need to add additional paths to $PYTHONPATH. But again, $PATH isn't used at all when Python searches for modules you have installed.
$PATH is used to find executables, so if you install MacPorts' Python, make sure /opt/local/bin is in your $PATH.
There's nothing wrong with using a MacPorts Python installation. If you are installing python modules from MacPorts but then not seeing them, that likely means you are not invoking the MacPorts python you installed to. In a terminal shell, you can use absolute paths to invoke the various Pythons that may be installed. For example:
$ /usr/bin/python2.5 # Apple-supplied 2.5 (Leopard)
$ /opt/local/bin/python2.5 # MacPorts 2.5
$ /opt/local/bin/python2.6 # MacPorts 2.6
$ /usr/local/bin/python2.6 # python.org (MacPython) 2.6
$ /usr/local/bin/python3.1 # python.org (MacPython) 3.1
To get the right python by default requires ensuring your shell $PATH is set properly to ensure that the right executable is found first. Another solution is to define shell aliases to the various pythons.
A python.org (MacPython) installation is fine, too, as others have suggested. easy_install can help but, again, because each Python instance may have its own easy_install command, make sure you are invoking the right easy_install.
If you use Python from MacPorts, it has it's own easy_install located at: /opt/local/bin/easy_install-2.6 (for py26, that is). It's not the same one as simply calling easy_install directly, even if you used python_select to change your default python command.
Have you looked into easy_install at all? It won't synchronize your macports or anything like that, but it will automatically download the latest package and all necessary dependencies, i.e.
easy_install nose
for the nose unit testing package, or
easy_install trac
for the trac bug tracker.
There's a bit more information on their EasyInstall page too.
For MacPython installations, I found an effective solution to fixing the problem with setuptools (easy_install) in this blog post:
http://droidism.com/getting-running-with-django-and-macpython-26-on-leopard
One handy tip includes finding out which version of python is active in the terminal:
which python
When you install modules with MacPorts, it does not go into Apple's version of Python. Instead those modules are installed onto the MacPorts version of Python selected.
You can change which version of Python is used by default using a mac port called python_select. instructions here.
Also, there's easy_install. Which will use python to install python modules.
You may already have pip3 pre-installed, so just try it!
Regarding which python version to use, Mac OS usually ships an old version of python. It's a good idea to upgrade to a newer version. You can download a .dmg from http://www.python.org/download/ . If you do that, remember to update the path. You can find the exact commands here http://farmdev.com/thoughts/66/python-3-0-on-mac-os-x-alongside-2-6-2-5-etc-/
I use easy_install with Apple's Python, and it works like a charm.
Directly install one of the fink packages (Django 1.6 as of 2013-Nov)
fink install django-py27
fink install django-py33
Or create yourself a virtualenv:
fink install virtualenv-py27
virtualenv django-env
source django-env/bin/activate
pip install django
deactivate # when you are done
Or use fink django plus any other pip installed packages in a virtualenv
fink install django-py27
fink install virtualenv-py27
virtualenv django-env --system-site-packages
source django-env/bin/activate
# django already installed
pip install django-analytical # or anything else you might want
deactivate # back to your normally scheduled programming