Rookie software developer here. I’m working on a Python module that harnesses some functionality from the FFmpeg framework - specifically, the ebur128 filter function. Ideally the module will stand on its own as an independent, platform agnostic tool for verifying that audio clips comply with EBU loudness standards. It’s being designed so that end users need only perform one simple, (hopefully!) painless installation procedure, which will encompass the installation of both the FFmpeg libraries and my Python wrapper/GUI.
I apologize for the rather vague question, but does anyone have general advice for creating Python module with external dependencies, or specific advice for standardizing the FFmpeg installation across platforms? Distutils seems pretty helpful – are there other guidelines or standard practices for developing a neatly packaged Python tool? I want to minimize any installation headaches for end users.
Thanks very much.
For Windows
I think it will be easy to find ffmpeg binaries that work on any system, just like for Qt or whatever GUI library you are using. You can ship these binaries with your project and things will work (you may want to distinguish 32 bit and 64 bit systems, though).
It looks like you want to create a software that is self-contained and easily installable for end-users. Inkscape is such an example -- its installer contains Python and all other dependencies, in binary form (if required). That is, for Windows, you do not need to create a real Python package (which would allow installation with pip), and you do not need to look into distutils (which supports building C extensions). Both you do not need/want, I guess.
Maybe it will be enough for you to assemble a good directory structure and to distribute a ZIP archive with your software. This is enough if you do not need to interact with the Windows registry, for instance. Such programs are usually called "standalone", in the Windows world. However, you might still want to have a real Windows installer (even if it is just a self-extracting archive). The following article covers your requirements, I believe: http://cyrille.rossant.net/create-a-standalone-windows-installer-for-your-python-application/
It suggests using http://www.jrsoftware.org/isinfo.php for creating such an installer.
Other platforms
On other operating systems it will be more difficult. For instance, I think it will be almost impossible to create ffmpeg binaries that run on every Linux system, because ffmpeg itself has so many binary dependencies. I do not know whether you can statically build ffmpeg at all.
Related
I have a C++ application that uses machine learning from Python and my current approach is making a single file executable with pyInstaller and then just running it from C++. This have obvious drawbacks, notably interapplication communication. At the moment I'm using an intermediate JSON file to talk to each other but this is massively suboptimal for my future requirements. What's beautiful about this, is that is working on all major platforms without too much hassle.
Section 1.6. from Python's manual reads "Compiling and Linking under Unix-like systems"
Does this mean that Python interpreter will be inside my application binary and target system doesn't need to have Python installed as the program will always use embedded interpreter ? If so, whats with python libraries ? Can I embed a whole conda enviroment ?
Also, whats with:
"(...) under Unix-like systems"
Does this means this approach is not multiplatform ?
Thanks in advance.
Embedding the Python interpreter is possible on all platforms. However it will only be the interpreter. Embedding any libraries will be a lot harder or even impossible.
But since you seem to deploy the Python libs already, you can use them just fine from the embedded interpreter. And then you could bridge C++ and Python without IPC, since they are both running in the same process.
pybind11 is very nice for embedding and generating C++ <-> Python interfaces.
A possible alternative, depending on the libraries in use, may be to export the model and use a C++ library to load and use it (for instance Tensorflow -> ONNX -> ONNX runtime).
It means that cpython (Python interpreter) will be inside your application. You will be able to run Python code and observe and manipulate virtual machine state directly from C++ code (good entry point C API reference is here). Your application might have some additional dynamic library dependencies (which ones depends on compilation options of embedded Python). Also interpreter isn't completely self contained and depends on some external .py modules normally shipped with Python distribution (as standard library). If you plan to import external modules that expect standard library, you will have to ship it with your application. There are ways how to build modules into binary too (freeze) but you might run into issues specially with modules that rely on filesystem.
As far as I tried, this procedure works on UNIX like systems and Windows (where easiest way is to link against DLL which you then ship with your application). On Windows you also need to make sure that you compile with same compiler as was used to compile DLL (or you compile Python DLL from source). Here is additional information about embedding on Windows: https://docs.python.org/3/faq/windows.html#how-can-i-embed-python-into-a-windows-application
Just note that embedding Python and shipping 3rd party modules with your application might have some licensing consequences.
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
I have written a small python script that i want to share with other users.(i want to keep it as a script rather than and exe so that users can edit the codes if they need to)
my script has several external libraries for python which doesn't come with basic python.
But the other users doesn't have python and the required libraries installed in their PCs .
So,For convenient, I am wondering if there's any way to automate the installation process for installing python and the external libraries they need.
To make things more clear, what i meant is to combine all the installers into 1 single big installer.
For you information, all the installers are window x86 MSI installers and there are about 5 or 6 of them.
Is this possible?Could there be any drawbacks of doing this?
EDIT:
All the users are using windows XP pro 32 bit
python 2.7
I would suggest using NSIS. You can bundle all the MSI installers (including python) into one executable, and install them in "silent mode" in whatever order you want. NSIS also has a great script generator you can download.
Also, you might be interested in activepython. It comes with pip and automatically adds everything to your path so you can just pip install most of your dependencies from a batch script.
what i meant is to combine all the installers into 1 single big installer.
I am not sure, if you mean to make one msi out of several. If you have built the msis, this is possible to work out, but in most situations there were reasons for the separation.
But for now I assume as the others, that you want a setup which combines all msi setups into one, e.g. with a packing/selfextracting part, but probably with some own logic.
This is a very common setup pattern, some call it "bootstrapper". Unfortunately the maturity of most tools for bootstrapping is by far not comparable to the msi creation tools so most companies I know, write kind of an own bootstrapper with the dialogs and the control logic they want. This can be a very expensive job.
If you have not high requirements, it may sound a simple job. Just starting a number of processes after each other. But what about a seamless process bar, what about uninstallation (single or bundled), what about repair, modify, what about, if one of them fails or needs a reboot also concerning repair/uninstall/modify/update. And so on.
As mentioned, one of the first issues of bundling several setups into one is about caring how many and which uninstall entries shall the user see, and if it is ok that your bootstrapper does not create an own, combining one.
If this is not an issue for you, then you have chances to find an easy solution.
I know at least three tools for bootstrappers, some call it suites or bundles. I can only mention them here:
WiX has at least something called "Burn". Google for WiX Burn and you will find it. I haven't used it yet, so I can't tell about.
InstallShield Premier, which is not really what most people call a cheap product, allows setup "Suites" which is the same. I don't want to comment the quality here.
In the Windows SDK there is (has been?) a kind of template of a setup.exe to show how to start installation of msi out of a program. I have never looked into that example really to tell more about it.
I suggest putting all the files into a .sfx.exe archive and get them to run it. Extract all files to %temp% and run a batch script to install python.msi and copy the libraries from %temp% to the python library directory. If you want to install python 2.7.5, grab an "Ninite" installer from http://ninite.com/
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.
If I have a Python package that depends on some C libraries (like say the Gnu Scientific Library (GSL) for numerical computations), is it a good idea to bundle the library with my code?
I'd like to make my package as easy to install as possible for users and I don't want them to have to download C libraries by hand and supply include-paths. Also I could always ensure that the version of the library that I ship is compatible with my code.
However, is it possible that there are clashes if the user has the library installed already, or ar there any other reasons why I shouldn't do this?
I know that I can make it easier for users by just providing a binary distribution, but I'd like to avoid having to maintain binary distributions for all possible OSs. So, I'd like to stick to a source distribution, but for the user (who proudly owns a C compiler) installation should be as easy as python setup.py install.
Distribution is one of the hard parts for any software project. Java and .NET lift part of this burden by defining a standard runtime and then just saying "just distribute everything else." Of course there's a drawback: everything must be rewritten in a language supported by the runtime - as soon as you want to use native code, you lose all the advantages.
That's harder in Python, as it is in Ruby, C, C++ and other languages, as they usually leverage existing native libraries.
Generally speaking:
Make it possible to get a source sdist, via pypi.python.org as an example. Correctly set your install_requires (probably you'll require python bindings for GSL, not GSL itself). Use standard setuptools/distribute layout. This will let anyone - let's say a package maintainer for any distro - to pick up your software and package it.
Additionally, consider providing a full-blown installable package for your audience. You don't have to support all the distros and operating system; pick one or two that you consider will be used most. Tools like PyInstaller will let you create an installable, runnable package for many operating systems, but especially for linux you might want the user to install the distribution's own version of transitive deps (libgsl?) - you'll need a full-blown deb or rpm package to satisfy that - again, don't try supporting any and all the distro, you'll turn out mad. Support something you most use, and let other users to help you with other packaging needs.
Also take a look at Python Packaging Guide
You could have two separate branches of the src, one containing the libraries and another that doesn't. That way you can explicitly warn your users in case they have installed the libraries. Another solution could be (if the licences of the libraries allow you) is to wrap 'em up in a single file.
I think there's no unique solution, but this are the ideas I could think so far.
Good luck
You can use virtualenv to create a private Python environment for your application. This avoids conflicts with other libraries. It is best if you package modules and dependencies such as your libraries using Distribute. Distutils is something else that is worth researching.