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unable to load sublime text 3 package [duplicate]

I'm trying to write a plugin for Sublime Text 3.
I have to use several third party packages in my code. I have managed to get the code working by manually copying the packages into /home/user/.config/sublime-text-3/Packages/User/, then I used relative imports to get to the needed code. How would I distribute the plugin to the end users? Telling them to copy the needed dependencies to the appropriate location is certainly not the way to go. How are 3rd party modules supposed to be used properly with Sublime Text plugins? I can't find any documentation online; all I see is the recommendation to put the modules in the folder.

Sublime uses it's own embedded Python interpreter (currently Python 3.3.6 although the next version will also support Python 3.8 as well) and as such it will completely ignore any version of Python that you may or may not have installed on your system, as well as any libraries that are installed for that version.
For that reason, if you want to use external modules (hereafter dependencies) you need to do extra work. There are a variety of ways to accomplish this, each with their own set of pros and cons.
The following lists the various ways that you can achieve this; all of them require a bit of an understanding about how modules work in Python in order to understand what's going on. By and large except for the paths involved there's nothing too "Sublime Text" about the mechanisms at play.
NOTE: The below is accurate as of the time of this answer. However there are plans for Package Control to change how it works with dependencies that are forthcoming that may change some aspect of this.
This is related to the upcoming version of Sublime supporting multiple versions of Python (and the manner in which it supports them) which the current Package Control mechanism does not support.
It's unclear at the moment if the change will bring a new way to specify dependencies or if only the inner workings of how the dependencies are installed will change. The existing mechanism may remain in place regardless just for backwards compatibility, however.
All roads to accessing a Python dependency from a Sublime plugin involve putting the code for it in a place where the Python interpreter is going to look for it. This is similar to how standard Python would do things, except that locations that are checked are contained within the area that Sublime uses to store your configuration (referred to as the Data directory) and instead of a standalone Python interpreter, Python is running in the plugin host.
Populate the library into the Lib folder
Since version 3.0 (build 3143), Sublime will create a folder named Lib in the data directory and inside of it a directory based on the name of the Python version. If you use Preferences > Browse Packages and go up one folder level, you'll see Lib, and inside of it a folder named e.g. python3.3 (or if you're using a newer build, python33 and python38).
Those directories are directly on the Python sys.path by default, so anything placed inside of them will be immediately available to any plugin just as a normal Python library (or any of those built in) would be. You could consider these folders to be something akin to the site-packages folder in standard Python.
So, any method by which you could install a standard Python library can be used so long as the result is files ending up in this folder. You could for example install a library via pip and then manually copy the files to that location from site-packages, manually install from sources, etc.
Lib/python3.3/
|-- librarya
| `-- file1.py
|-- libraryb
| `-- file2.py
`-- singlefile.py
Version restrictions apply here; the dependency that you want to use must support the version of Python that Sublime is using, or it won't work. This is particularly important for Python libraries with a native component (e.g. a .dll, .so or .dylib), which may require hand compiling the code.
This method is not automatic; you would need to do it to use your package locally, and anyone that wants to use your package would also need to do it as well. Since Sublime is currently using an older version of Python, it can be problematic to obtain a correct version of libraries as well.
In the future, Package Control will install dependencies in this location (Will added the folder specifically for this purpose during the run up to version 3.0), but as of the time I'm writing this answer that is not currently the case.
Vendor your dependencies directly inside of your own package
The Packages folder is on the sys.path by default as well; this is how Sublime finds and loads packages. This is true of both the physical Packages folder, as well as the "virtual" packages folder that contains the contents of sublime-package files.
For example, one can access the class that provides the exec command via:
from Default.exec import ExecCommand
This will work even though the exec.py file is actually stored in Default.sublime-package in the Sublime text install folder and not physically present in the Packages folder.
As a result of this, you can vendor any dependencies that you require directly inside of your own package. Here this could be the User package or any other package that you're creating.
It's important to note that Sublime will treat any Python file in the top level of a package as a plugin and try to load it as one. Hence it's important that if you go this route you create a sub-folder in your package and put the library in there.
MyPackage/
|-- alibrary
| `-- code.py
`-- my_plugin.py
With this structure, you can access the module directly:
import MyPackage.alibrary
from MyPackage.alibrary import someSymbol
Not all Python modules lend themselves to this method directly without modification; some code changes in the dependency may be required in order to allow different parts of the library to see other parts of itself, for example if it doesn't use relative import to get at sibling files. License restrictions may also get in the way of this as well, depending on the library that you're using.
On the other hand, this directly locks the version of the library that you're using to exactly the version that you tested with, which ensures that you won't be in for any undue surprises further on down the line.
Using this method, anything you do to distribute your package will automatically also distribute the vendored library that's contained inside. So if you're distributing by Package Control, you don't need to do anything special and it will Just Work™.
Modify the sys.path to point to a custom location
The Python that's embedded into Sublime is still standard Python, so if desired you can manually manipulate the sys.path that describes what folders to look for packages in so that it will look in a place of your choosing in addition to the standard locations that Sublime sets up automatically.
This is generally not a good idea since if done incorrectly things can go pear shaped quickly. It also still requires you to manually install libraries somewhere yourself first, and in that case you're better off using the Lib folder as outlined above, which is already on the sys.path.
I would consider this method an advanced solution and one you might use for testing purposes during development but otherwise not something that would be user facing. If you plan to distribute your package via Package Control, the review of your package would likely kick back a manipulation of the sys.path with a request to use another method.
Use Package Control's Dependency system (and the dependency exists)
Package control contains a dependency mechanism that uses a combination of the two prior methods to provide a way to install a dependency automatically. There is a list of available dependencies as well, though the list may not be complete.
If the dependency that you're interested in using is already available, you're good to go. There are two different ways to go about declaring that you need one or more dependencies on your package.
NOTE: Package Control doesn't currently support dependencies of dependencies; if a dependency requires that another library also be installed, you need to explicitly mention them both yourself.
The first involves adding a dependencies key to the entry for your package in the package control channel file. This is a step that you'd take at the point where you're adding your package to Package Control, which is something that's outside the scope of this answer.
While you're developing your package (or if you decide that you don't want to distribute your package via Package Control when you're done), then you can instead add a dependencies.json file into the root of your package (an example dependencies.json file is available to illustrate this).
Once you do that, you can choose Package Control: Satisfy Dependencies from the command Palette to have Package Control download and install the dependency for you (if needed).
This step is automatic if your package is being distributed and installed by Package Control; otherwise you need to tell your users to take this step once they install the package.
Use Package Control's Dependency system (but the dependency does not exist)
The method that Package Control uses to install dependencies is, as outlined at the top of the question subject to change at some point in the (possibly near) future. This may affect the instructions here. The overall mechanism may remain the same as far as setup is concerned, with only the locations of the installation changing, but that remains to be seen currently.
Package Control installs dependencies via a special combination of vendoring and also manipulation of the sys.path to allow things to be found. In order to do so, it requires that you lay out your dependency in a particular way and provide some extra metadata as well.
The layout for the package that contains the dependency when you're building it would have a structure similar to the following:
Packages/my_dependency/
├── .sublime-dependency
└── prefix
└── my_dependency
└── file.py
Package Control installs a dependency as a Package, and since Sublime treats every Python file in the root of a package as a plugin, the code for the dependency is not kept in the top level of the package. As seen above, the actual content of the dependency is stored inside of the folder labeled as prefix above (more on that in a second).
When the dependency is installed, Package Control adds an entry to it's special 0_package_control_loader package that causes the prefix folder to be added to the sys.path, which makes everything inside of it available to import statements as normal. This is why there's an inherent duplication of the name of the library (my_dependency in this example).
Regarding the prefix folder, this is not actually named that and instead has a special name that determines what combination of Sublime Text version, platform and architecture the dependency is available on (important for libraries that contain binaries, for example).
The name of the prefix folder actually follows the form {st_version}_{os}_{arch}, {st_version}_{os}, {st_version} or all. {st_version} can be st2 or st3, {os} can be windows, linux or osx and {arch} can be x32 or x64.
Thus you could say that your dependency supports only st3, st3_linux, st3_windows_x64 or any combination thereof. For something with native code you may specify several different versions by having multiple folders, though commonly all is used when the dependency contains pure Python code that will work regardless of the Sublime version, OS or architecture.
In this example, if we assume that the prefix folder is named all because my_dependency is pure Python, then the result of installing this dependency would be that Packages/my_dependency/all would be added to the sys.path, meaning that if you import my_dependency you're getting the code from inside of that folder.
During development (or if you don't want to distribute your dependency via Package Control), you create a .sublime-dependency file in the root of the package as shown above. This should be a text file with a single line that contains a 2 digit number (e.g. 01 or 50). This controls in what order each installed dependency will get added to the sys.path. You'd typically pick a lower number if your dependency has no other dependencies and a higher value if it does (so that it gets injected after those).
Once you have the initial dependency laid out in the correct format in the Packages folder, you would use the command Package Control: Install Local Dependency from the Command Palette, and then select the name of your dependency.
This causes Package Control to "install" the dependency (i.e. update the 0_package_control_loader package) to make the dependency active. This step would normally be taken by Package Control automatically when it installs a dependency for the first time, so if you are also manually distributing your dependency you need to provide instructions to take this step.

What is a reliable way to include libraries for virtualenv python packages in nix?

I'll start by saying virtualenv is basically a requirement here since Nix is not yet being used by the rest of the development team. This excellent guide on Python in Nix doesn't quite drill down to this particular issue.
In some cases I can update LD_LIBRARY_PATH, but it gets to be rather tedious and potentially error prone due to the dynamic nature of Python (a particular branch could trigger the use of a library not previously included in LD_LIBRARY_PATH):
shellHook = ''
export LD_LIBRARY_PATH=${mysql57}/lib:${gcc6}/lib:$LD_LIBRARY_PATH
'';
Worse, the ${ggc6}/lib doesn't work for me here, since the library I need (libatomic.so) is under the *-gcc-6.4.0-lib/lib directory, not the *-gcc-6.4.0/lib directory, and I'm not sure how to reference the former.
$ echo $LD_LIBRARY_PATH
/nix/store/x3x3si0pc3w0vam9jj308b0qhcv7zlg2-mysql-5.7.19/lib:/nix/store/mc8p626zjk9zlgji1i8f85nax4c62nrj-gcc-wrapper-6.4.0/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64
Some output from find for libatomic:
/nix/store/rww78vdn2rkayrnqsjl8ib5iq2vfm3sw-gcc-6.4.0/lib/libatomic.a
/nix/store/klqzvvcy1xyjjflmf7agryayc4s72jg2-gcc-6.4.0-lib/lib/libatomic.so.1
/nix/store/klqzvvcy1xyjjflmf7agryayc4s72jg2-gcc-6.4.0-lib/lib/libatomic.so
/nix/store/klqzvvcy1xyjjflmf7agryayc4s72jg2-gcc-6.4.0-lib/lib/libatomic.la
/nix/store/klqzvvcy1xyjjflmf7agryayc4s72jg2-gcc-6.4.0-lib/lib/libatomic.so.1.2.0

I don't use the nixpkgs Python infrastructure much, so I'm not sure if there is a way to eliminate setting the LD_LIBRARY_PATH. Recommendations for setting it:
You can use lib.makeLibraryPath to make the process much less tedious. If you know that all the libraries that might be necessary are (mostly) in buildDepends anyway, you can use lib.makeLibraryPath (buildDepends ++ [ anything else ]).
The issue with GCC libraries has to do with the fact that Nix needs wrapped versions of GCC, so pkgs.gcc6 isn't the "raw" GCC derivation. You can use gcc6.cc.lib, or, if you are using makeLibraryPath, just gcc6.cc will be enough (as makeLibraryPath will automatically figure out that the lib output is the correct one to look under).

Proper procedure for python package collections in Nixos

I am interested in a reliable and robust procedure for collecting python package and dependencies for the Psychopy library into a single collection or environment to make a self-contained and maintainable installation. As well it would be good to have some general recommendations on the recommended way to do this since googling Nixos and Python yields a number of approaches, some of which use poorly documented function e.g. myEnvFun
Psychopy is a python package used for psychology experiments. It has several dependencies, most of which are python packages, but not all (e.g. AVbin); and most of which are in the nixos package collection, but not all (pyo and py-parallel).
My goal would be to be able to get all the needed pieces together and have a functioning psychopy environment with a single installation request. I have figured out how to get psychopy installed, but the path's don't play nicely.
For example if the following is saved as ~/pkg/psychopy/default.nix
let
pkgs = import <nixpkgs> {};
in
{stdenv ? pkgs.stdenv, python ? pkgs.python, fetchurl ? pkgs.fetchurl}:
with pkgs;
buildPythonPackage {
name = "psychopy";
src = fetchurl {
url = http://sourceforge.net/projects/psychpy/files/PsychoPy/PsychoPy-1.82.02.zip;
md5 = "52309280bdca4408970aab0952c674e4";
};
buildInputs = [
python27
];
}
One can run nix-env -f ~/pkg/ -iA psychopy and Psychopy will be installed, but it will not be easily useable because the path to the psychopy library is not seen by any system wide python2 installation, or even the python version that is installed as part of the build inputs.
This leads to the following questions that though they are specifically about psychopy would apply more generally to python and Nixos.
Is the recommend practice to install python packages that exist in the nixos expression collections (e.g. numpy and scipy) once as system or user wide packages or with each particular experimental library?
If one wishes to bundle together a python collection with more than one library outside the nixos expression channel (e.g. psychopy and pyo and pyparallel) what is the recommended procedure? And how does this change if some non-python software is required, e.g. in this case AVbin (which actually has installation instructions that refers to paths that are not standard in Nixos to my understanding, i.e. /usr/lib)?
Can some discussion of handling paths in Python with the context of Nixos be shared?

myEnvFun is deprecated, where did you read about it?
Answers:
It's recommended to create environments with nix-shell, you should be able to run it inside ~/pkg/psychopy/ and get $PYTHONPATH populated.
The idea behind Nix is not to have any global sets of packages, but rather environments for each need.
By just declaring AVBin as build dependency it should be enough. Note that your users will need to install Nix. If you want to avoid that, you'll need to write a wrapper that will do something similar to nix-shell.
There isn't much going on here. All Nix packages are build in isolated chroots. Nix has a concept called setup hooks, which are executed for each package in the dependency tree. So for Python packages https://github.com/NixOS/nixpkgs/blob/master/pkgs/development/interpreters/python/2.7/setup-hook.sh#L15 is called in order to populate $PYTHONPATH. For command line programs we then wrap the resulting script with $PYTHONPATH hardcoded.
For discussion it's best to join Freenode IRC channel #nixos

Why use sys.path.append(path) instead of sys.path.insert(1, path)?

Edit: based on a Ulf Rompe's comment, it is important you use "1" instead of "0", otherwise you will break sys.path.
I have been doing python for quite a while now (over a year), and I am always confused as to why people recommend you use sys.path.append() instead of sys.path.insert(). Let me demonstrate.
Let's say I am working on a module named PyWorkbooks (that is installed on my computer), but I am simultaneously working on a different module (let's say PyJob) that incorporates PyWorkbooks. As I'm working on PyJob I find errors in PyWorkbooks that I am correcting, so I would like to import a development version.
There are multiple ways to work on both (I could put my PyWorkbooks project inside of PyJob, for instance), but sometimes I will still need to play with the path. However, I cannot simply do a sys.path.append() to the folder where PyWorkbooks is at. Why? Because python will find my installed PyWorkbooks first!
This is why you have to do a sys.path.insert(1, path_to_dev_pyworkbooks)
In summary:
sys.path.append(path_to_dev_pyworkbooks)
import PyWorkbooks # does NOT import dev pyworkbooks, imports installed one
or:
sys.path.insert(1, path_to_dev_pyworkbooks) # based on comments you should use **1 not 0**
import PyWorkbooks # imports correct file
This has caused a few hangups for me in the past, and I would really like it if we (as a community) started recommending sys.path.insert(1, path), as if you are manually inserting a path I think it is safe to say that that is the path you want to use!
Or do I have something wrong? It's a question that sometimes bothers me and I wanted it in the open!

If you really need to use sys.path.insert, consider leaving sys.path[0] as it is:
sys.path.insert(1, path_to_dev_pyworkbooks)
This could be important since 3rd party code may rely on sys.path documentation conformance:
As initialized upon program startup, the first item of this list,
path[0], is the directory containing the script that was used to
invoke the Python interpreter.

If you have multiple versions of a package / module, you need to be using virtualenv (emphasis mine):
virtualenv is a tool to create isolated Python environments.
The basic problem being addressed is one of dependencies and versions, and indirectly permissions. Imagine you have an application that needs version 1 of LibFoo, but another application requires version 2. How can you use both these applications? If you install everything into /usr/lib/python2.7/site-packages (or whatever your platform’s standard location is), it’s easy to end up in a situation where you unintentionally upgrade an application that shouldn’t be upgraded.
Or more generally, what if you want to install an application and leave it be? If an application works, any change in its libraries or the versions of those libraries can break the application.
Also, what if you can’t install packages into the global site-packages directory? For instance, on a shared host.
In all these cases, virtualenv can help you. It creates an environment that has its own installation directories, that doesn’t share libraries with other virtualenv environments (and optionally doesn’t access the globally installed libraries either).
That's why people consider insert(0, to be wrong -- it's an incomplete, stopgap solution to the problem of managing multiple environments.

you are confusing the concept of appending and prepending. the following code is prepending:
sys.path.insert(1,'/thePathToYourFolder/')
it places the new information at the beginning (well, second, to be precise) of the search sequence that your interpreter will go through. sys.path.append() puts things at the very end of the search sequence.
it is advisable that you use something like virtualenv instead of manually coding your package directories into the PYTHONPATH everytime. for setting up various ecosystems that separate your site-packages and possible versions of python, read these two blogs:
python ecosystems introduction
bootstrapping python virtual environments
if you do decide to move down the path to environment isolation you would certainly benefit by looking into virtualenvwrapper: http://www.doughellmann.com/docs/virtualenvwrapper/

Py2App Can't find standard modules

I've created an app using py2app, which works fine, but if I zip/unzip it, the newly unzipped version can't access standard python modules like traceback, or os. The manpage for zip claims that it preserves resource forks, and I've seen other applications packaged this way (I need to be able to put this in a .zip file). How do I fix this?

This is caused by building a semi-standalone version that contains symlinks to the natively installed files and as you say, the links are lost when zipping/unzipping unless the "-y" option is used.
An alternate solution is to build for standalone instead, which puts (public domain) files inside the application and so survives zipping/unzipping etc. better. It also means the app is more resilient to changes in the underlying OS. The downside is that it is bigger, of course, and is more complicated to get it set up.
To build a stand alone version, you need to install the python.org version which can be repackaged.
An explanation of how to do this is here, but read the comments as there have been some changes since the blog post was written.

use zip -y ... to create the file whilst preserving symlinks.

You probably need to give it your full PYTHONPATH.
Depends on your os. Here's how to find out:
import os [or any other std module]
os.file()