setuptools "eager_resources" to executable directory - python

I maintain a Python utility that allows bpy to be installable as a Python module. Due to the hugeness of the spurce code, and the length of time it takes to download the libraries, I have chosen to provide this module as a wheel.
Unfortunately, platform differences and Blender runtime expectations makes support for this tricky at times.
Currently, one of my big goals is to get the Blender addon scripts directory to install into the correct location. The directory (simply named after the version of Blender API) has to exist in the same directory as the Python executable.
Unfortunately the way that setuptools works (or at least the way that I have it configured) the 2.79 directory is not always placed as a sibling to the Python executable. It fails on Windows platforms outside of virtual environments.
However, I noticed in setuptools documentation that you can specify eager_resources that supposedly guarantees the location of extracted files.
https://setuptools.readthedocs.io/en/latest/setuptools.html#automatic-resource-extraction
https://setuptools.readthedocs.io/en/latest/pkg_resources.html#resource-extraction
There was a lot of hand waving and jargon in the documentation, and 0 examples. I'm really confused as to how to structure my setup.py file in order to guarantee the resource extraction. Currently, I just label the whole 2.79 directory as "scripts" in my setuptools Extension and ship it.
Is there a way to write my setup.py and package my module so as to guarantee the 2.79 directory's location is the same as the currently running python executable when someone runs
py -3.6.8-32 -m pip install bpy
Besides simply "hacking it in"? I was considering writing a install_requires module that would simply move it if possible but that is mangling with the user's file system and kind of hacky. However it's the route I am going to go if this proves impossible.
Here is the original issue for anyone interested.
https://github.com/TylerGubala/blenderpy/issues/13
My build process is identical to the process descsribed in my answer here
https://stackoverflow.com/a/51575996/6767685

Maybe try the data_files option of distutils/setuptools.
You could start by adding data_files=[('mydata', ['setup.py'],)], to your setuptools.setup function call. Build a wheel, then install it and see if you can find mydata/setup.py somewhere in your sys.prefix.
In your case the difficult part will be to compute the actual target directory (mydata in this example). It will depend on the platform (Linux, Windows, etc.), if it's in a virtual environment or not, if it's a global or local install (not actually feasible with wheels currently, see update below) and so on.
Finally of course, check that everything gets removed cleanly on uninstall. It's a bit unnecessary when working with virtual environments, but very important in case of a global installation.
Update
Looks like your use case requires a custom step at install time of your package (since the location of the binary for the Python interpreter relative to sys.prefix can not be known in advance). This can not be done currently with wheels. You have seen it yourself in this discussion.
Knowing this, my recommendation would be to follow the advice from Jan Vlcinsky in his comment for his answer to this question:
Post install script after installing a wheel.
Add an extra setuptools console entry point to your package (let's call it bpyconfigure).
Instruct the users of your package to run it immediately after installing your package (pip install bpy && bpyconfigure).
The purpose of bpyconfigure should be clearly stated (in the documentation and maybe also as a notice shown in the console right after starting bpyconfigure) since it would write into locations of the file system where pip install does not usually write.
bpyconfigure should figure out where is the Python interpreter, and where to write the extra data.
The extra data to write should be packaged as package_data, so that it can be found with pkg_resources.
Of course bpyconfigure --uninstall should be available as well!

Related

Debian build package: Add python virtualenv into dpkg-buildpackage to be uploaded to launchpad

I would like to pack a python program and ship it in a deb package.
For reasons (I know in 99% it is bad practice) I want to ship the program in a python virtual environment within a debian package.
I know I can do this using dh-virtualenv. This works great - generally no problem.
But the problem arises when I want to upload this to launchpad. Uploading to launchpad means uploading a source package. In terms of dh-virtualenv a source package is the package description, where the virtualenv has not been created, yet.
What happens when I upload this to launchpad is, that the package will not build, since the dh-virtualenv which is executed during the build process on launchpad will try to install python modules into the virtualenv, which means installing these from the PyPI, which will not work, since launchpad does not allow external network access.
So basically there are two possible solutions:
Approach A
Prepare the virtualenv and somehow incorporate it into the source package and having the dh build process simply "move" this prepared virtualenv to its end location. This could work with virtualenv --relocatable. BUT the relocation strips the utf-8 marker at the beginning of all python scripts, rendering all python scripts in the virtualenv broken.
Apporach B
Somehow cache all necessary python packages in the source package and have dh_virtualenv install from the cache instead of from PyPI.
This seems like to be doable with pip2pi, but certain experiements show, that it will not install packages, although they are located in the local package index.
Both approaches seem a bit clumsy and prone to errors.
What do you think of this?
What are your experiences?
What would you recommend?

How to ditribute my Unix application?

I created a command-line python tool for Unix systems.
I want my script to be executed from anywhere just like any Unix command. One solution is to make my script executable and move it to /usr/bin.
But the script works with external files, and I guess moving all these files with my script in /usr/bin is a bad habit, as it will be hard to delete them one by one in the future.
Where should I put the directory of my application ? How to add the main script to the PATH, to execute it from anywhere ?
I would like then to create a package that could move my files in the right place, and delete them in the case the user wants to uninstall my application.
I don't know how to do this.
Thank you.
There are many way of distributing a Linux application.
It will depend on the distribution you are using, since they do not all use the same package manager. For example, you would create a .deb package for Debian, Ubuntu and there derivatives, an Arch package for Archlinux, etc...
You could then share the package with anyone to let them install your tool.
However, since your tool is in written in Python, you can also make a python package. You could then upload it to the Python Package Index to let anyone install it using python's pip package manager.
To create a python package, you will need to create a file called setup.py, and, from it, to call the setup method from the setuptool packages.
You will probably want to read the python documentation about writing such a script: https://setuptools.readthedocs.io/en/latest/setuptools.html
You may especially be interested by this sections:
Including Data Files
Automatic Script Creation
If you do things correctly, setuptools will take care of installing your script and its files somewhere in the PATH so it can be executed from the command line.
You should use setuptools to distribute your application, creating a setup.py file to configure its setup and installation.
Binaries can be delivered using the console_scripts option, while data files can be delivered using either package_data.

What is Building and Installing?

This is probably a question that has a very easy and straightforward answer, however, despite having a few years programming experience, for some reason I still don't quite get the exact concepts of what it means to "build" and then to "install". I know how to use them and have used them a lot, but have no idea about the exact processes which happen in the background...
I have looked across the web, wikipedia, etc... but there is no one simple answer to it, neither can I find one here.
A good example, which I tried to understand, is adding new modules to python:
http://docs.python.org/2/install/index.html#how-installation-works
It says that "the build command is responsible for putting the files to install into a build directory"
And then for the install command: "After the build command runs (whether you run it explicitly, or the install command does it for you), the work of the install command is relatively simple: all it has to do is copy everything under build/lib (or build/lib.plat) to your chosen installation directory."
So essentially what this is saying is:
1. Copy everything to the build directory and then...
2. Copy everything to the installation directory
There must be a process missing somewhere in the explanation...complilation?
Would appreciate some straightforward not too techy answer but in as much detail as possible :)
Hopefully I am not the only one who doesn't know the detailed answer to this...
Thanks!
Aivoric
Building means compiling the source code to binary in a sandbox location where it won't affect your system if something goes wrong, like a build subdirectory inside the source code directory.
Install means copying the built binaries from the build subdirectory to a place in your system path, where they become easily accessible. This is rarely done by a straight copy command, and it's often done by some package manager that can track the files created and easily uninstall them later.
Usually, a build command does all the compiling and linking needed, but Python is an interpreted language, so if there are only pure Python files in the library, there's no compiling step in the build. Indeed, everything is copied to a build directory, and then copied again to a final location. Only if the library depends on code written in other languages that needs to be compiled you'll have a compiling step.
You want a new chair for your living-room and you want to make it yourself. You browse through a catalog and order a pile of parts. When they arrives at your door, you can't immediately use them. You have to build the chair at your workshop. After a bit of elbow-grease, you can sit down in it. Afterwards, you install the chair in your living-room, in a convenient place to sit down.
The chair is a program you want to use. It arrives at your house as source code. You build it by compiling it into a runnable program. You install it by making it easier to use.
The build and install commands you are refering to come from setup.py file right?
Setup.py (http://docs.python.org/2/distutils/setupscript.html)
This file is created by 3rd party applications / extensions of Python. They are not part of:
Python source code (bunch of c files, etc)
Python libraries that come bundled with Python
When a developer makes a library for python that he wants to share to the world he creates a setup.py file so the library can be installed on any computer that has python. Maybe this is the MISSING STEP
Setup.py sdist
This creates a python module (the tar.gz files). What this does is copy all the files used by the python library into a folder. Creates a setup.py file for the module and archives everything so the library can be built somewhere else.
Setup.py build
This builds the python module back into a library (SPECIFICALLY FOR THIS OS).
As you may know, the computer that the python library originally came from will be different from the library that you are installing on.
It might have a different version of python
It might have a different operating system
It might have a different processor / motherboard / etc
For all the reasons listed above the code will not work on another computer. So setup.py sdist creates a module with only the source files needed to rebuild the library on another computer.
What setup.py does exactly is similar to what a makefile would do. It compiles sources / creates libraries all that stuff.
Now we have a copy of all the files we need in the library and they will work on our computer / operating system.
Setup.py install
Great we have all the files needed. But they won't work. Why? Well they have to be added to Python that's why. This is where install comes in. Now that we have a local copy of the library we need to install it into python so you can use it like so:
import mycustomlibrary
In order to do this we need to do several things including:
Copy files to their library folders in our version of python.
Make sure library can be imported using import command
Run any special install instructions for this library. (seting up paths, etc)
This is the most complicated part of the task. What if our library uses BeautifulSoup? This is not a part of Python Library. We'd have to install it in a way such that our library and any others can use BeautifulSoup without interfering with each other.
Also what if python was installed someplace else? What if it was installed on a server with many users?
Install handles all these problems transparently. What is does is make the library that we just built able to run. All you have to do is use the import command, install handles the rest.

Python compile all modules into a single python file

I am writing a program in python to be sent to other people, who are running the same python version, however these some 3rd party modules that need to be installed to use it.
Is there a way to compile into a .pyc (I only say pyc because its a python compiled file) that has the all the dependant modules inside it as well?
So they can run the programme without needing to install the modules separately?
Edit:
Sorry if it wasnt clear, but I am aware of things such as cx_freeze etc but what im trying to is just a single python file.
So they can just type "python myapp.py" and then it will run. No installation of anything. As if all the module codes are in my .py file.
If you are on python 2.3 or later and your dependencies are pure python:
If you don't want to go the setuptools or distutiles routes, you can provide a zip file with the pycs for your code and all of its dependencies. You will have to do a little work to make any complex pathing inside the zip file available (if the dependencies are just lying around at the root of the zip this is not necessary. Then just add the zip location to your path and it should work just as if the dependencies files has been installed.
If your dependencies include .pyds or other binary dependencies you'll probably have to fall back on distutils.
You can simply include .pyc files for the libraries required, but no - .pyc cannot work as a container for multiple files (unless you will collect all the source into one .py file and then compile it).
It sounds like what you're after is the ability for your end users to run one command, e.g. install my_custom_package_and_all_required_dependencies, and have it assemble everything it needs.
This is a perfect use case for distutils, with which you can make manifests for your own code that link out to external dependencies. If your 3rd party modules are available publicly in a standard format (they should be, and if they're not, it's pretty easy to package them yourself), then this approach has the benefit of allowing you to very easily change what versions of 3rd party libraries your code runs against (see this section of the above linked doc). If you're dead set on packaging others' code with your own, you can always include the required files in the .egg you create with distutils.
Two options:
build a package that will install the dependencies for them (I don't recommend this if the only dependencies are python packages that are installed with pip)
Use virtual environments. You use an existing python on their system but python modules are installed into the virtualenv.
or I suppose you could just punt, and create a shell script that installs them, and tell them to run it once before they run your stuff.

Installing nosetests - permission denied

Trying to install nosetests as per the learnpythonthehardway tutorial, I'm having problems. Any clues on what I should try next?
$ easy_install nose
Searching for nose
Best match: nose 1.1.2
Processing nose-1.1.2-py2.6.egg
nose 1.1.2 is already the active version in easy-install.pth
Installing nosetests-2.6 script to /usr/local/bin
error: /usr/local/bin/nosetests-2.6: Permission denied`
One question about installing that I have: if I have something saved in a random location on my computer, can it be imported into a python script regardless of where it is? So if I execute runthis.py that's in a folder called "projects", and I have from setup tools import setup as the first line of the program, does setup tools have to be anywhere in particular (such as the "projects" folder) for python to find it?
Are you able to use sudo?
If so, simply use sudo easy_install nose to install as root.
If not, you'll need to install somewhere you can write to, not the default location which you don't have permission to modify. This can be done easily in the traditional way, or using virtualenv which can a bit trickier to get set up initially.
As for the second question, no, python will only find things that are in directories found in sys.path, which is set to the contents of the PYTHONPATH environment variable plus the installed python's own library directories by default.
It is often (highly!) advisable to set up your own "local" repository of packages, for whatever language system (be it Python or otherwise) that you are using. Leave the "system installed" packages, whatever they might be, completely alone ... in case some uber-important system tool (the package-manager, anyone?) might also be using them and might be dependent on them.
The means of doing this vary from language to language, but they'll be documented somewhere all the same. You might even find that the "distro" that you're using has already anticipated this requirement and has set-aside some agreed upon location, e.g. "/usr/local/..." just for your own personal use.

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