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I have some small Python programs which depend on several big libraries, such as:
NumPy & SciPy
matplotlib
PyQt
OpenCV
PIL
I'd like to make it easier to install these programs for Windows users. Currently I have two options:
either create huge executable bundles with PyInstaller, py2exe or similar tool,
or write step-by-step manual installation instructions.
Executable bundles are way too big. I always feel like there is some magic happening, which may or may not work the next time I use a different library or a new library version. I dislike wasted space too. Manual installation is too easy to do wrong, there are too many steps: download this particular interpreter version, download numpy, scipy, pyqt, pil binaries, make sure they all are built for the same python version and the same platform, install one after another, download and unpack OpenCV, copy its .pyd file deep inside Python installation, setup environment variables and file asssociations... You see, few users will have the patience and self-confidence to do all this.
What I'd like to do: distribute only a small Python source and, probably, an installation script, which fetches and installs all the missing dependencies (correct versions, correct platform, installs them in the right order). That's a trivial task with any Linux package manager, but I just don't know which tools can accomplish it on Windows.
Are there simple tools which can generate Windows installers from a list of URLs of dependencies1?
1 As you may have noticed, most of the libraries I listed are not installable with pip/easy_install, but require to run their own installers and modify some files and environment variables.
npackd exists http://code.google.com/p/windows-package-manager/ It could be done through here or use distribute (python 3.x) or setuptools (python 2.x) with easy_install, possibly pip (don't know it's windows compatibility). But I would choose npackd because PyQt and it's unusual setup for pip/easy_install (doesn't play with them nicely, using a configure.py instead of setup.py). Though you would have to create your own repo for npackd to use for some of them. I forget what is contributed in total for python libs with it.
AFAIK there is no tool (and I'd assume you googled), so you must make one yourself.
Fetching the proper library versions seems simple enough -- using python's ftplib you can fetch the proper installers for every library. How would you know which version is compatible with the user's python? You can store different lists of download URLs, each for a different python version (this method came off the top of my head and there is probably a better way; not that it matters much if it's simple and it works).
After you figure out how to make each installer run, you can py2exe your installer script, and even use it to fetch the program itself.
EDIT
Some Considerations
There are a couple of things that popped into my mind just as I posted:
First, some pseudocode (how I would approach it, anyway)
#first, we check modules
try:
import numpy
except ImportError:
#flag numpy for installation
#lather, rinse repeat for all dependencies
#next we check version compatibility -- note that if a library version you need
#is not backwards-compatible, you're in DLL hell, and there is little we can do.
<insert version-checking code here>
#once you have your unavailable dependencies, you install them
import ftplib
<all your file-downloading here>
#now you install. sorry I can't help you here.
There are a few things you can do to make your utility reusable --
put all URL lists, minimum version numbers, required library names etc in config files
Write a script which helps you set up an installer
Py2exe the installer-maker-script
Sell it
Even better, release it under GPL so we can all feast upon fruits of your labours.
I have a similar need as you, but in addition I need the packaged application to work on several platforms. I'm currently exploring the currently available solutions, here are a few interesting ones:
Use SnakeBasket, which wraps around Pip and add a recursive dependency resolution plus a heuristic to choose the right version when there are conflicts.
Package all dependencies as an egg, but not your sourcecode which will still be editable: https://stackoverflow.com/a/528064/1121352
Package all dependencies in a zip file and directly import the modules on the fly: Cross-platform alternative to py2exe or http://davidf.sjsoft.com/mirrors/mcmillan-inc/install1.html
Using buildout: http://www.buildout.org/en/latest/install.html
Using virtualenv with virtualenv-tools (instead of "relocate")
If your main problem when freezing your code using PyInstaller or similar is that you end up with a big single file, you can customize the process so that you get several files, one for each dependency, instead of one big executable.
I will update here if I find something that fills my bill.
I have a wxPython application that is almost done & I would like to place it in my portfolio. I have to consider when someone attempts to run my app that they may not have Python, or wxPython, so if they just click the main script/python file its not going to run, right?
How should I distribute my app (how do you distribute ur apps) so that it can be run & also so that it could be run on the 3 major OS's (Unix, Windows, MacOSX)?
I know of py2exe for releasing under windows, but what can I use for Unix & MacOSX to compile the program? Whats the easiest way?
Use Gui2exe and compress with UPX to get unpacked size down.
For a setup file(exe) with uinstall info Inno-Setup is good.
I have use this with wxpython several times and got it to work on all windows versions.
For Gui2exe use optimize(2) - compressed(2) - Bundle files(3)
Bundle files(3) is the most stable,
Bundle files(1) make one big exe-file.
For one exe-file is better as last step to use Inno-Setup
You can use py2exe for Windows and py2app for Mac. PyInstaller works for Windows and Linux. Personally, I use GUI2Exe, which wraps all three and makes them a little easier to use. Note: I don't have a Mac, so I haven't tried it with that. You can check out my series on freezing Python here:
http://www.blog.pythonlibrary.org/2010/08/10/a-pyinstaller-tutorial-build-a-binary-series/
http://www.blog.pythonlibrary.org/2010/07/31/a-py2exe-tutorial-build-a-binary-series/
http://www.blog.pythonlibrary.org/2010/08/31/another-gui2exe-tutorial-build-a-binary-series/
There are a couple others on the blog too.
I suggest both, script for all platforms and frozen binary for lazy windows users.
To answer your latest question, you don't compile python. Python is an interpreted language, it gets compiled on the fly when run. A python frozen binary is actually the python interpreter with your script hardcoded in it. And frozen binaries are windows-only, AFAIK. Besides, Unix and MacOS (usually) come with python pre-installed.
I once read about minimal python installation without a lot of the libraries that come with the python default installation but could not find it on the web...
What I want to do is to just pack a script with the python stuff required to execute it and make portable.
Does any one know about something like that?
Thanks
Micro Python is actively maintained and has been ported to a bunch of microcontrollers.
For other small implementations, you might also want to check out tinypy or PyMite.
If you don't care about size, but really just want an easy way to distribute a python program, consider PyInstaller or one of the others on this list.
Portable python might do what you want. It's a python installation for USB thumb drives.
There's now finally Micro Python, claiming to be full reimplementation of Python 3 core, fitting even into medium-size 32bit microcontrollers. API will be different of course, so C modules will require porting. Project is funded via KickStarter, source code will be released some time after the campaign (request for consideration was made to author to not delay release of the source, to help bootstrap Micro Python community sooner).
http://micropython.org/
You can also look for already installed instances.
OpenOffice / LibreOffice
Look at the environment variable UNO_PATH or into the default install directories, for example for Windows and LO5
%ProgramFiles(x86)%\LibreOffice 5\program\python.exe
Gimp
look into the default install directories, for example for Windows
C:\Program Files\GIMP 2\Python
and so on...
I'm a .NET developer who knows very little about Python, but want to give it a test drive for a small project I'm working on.
What tools and packages should I install on my machine? I'm looking for a common, somewhat comprehensive, development environment.
I'll likely run Ubuntu 9.10, but I'm flexible. If Windows is a better option, that's fine too.
Edit: To clarify, I'm not looking for the bare minimum to get a Python program to run. I wouldn't expect a newbie .NET dev to use notepad and a compiler. I'd recommend Visual Studio, NUnit, SQL Server, etc.
Your system already has Python on it. Use the text editor or IDE of your choice; I like vim.
I can't tell you what third-party modules you need without knowing what kind of development you will be doing. Use apt as much as you can to get the libraries.
To speak to your edit:
This isn't minimalistic, like handing a .NET newbie notepad and a compiler: a decent text editor and the stdlib are all you really need to start out. You will likely need third-party libraries to develop whatever kind of applications you are writing, but I cannot think of any third-party modules all Python programmers will really need or want.
Unlke the .NET/Windows programming world, there is no one set of dev tools that stands above all others. Different people use different editors a whole lot. In Python, a module namespace is fully within a single file and project organization is based on the filesystem, so people do not lean on their IDEs as hard. Different projects use different version control software, which has been booming with new faces recently. Most of these are better than TFS and all are 1000 times better than SourceSafe.
When I want an interactive session, I use the vanilla Python interpreter. Various more fancy interpreters exist: bpython, ipython, IDLE. bpython is the least fancy of these and is supposed to be good about not doing weird stuff. ipython and IDLE can lead to strange bugs where code that works in them doens't work in normal Python and vice-versa; I've seen this first hand with IDLE.
For some of the tools you asked about and some others
In .NET you would use NUnit. In Python, use the stdlib unittest module. There are various third-party extensions and test runners, but unittest should suit you okay.
If you really want to look into something beyond this, get unittest2, a backport of the 2.7 version of unittest. It has incorporated all the best things from the third-party tools and is really neat.
In .NET you would use SQL Server. In Python, you may use PostgreSQL, MySQL, sqlite, or some other database. Python specifies a unified API for databases and porting from one to another typically goes pretty smoothly. sqlite is in the stdlib.
There are various Object Relational Models to make using databases more abstracted. SQLAlchemy is the most notable of these.
If you are doing network programming, get Twisted.
If you are doing numerical math, get numpy and scipy.
If you are doing web development, choose a framework. There are about 200000: Pylons, zope, Django, CherryPy, werkzeug...I won't bother starting an argument by recommending one. Most of these will happily work with various servers with a quick setting.
If you want to do GUI development, there are quite a few Python bindings. The stdlib ships with Tk bindings I would not bother with. There are wx bindings (wxpython), GTK+ bindings (pygtk), and two sets of Qt bindings. If you want to do native Windows GUI development, get IronPython and do it in .NET. There are win32 bindings, but they'll make you want to pull your hair out trying to use them directly.
In order to reduce the chance of effecting/hosing the system install of python, I typically install virtualenv on the ubuntu python install. I then create a virtualenv in my home directory so that subsequent packages I install via pip or easy_install do not effect the system installation. And I add the bin from that virtualenv to my path via .bashrc
$ sudo apt-get install python-virtualenv
$ virtualenv --no-site-packages ~/local
$ PATH=~/local/bin:$PATH #<----- add this to .bashrc to make it permanent
$ easy_install virtualenv #<--- so that project environments are based off your local environment rather than the system, probably not necessary
Install your favorite editor, I like emacs + rope, but editors are a personal preference and there are plenty of choices.
When I start a new project/idea I create a new virtual environment for that project, so that I don't effect dependencies anywhere else. Since I would hate for some of my projects to break due to an upgrade of a library both that project and the new one depends on.
~/projects $ virtualenv --no-site-packages my_new_project.env
~/projects/my_new_project.env $ source bin/activate
(my_new_project.env)~/projects/my_new_project.env $ easy_install paste ipython #whatever else I think I need
(my_new_project.env)~/projects/my_new_project.env $ emacs ./ & # start hacking
When creating a new package...in order to have something that will be easy_installable/pippable use paster create
(my_new_project.env)~/projects/my_new_project.env$ paster create new_package
(my_new_project.env)~/projects/my_new_project.env/new_package$ python setup.py develop new_package
That's the common stuff as far as I can think of it. Everything else would be editor/version control tool specific
Since I'm accustomed to Eclipse, I find Eclipse + PyDev convenient for Python. For quick computations, Idle is great.
I've used Python on Windows and on Ubuntu, and Linux is much cleaner.
If you launch a terminal and type python you'll get an interpreter, where you can start trying stuff.
Just in case you haven't seen it, check out the book Dive Into Python, is free on-line.
http://www.diveintopython.org/
Follow the examples in the book using the interpreter.
For storing your work you could use any editor; Vim or EMACS could be the most powerful, but also the most difficult to learn at first. If you want a more "traditional" IDE, you could try WingIDE.
http://www.wingware.com/
After you start to get more comfortable with python you should try an enhanced interpreter; try ipython.
http://ipython.scipy.org/moin/
When you start to develop a more serious project you'll need to get additional modules. Here you have two options; 1) Use your distribution tools to install additional modules; or 2) Download the modules you need directly from their sites and install them manually. You'll be responsible to upgrade them of course.
You'll have to decide for yourself which way to go. Personally I prefer to download and install additional modules manually.
Python (duh), setuptools or pip, virtualenv, and an editor. I suggest geany, but that's just me. And of course, any other Python modules you'll need.
Getting to Python from .NET world
Jumping into the Linux world from a .NET / WIndows background can be a bit disconcerting (but I do encourage you to keep trying Linux)
But I would suggest to anyone coming from Windows, to stick with Windows for a little while. goto www.Activestate.com and download their Python package - it includes the full win32com extentions by Mark Hammond and it also includes a complete, fast IDE "pythonwin"
I have done real professional development with just this setup alone on a windows box - one 14MB .msi and off you go !
Now to use Python on the DLR (Dynamic common language runtime) you need to download IronPython. THis is a seperate interpreter, that was also originally written by Mark Hammond at Microsoft and is at ironpython.org.
With this you can run code like (from wikipedia) ::
import clr
clr.AddReference("System.Windows.Forms")
from System.Windows.Forms import MessageBox
MessageBox.Show("Hello World")
Now you can access any .NET code from python.
If you're just starting out with Python, I'd actually argue against bringing in the complexity of virtualenv (which I think can be pretty overwhelming), at least until you've got a firm grasp of Python basics (especially regarding library/dependency management).
If you're using Ubuntu and the Gnome desktop environment, gedit is the default (gui) text editor, and has great support for Python built in. So my recommendation is to start with the pre-installed Python and gedit (which is pretty extensible on its own).
You don't need much. Python comes with "Batteries Included."
Visual Studio == IDLE. You already have it. If you want more IDE-like environment, install Komodo Edit.
NUnit == unittest. You already have it in the standard library.
SQL Server == sqlite. You already have it in the standard library.
Stop wasting time getting everything ready. It's already there in the basic Python installation.
Get to work.
Linux, BTW, is primarily a development environment. It was designed and built by developers for developers. Windows is an end-user environment which has to be supplemented for development.
Linux was originally focused on developers. All the tools you need are either already there or are part of simple yum or RPM installs.
You would probably like to give NetBeans Python IDE a shot. You can choose to use either Windows/Linux.
Database: sqlite (inbuilt). You might want SQLAlchemy though.
GUI: tcl is inbuilt, but wxPython or pyQt are recommended.
IDE: I use idle (inbuilt) on windows, TextMate on Mac, but you might like PyDev. I've also heard good things about ulipad.
Numerics: numpy.
Fast inline code: lots of options. I like boost weave (part of scipy), but you could look into ctypes (to use dlls), Cython, etc.
Web server: too many options. Django (plus Apache) is the biggest.
Unit testing: inbuilt.
Pyparsing, just because.
BeautifulSoup (or another good HTML parser).
hg, git, or some other nice VC.
Trac, or another bug system.
Oh, and StackOverflow if you have any questions.
Pycharm Community is worth to try.
I bought a low-end MacBook about a month ago and am finally getting around to configuring it for Python. I've done most of my Python work in Windows up until now, and am finding the choices for OS X a little daunting. It looks like there are at least five options to use for Python development:
"Stock" Apple Python
MacPython
Fink
MacPorts
roll-your-own-from-source
I'm still primarily developing for 2.5, so the stock Python is fine from a functionality standpoint. What I want to know is: why should I choose one over the other?
Update:
To clarify, I am looking for a discussion of the various options, not links to the documentation. I've marked this as a Community Wiki question, as I don't feel there is a "correct" answer. Thanks to everyone who has already commented for their insight.
One advantage I see in using the "stock" Python that's included with Mac OS X is that it makes deployment to other Macs a piece of cake. I don't know what your deployment scenario is, but for me this is important. My code has to run on any number of Macs at work, and I try to minimize the amount of work it takes to run my code on all of those systems.
I would highly recommend using MacPorts with Porticus for managing your Python installation. It takes a while to build everything, but the advantage is that whatever you build yourself will be built against the same libraries, so you won't have to futz around with statically linked shared objects, etc. if you want your Python stuff to work with Apache, PostgreSQL, etc.
If you choose to go this way, remember to install the python_select port and use it to make your system use the Python installed from MacPorts.
As an added bonus, MacPorts has packages for most main-stream Python eggs, so if you should be able to have MacPorts keep you up-to-date with the latest versions of all that stuff :)
Here's some helpful info to get you started. http://www.python.org/download/mac/
Depends what you are using python for. If you are using MacOS funitionality and things like PyObjC you are probably best of with MacPython or the python provided by Apple.
I use Python on my Mac mostly for development of server side applications which later will run on FreeBSD & Linux boxes. For that I have used fink python for a few years and ever since MacPorts python. With mac ports it is simple to add required c modules (like database driver etc). It's also easy to keep two python Versions (2.5 & 2.6 in my case) around.
I used "compile your own" python to test pre-3.0 python but generally I find managing dependencies to c modules painfull if done by hand.
Thanks to easy_install installing pure python modules is fast and easy for all the options mentioned above.
I was never very much an IDE person. For development I use command line subversion installed by MacPorts, Textmate and occasionaly Expandrive do directly access files on servers. I personally are very dependent on Bicyclerepairman for Textmade to handle my refactoring needs.
Others seem to be very happy with Eclipse & Pydev.
How about EPD from Enthought? Yes, it's large but it is a framework build and includes things like wxPython, vtk, numpy, scipy, and ipython built-in.
I recommend using Python Virtual environments, especially if you use a Timecapsule because Timecapsule will back everything up, except modules you added to Python!
Based on the number of bugs and omissions people have been encountering in Leopard python (just here on SO!), I couldn't recommend that version. e.g., see:
Why do I get wrong results for hmac in Python but not Perl?
Problems on select module on Python 2.5
I would choose MacPorts.
It does not eliminate your existing python supplied by Apple since it installs by default in /opt/local/bin (plays nice with it) and plus it is easy to download and install additional python modules (even binary modules that you need to compile!). I use Porticus GUI to maintain my MacPorts installed list of packages, including python.
In my windows environment I use Eclipse and PyDev, which works quite well together, even if it's a bit sparse. Apparently the exact same environment is available for the Mac as well, so I suggest downloading Eclipse and using the internal update software function to update PyDev with the URL http://pydev.sourceforge.net/updates/. To look further into PyDev, look here.
Apple's supplied python is quite old – my tiger install has 2.3.5. This may not be a problem for you, but you would be missing out on a lot. Also, there is a risk that Apple will update it. I'm not sure if moving from 2.3.5 to (say) 2.4 would cause code to break, but I guess it's possible. This happened to perl people recently: http://developers.slashdot.org/article.pl?sid=09/02/18/1435227
Macpython is a framework build (as is Apple's, I believe). To be honest, I'm not sure exactly what that means, but it's a prerequisite for some modules, in particular wxPython. If you get python from macports or fink, you will not be able to run wxPython (unless you run it through X11).
And guess what was forgotten by every answer here ... ActivePython.
No compilation required, even for third-party modules such as numpy, lxml, pyqt and thousands of others.
I recommend python (any python?) plus the ipython shell. My most recent experience with MacPython was MacPython 2.5, and I found IDLE frustrating to use as an editor. It's not very featureful, and its' very slow to scroll large quantities of output.