Develop Reference

How to make my python 3 desktop application portable?

I have tried portable python but the latest version is 3.2.5. (need 3.6+)
I cannot install libraries on it, even the get-pip.py doesn't work.
I'm trying to figure out how to make my project portable on windows systems that do not have python installed.
Also I want the minimum possible libraries(core python modules) to keep the project as lean as possible,

I would go with cx_Freeze - multiplatform module for freezing your Python script in a way that allows you to open it on other Windows machines even if they do not have Python installed. It got very nice and clear documentation also: http://cx-freeze.readthedocs.io/en/latest/ and works a bit better on Windows machines then alternative PyInstaller from my experience (which has interesting option of one-file-package, but in many cases leads to security warnings due to some dirty hacks used to obtain that feature).
However, it may not be enough if you are using some specific modules in your app, as for example matplotlib, dash, etc modules are very hard to pack correctly with Freezer.

I have found a solution to my own question after a couple of days.
I did not want to create an executable for my project but I wanted a portable python folder so that I can add libraries to it as and when I need.
The recent version of portable python is WinPython.
I had to delete some unnecessary files out of it though.
It's size is about 77 mb after extracting
https://winpython.github.io/
https://sourceforge.net/projects/winpython/files/WinPython_3.6/3.6.5.0/WinPython64-3.6.5.0Zero.exe/download

Installing pre-packaged Python modules on Windows

I need to distribute some code that was written in Python for Windows. Unfortunately, this code has many dependencies, and I'd like to make the installation as user-friendly as possible (read: doable even for people who don't even know how to use the command line). Is there a way I can build an installer which at he same time installs Python and the uses pip/easy_install to install the required modules as well? Can I package all this in a single executable, or do I need at least a second installation script? Thanks a lot.

If you just want an installer/binary, check out py2exe
http://www.py2exe.org/
There are a few known problems if your code includes certain resources but there is help for ensuring the includes worked http://www.py2exe.org/index.cgi/WorkingWithVariousPackagesAndModules

Deploy Python programs on Windows and fetch big library dependencies

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.

Python Code Completion

After using C# for long time I finally decided to switch to Python.
The question I am facing for the moment has to do about auto-complete.
I guess I am spoiled by C# and especially from resharper and I was expecting something similar to exist for Python.
My editor of choice is emacs and after doing some research I found autocomplete.pl, yasnippet and rope although it is not clear to me if and how they can be installed in a cygwin based system which is what I use since all the related documentation appears to be linux specific...
The version of emacs I currently use is 23.2.1 which bundles the python mode that although useful is far behind from whatever research has to offer.
My question to python users has to do about how common is autocomplete vs manual typing (using M-/ where possible) ?
I am thinking about just memorizing python build-in functions like len, append, extend etc. and revert close to a pre-autocomplete editing mode. How different such an approach is from what other pythonistas are doing?

I found this post
My Emacs Python environment
to be the most useful and comprehensive list of instructions and references on how to setup a decent Python development environment in Emacs regardless of OS platform. It is still a bit of work to setup but at least it covers the popular packages and components generally recommended for Python in Emacs that provide auto-completion functionality.
I loosely used this post as a guide to do the setup on my Windows machine with Emacs 23.2.1 and Python 2.6.5. Although, I also have Cygwin installed in some cases instead of running the *nix shell commands mentioned in the post, I just download the packages via a web browser, unzip them with 7zip, and copy them to my Emacs' plugin directory.
Also, to install Pymacs, Rope, and Ropemacs, I used Python's EasyInstall package manager. To use it, I downloaded and installed the setuptools package using the Windows install version. Once installed, at the command line, cd to their respective download locations and run the command
easy_install .
instead of the shell commands shown in the post.
Generally, I saved any *.el files in my ~\.emacs.d\plugins (e.g. in %USERPROFILE%\Application Data\.emacs.d\) and then updated my .emacs file to reference them as documented in the post.
Despite all this, on occasion, I've used DreamPie since it does have overall better auto-completion out of the box than my Emacs setup.

I'm spoiled by Intellisense too. The PyDev extensions for Eclipse offer a pretty good auto-complete substitute.

I find that PyDev + Eclipse can meet most of my needs. There is also PyCharm from the Intellij team. PyCharm has the added advantage of smooth integration with git.

I've been using PyScripter, an IDE for Windows, for a while now, and have found it very good. It has autocompletion among many other features. It's written in Delphi -- not that there's anything wrong with that -- it just bothers me a bit, though...

Take a look at Spyderlib, support most of the features including code completion

IMO, by far the easiest way to take advantage of the python tools available for emacs is to take advantage of the defaults that are all set up at:
https://github.com/gabrielelanaro/emacs-for-python
I actually took the time to get pymacs and ropemacs and python-mode all working independently before finding that little gem, and now I rely on it entirely for all my python based customizations. If you are new, I would definitely start there.

Recommendations for Python development on a Mac?

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.