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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 the proper way to work with shared modules in Python development?

I'm working toward adopting Python as part of my team's development tool suite. With the other languages/tools we use, we develop many reusable functions and classes that are specific to the work we do. This standardizes the way we do things and saves a lot of wheel re-inventing.
I can't seem to find any examples of how this is usually handled with Python. Right now I have a development folder on a local drive, with multiple project folders below that, and an additional "common" folder containing packages and modules with re-usable classes and functions. These "common" modules are imported by modules within multiple projects.
Development/
Common/
Package_a/
Package_b/
Project1/
Package1_1/
Package1_2/
Project2/
Package2_1/
Package2_2/
In trying to learn how to distribute a Python application, it seems that there is an assumption that all referenced packages are below the top-level project folder, not collateral to it. The thought also occurred to me that perhaps the correct approach is to develop common/framework modules in a separate project, and once tested, deploy those to each developer's environment by installing to the site-packages folder. However, that also raises questions re distribution.
Can anyone shed light on this, or point me to a resource that discusses this issue?

If you have common code that you want to share across multiple projects, it may be worth thinking about storing this code in a physically separate project, which is then imported as a dependency into your other projects. This is easily achieved if you host your common code project in github or bitbucket, where you can use pip to install it in any other project. This approach not only helps you to easily share common code across multiple projects, but it also helps protect you from inadvertently creating bad dependencies (i.e. those directed from your common code to your non common code).
The link below provides a good introduction to using pip and virtualenv to manage dependencies, definitely worth a read if you and your team are fairly new to working with python as this is a very common toolchain used for just this kind of problem:
http://dabapps.com/blog/introduction-to-pip-and-virtualenv-python/
And the link below shows you how to pull in dependencies from github using pip:
How to use Python Pip install software, to pull packages from Github?

The must-read-first on this kind of stuff is here:
What is the best project structure for a Python application?
in case you haven't seen it (and follow the link in the second answer).
The key is that each major package be importable as if "." was the top level directory, which means that it will also work correctly when installed in a site-packages. What this implies is that major packages should all be flat within the top directory, as in:
myproject-0.1/
myproject/
framework/
packageA/
sub_package_in_A/
module.py
packageB/
...
Then both you (within your other packages) and your users can import as:
import myproject
import packageA.sub_package_in_A.module
etc
Which means you should think hard about #MattAnderson's comment, but if you want it to appear as a separately-distributable package, it needs to be in the top directory.
Note this doesn't stop you (or your users) from doing an:
import packageA.sub_package_in_A as sub_package_in_A
but it does stop you from allowing:
import sub_package_in_A
directly.

...it seems that there is an assumption that all referenced packages
are below the top-level project folder, not collateral to it.
That's mainly because the current working directory is the first entry in sys.path by default, which makes it very convenient to import modules and packages below that directory.
If you remove it, you can't even import stuff from the current working directory...
$ touch foo.py
$ python
>>> import sys
>>> del sys.path[0]
>>> import foo
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
ImportError: No module named foo
The thought also occurred to me that perhaps the correct approach is
to develop common/framework modules in a separate project, and once
tested, deploy those to each developer's environment by installing to
the site-packages folder.
It's not really a major issue for development. If you're using version control, and all developers check out the source tree in the same structure, you can easily employ relative path hacks to ensure the code works correctly without having to mess around with environment variables or symbolic links.
However, that also raises questions re distribution.
This is where things can get a bit more complicated, but only if you're planning to release libraries independently of the projects which use them, and/or having multiple project installers share the same libraries. It that's the case, take a look at distutils.
If not, you can simply employ the same relative path hacks used in development to ensure you project works "out of the box".

I think that this is the best reference for creating a distributable python package:
link removed as it leads to a hacked site.
also, don't feel that you need to nest everything under a single directory. You can do things like
platform/
core/
coremodule
api/
apimodule
and then do things like from platform.core import coremodule, etc.

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/

Automatically fetching latest version of a file on import

I have a module that I want to keep up to date, and I'm wondering if this is a bad idea:
Have a module (mod1.py) in the
site-packages directory that copies a
different module from some other
location into the site-packages
directory, and then imports * from
that module.
import shutil
from distutils.sysconfig import get_python_lib
p_source = r'\\SourceSafeServer\mod1_current.py'
p_local = get_python_lib() + r'\mod1_current.py'
shutil.copyfile(p_source, p_local)
from mod1_current import *
Now I can do this in any module, and it will always be the latest version:
from mod1 import function1
This works.... but is there a better way of doing this?
Update
Here is the current process... there is a project under source-control that has a single module: mod1.py There is also a setup.py Running setup.py copies mod1.py to the site-packages directory.
Developers that use the module must run setup.py to update the module. Sometimes, they don't and not having the latest version causes problems.
I want to be able to just check-in the a new version, and any code that imports that module will automatically grab the latest version every time, without anyone having to run setup.py

Do you really want to do this? This means you could very easily roll code to a production app simply by committing to source control. I would consider this a nasty side-effect for someone who isn't aware of your setup.
That being said this seems like a pretty good solution - you may want to add some exception-handling around the network file calls as those are prone to failure.

In some cases, we put .pth files in the Python site-packages directory. The .pth files name our various SVN checkout directories.
No install. No copy.
.pth files are described here.

The original strategy of having other developers copy mod1.py into their site-packages in order to use the module sounds like it's the real problem. Why aren't they just using the same source control are you are?
This auto-copying will make it hard to do rollbacks, especially if other developers copy your strategy. Imagine this same system used for dozens and dozens of files. And then imagine you actually do want to use a version of mod1.py that is not the latest for something.

How can I make a Python extension module packaged as an egg loadable without installing it?

I'm in the middle of reworking our build scripts to be based upon the wonderful Waf tool (I did use SCons for ages but its just way too slow).
Anyway, I've hit the following situation and I cannot find a resolution to it:
I have a product that depends on a number of previously built egg files.
I'm trying to package the product using PyInstaller as part of the build process.
I build the dependencies first.
Next I want to run PyInstaller to package the product that depends on the eggs I built. I need PyInstaller to be able to load those egg files as part of it's packaging process.
This sounds easy: you work out what PYTHONPATH should be, construct a copy of sys.environ setting the variable up correctly, and then invoke the PyInstaller script using subprocess.Popen passing the previously configured environment as the env argument.
The problem is that setting PYTHONPATH alone does not seem to be enough if the eggs you are adding are extension modules that are packaged as zipsafe. In this case, it turns out that the embedded libraries are not able to be imported.
If I unzip the eggs (renaming the directories to .egg), I can import them with no further settings but this is not what I want in this case.
I can also get the eggs to import from a subshell by doing the following:
Setting PYTHONPATH to the directory that contains the egg you want to import (not the path of the egg itself)
Loading a python shell and using pkg_resources.require to locate the egg.
Once this has been done, the egg loads as normal. Again, this is not practical because I need to be able to run my python shell in a manner where it is ready to import these eggs from the off.
The dirty option would be to output a wrapper script that took the above actions before calling the real target script but this seems like the wrong thing to do: there must be a better way to do this.

Heh, I think this was my bad. The issue appear to have been that the zipsafe flag in setup.py for the extension package was set to False, which appears to affect your ability to treat it as such at all.
Now that I've set that to True I can import the egg files, simply by adding each one to the PYTHONPATH.
I hope someone else finds this answer useful one day!

Although you have a solution, you could always try "virtualenv" that creates a virtual environment of python where you can install and test Python Packages without messing with the core system python:
http://pypi.python.org/pypi/virtualenv