I'm writing a Python project which is published as a package to a pypi-like repository (using setuptools and twine). I use type hints in my code.
The issue is, when importing the package from a different project and running mypy, I get the following error:
error: Skipping analyzing 'XXX': found module but no type hints or library stubs
As I understand, I got this error because my package was not compliant with https://www.python.org/dev/peps/pep-0561/ .
After some searching online, I didn't find a way that was not manual to add the required files to the package.
I resorted to writing my own code to:
Run stubgen to create stub files.
Create py.typed files in every directory.
Collect all the created files in a dict in package_data field in the setup.py file.
This code solved the issue and mypy runs without errors. But this feels very wrong to me. Is there a standard tool for making a package PEP-561 compliant? Am I missing something else?
As mentioned before, You need to add the py.typed in the package folder of the module.
You also need to add that file to the setup.py package_data - otherwise the file would not be part of the package when You deploy it.
I personally put the type annotations in the code and dont create extra stub files - but that is only possible from python 3.4 upwards. If You want to make python2.7 compatible code, You can not use inline type annotation - in that case You can use stub files.
If You want to type annotate a third party library, You can write a *.pyi file for the functions You use for that library. That can be a bit tricky, because MYPY must only find that *.pyi file ONCE in the MYPY Path.
So I handle it that way :
for local testing, the MYPY path is set to a directory were I collect all the 3rd party stubs,
for testing on travis, I have a subdirectory in the package with the stubs needed for that module to test it on travis, and set the mypy path accordingly.
The solution was to add one py.typed file to the root of the main package. This forces mypy to analyze the types.
Related
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.
I have a python package built from source code in /Document/pythonpackage directory
/Document/pythonpackage/> python setup.py install
This creates a folder in site-packages directory of python
import pythonpackage
print(pythonpackage.__file__)
>/anaconda3/lib/python3.7/site-packages/pythonpackage-x86_64.egg/pythonpackage/__init__.py
I am running a script on multiple environments so the only path I know I will have is pythonpackage.__file__. However Document/pythonpackage has some data that is not in site-packages is there a way to automatically find the path to /Document/pythonpackage given that you only have access to the module in python?
working like that is discouraged. it's generally assumed that after installing a package the user can remove the installation directory (as most automated package managers would do). instead you'd make sure your setup.py copied any data files over into the relevant places, and then your code would pick them up from there.
assuming you're using the standard setuptools, you can see the docs on Including Data Files, which says at the bottom:
In summary, the three options allow you to:
include_package_data
Accept all data files and directories matched by MANIFEST.in.
package_data
Specify additional patterns to match files that may or may not be matched by MANIFEST.in or found in source control.
exclude_package_data
Specify patterns for data files and directories that should not be included when a package is installed, even if they would otherwise have been included due to the use of the preceding options.
and then says:
Typically, existing programs manipulate a package’s __file__ attribute in order to find the location of data files. However, this manipulation isn’t compatible with PEP 302-based import hooks, including importing from zip files and Python Eggs. It is strongly recommended that, if you are using data files, you should use the ResourceManager API of pkg_resources to access them
Not sure, but you could create a repository for your module and use pip to install it. The egg folder would then have a file called PKG-INFO which would contain the url to the repository you imported your module from.
In my office we have a quite complex directory structure when it comes to our code.
One of the things we have is a libs module to drop "common" things used by other parts of our big application (or set of applications... that are all living under a common directory).
The code in that libs/ directory requires certain packages installed in order for it to work. In said libs/ directory we have a requirements.txt file that supposedly lists the dependencies required for the things (things being Python code) in it to work. We have been filling that requirements.txt file pretty manually, tracking that "if this .py file uses this module, we should add it to the requirements file" so it's almost certain that by now we have forgotten adding some required modules.
Because of the complex structure we have (some parts use pipenv, some other have their own requirements.txt...) is very hard knowing whether a required module is going to end up installed or not.
So I would like to make sure that this libs/ directory (cough, cough... module ) has all its dependencies listed in its libs/requirements.txt.
Is that possible? Ideally it'd be "run this command passing /libs/ as an argument, it'll scan the directory and tell you what packages are needed by the py(s) found in it"
Thank you in advance.
Unfortunately, python does not know whether its dependencies are satisfied until runtime. requirements.txt is just a helper file for pip and similar tools, and you have to update it manually.
That said, you could
use the os module to recursively get a list of all *.py files in the folder
parse each one of them for lines having the format import aaa.bbb or from aaa import bbb
keep a set of the imports
However, even in that case, the name of the imported module is not the same as the name you need to pass to pip (eg, import yaml requires pyyaml in requirements.txt), but at least it could be a hint of what's missing.
EDIT I was being stupid. Just type help('package_name'.'pyb_name') which worked.
I would like to find out what is actually in a python package I have locally downloaded and installed with pip.
Typing help(package_name) just lists NAME, FILE (where the init.py is) and PACKAGE CONTENTS which is just one .pyd file.
I can't open the .pyd file to check what's inside(tbh not all that familiar with .pyds). These two with a 159byte init.pyc are the only files in the package.
I need to use this (not widely available) package for some university work.
Thanks.
You can't know what a python package does unless it is stated in its docs (on PyPI or in the repository) or without reading the code. A Python package can be anything that has a setup.py and either a single module or multiple files under a folder with a __init__.py file in it.
The fact that the __init__.py is empty doesn't mean anything other than the fact that its existence means there's a python package involved.
Any specific package you want to know about, you should look up for documentation or read the code to get a sense of its purpose.
I have a Python project that has the following structure:
package1
class.py
class2.py
...
package2
otherClass.py
otherClass2.py
...
config
dev_settings.ini
prod_settings.ini
I wrote a setup.py file that converts this into an egg with the same file structure. (When I examine it using a zip program the structure seems identical.) The funny thing is, when I run the Python code from my IDE it works fine and can access the config files; but when I try to run it from a different Python script using the egg, it can't seem to find the config files in the egg. If I put the config files into a directory relative to the calling Python script (external to the egg), it works - but that sort of defeats the purpose of having a self-contained egg that has all the functionality of the program and can be called from anywhere. I can use any classes/modules and run any functions from the egg as long as they don't use the config files... but if they do, the egg can't find them and so the functions don't work.
Any help would be really appreciated! We're kind of new to the egg thing here and don't really know where to start.
The problem is, the config files are not files anymore - they're packaged within the egg. It's not easy to find the answer in the docs, but it is there. From the setuptools developer's guide:
Typically, existing programs manipulate a package's __file__ attribute in order to find the location of data files. However, this manipulation isn't compatible with PEP 302-based import hooks, including importing from zip files and Python Eggs.
To access them, you need to follow the instructions for the Resource Management API.
In my own code, I had this problem with a logging configuration file. I used the API successfully like this:
from pkg_resources import resource_stream
_log_config_file = 'logging.conf'
_log_config_location = resource_stream(__name__, _log_config_file)
logging.config.fileConfig(_log_config_location)
_log = logging.getLogger('package.module')
See Setuptools' discussion of accessing pacakged data files at runtime. You have to get at your configuration file a different way if you want the script to work inside an egg. Also, for that to work, you may need to make your config directory a Python package by tossing in an empty __init__.py file.