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mypy does not detect errors when wrongly using a function imported from an external package

I've run a simple experiment where I've created a very simple python package containing the following files:
In the folder my_package:
# example.py
def foo(number: int, text: str) -> None:
print(number)
print(text)
An empty __init__.py
In the root folder, a setup.py file:
from setuptools import setup
setup(
name='ExamplePackage',
version='0.1.0',
author='An Awesome Coder',
author_email='aac#example.com',
packages=['my_package'],
description='An awesome package that does something',
)
After building the package using python ./setup.py bdist_wheel I've copied the .whl file to another python project, ran pip install ExamplePackage-0.1.0-py3-none-any.whl and created the following file main.py:
from my_package.example import foo
# No mypy errors at all!
x = foo()
def internal_foo(number: int, text: str) -> None:
print(number)
print(text)
# Missing positional arguments "number", "text" in call to "internal_foo" [call-arg]
# "internal_foo" does not return a value [func-returns-value]
y = internal_foo()
My mypy.ini looks like this:
[mypy]
ignore_missing_imports = True
show_error_codes = True
strict = True
check_untyped_defs = True
raise_exceptions = True
I'm struggling to understand why mypy which could easily infer the signature of the imported foo function, does not show any errors regarding the wrong usage
Any help will be much appreciated

According to PEP-561 (a python standard that regulates use of typing data for packages), there are two general ways to declare types for package.
The first (applicable in your case) is py.typed marker. It is an empty file named py.typed, placed in package root (the same place where the topmost __init__.py resides; for namespace packages prefer adding py.typed to every submodule to avoid inconsistent interpretation). It declares that the package contains inline type information.
It is important not to forget to add it as package data. You need to add it as MANIFEST.in entry + any configuration necessary to enable it - nothing for pyproject.toml-based packages, include_package_data = True for setup.py and setup.cfg, something else (similar?) for non-setuptools distros (Poetry, flit, hatch or whatever you need for some reason). Alternatively, it can be declared in [tool.setuptools.package-data] section of pyproject.toml, package_data in setup.py, [options.package_data] in setup.cfg and something similar for other build systems. There are other options like VCS integration (from .gitignore and similar files) with appropriate plugins, refer to setuptools documentation here or docs for system of your choice.
Another supported solution is using stub files - these are separate files with .pyi extension, providing only typing for functions/methods and variables/attributes. They have a higher precedence (e.g. if there are both stubs and py.typed, stubs types are used), but this should not happen (if code can be annotated inline, then there is no need in separate stubs). Stub packages are named <package>-stubs. There are also "side-by-side" approach that allows putting .py and .pyi near each other.

What does an import statement with "..." in python mean? [duplicate]

I want to inherit from a class in a file that lies in a directory above the current one.
Is it possible to relatively import that file?

from ..subpkg2 import mod
Per the Python docs: When inside a package hierarchy, use two dots, as the import statement doc says:
When specifying what module to import you do not have to specify the absolute name of the module. When a module or package is contained within another package it is possible to make a relative import within the same top package without having to mention the package name. By using leading dots in the specified module or package after from you can specify how high to traverse up the current package hierarchy without specifying exact names. One leading dot means the current package where the module making the import exists. Two dots means up one package level. Three dots is up two levels, etc. So if you execute from . import mod from a module in the pkg package then you will end up importing pkg.mod. If you execute from ..subpkg2 import mod from within pkg.subpkg1 you will import pkg.subpkg2.mod. The specification for relative imports is contained within PEP 328.
PEP 328 deals with absolute/relative imports.

import sys
sys.path.append("..") # Adds higher directory to python modules path.

#gimel's answer is correct if you can guarantee the package hierarchy he mentions. If you can't -- if your real need is as you expressed it, exclusively tied to directories and without any necessary relationship to packaging -- then you need to work on __file__ to find out the parent directory (a couple of os.path.dirname calls will do;-), then (if that directory is not already on sys.path) prepend temporarily insert said dir at the very start of sys.path, __import__, remove said dir again -- messy work indeed, but, "when you must, you must" (and Pyhon strives to never stop the programmer from doing what must be done -- just like the ISO C standard says in the "Spirit of C" section in its preface!-).
Here is an example that may work for you:
import sys
import os.path
sys.path.append(
os.path.abspath(os.path.join(os.path.dirname(__file__), os.path.pardir)))
import module_in_parent_dir

Import module from a directory which is exactly one level above the current directory:
from .. import module

How to load a module that is a directory up
preface: I did a substantial rewrite of a previous answer with the hopes of helping ease people into python's ecosystem, and hopefully give everyone the best change of success with python's import system.
This will cover relative imports within a package, which I think is the most probable case to OP's question.
Python is a modular system
This is why we write import foo to load a module "foo" from the root namespace, instead of writing:
foo = dict(); # please avoid doing this
with open(os.path.join(os.path.dirname(__file__), '../foo.py') as foo_fh: # please avoid doing this
exec(compile(foo_fh.read(), 'foo.py', 'exec'), foo) # please avoid doing this
Python isn't coupled to a file-system
This is why we can embed python in environment where there isn't a defacto filesystem without providing a virtual one, such as Jython.
Being decoupled from a filesystem lets imports be flexible, this design allows for things like imports from archive/zip files, import singletons, bytecode caching, cffi extensions, even remote code definition loading.
So if imports are not coupled to a filesystem what does "one directory up" mean? We have to pick out some heuristics but we can do that, for example when working within a package, some heuristics have already been defined that makes relative imports like .foo and ..foo work within the same package. Cool!
If you sincerely want to couple your source code loading patterns to a filesystem, you can do that. You'll have to choose your own heuristics, and use some kind of importing machinery, I recommend importlib
Python's importlib example looks something like so:
import importlib.util
import sys
# For illustrative purposes.
file_path = os.path.join(os.path.dirname(__file__), '../foo.py')
module_name = 'foo'
foo_spec = importlib.util.spec_from_file_location(module_name, file_path)
# foo_spec is a ModuleSpec specifying a SourceFileLoader
foo_module = importlib.util.module_from_spec(foo_spec)
sys.modules[module_name] = foo_module
foo_spec.loader.exec_module(foo_module)
foo = sys.modules[module_name]
# foo is the sys.modules['foo'] singleton
Packaging
There is a great example project available officially here: https://github.com/pypa/sampleproject
A python package is a collection of information about your source code, that can inform other tools how to copy your source code to other computers, and how to integrate your source code into that system's path so that import foo works for other computers (regardless of interpreter, host operating system, etc)
Directory Structure
Lets have a package name foo, in some directory (preferably an empty directory).
some_directory/
foo.py # `if __name__ == "__main__":` lives here
My preference is to create setup.py as sibling to foo.py, because it makes writing the setup.py file simpler, however you can write configuration to change/redirect everything setuptools does by default if you like; for example putting foo.py under a "src/" directory is somewhat popular, not covered here.
some_directory/
foo.py
setup.py
.
#!/usr/bin/env python3
# setup.py
import setuptools
setuptools.setup(
name="foo",
...
py_modules=['foo'],
)
.
python3 -m pip install --editable ./ # or path/to/some_directory/
"editable" aka -e will yet-again redirect the importing machinery to load the source files in this directory, instead copying the current exact files to the installing-environment's library. This can also cause behavioral differences on a developer's machine, be sure to test your code!
There are tools other than pip, however I'd recommend pip be the introductory one :)
I also like to make foo a "package" (a directory containing __init__.py) instead of a module (a single ".py" file), both "packages" and "modules" can be loaded into the root namespace, modules allow for nested namespaces, which is helpful if we want to have a "relative one directory up" import.
some_directory/
foo/
__init__.py
setup.py
.
#!/usr/bin/env python3
# setup.py
import setuptools
setuptools.setup(
name="foo",
...
packages=['foo'],
)
I also like to make a foo/__main__.py, this allows python to execute the package as a module, eg python3 -m foo will execute foo/__main__.py as __main__.
some_directory/
foo/
__init__.py
__main__.py # `if __name__ == "__main__":` lives here, `def main():` too!
setup.py
.
#!/usr/bin/env python3
# setup.py
import setuptools
setuptools.setup(
name="foo",
...
packages=['foo'],
...
entry_points={
'console_scripts': [
# "foo" will be added to the installing-environment's text mode shell, eg `bash -c foo`
'foo=foo.__main__:main',
]
},
)
Lets flesh this out with some more modules:
Basically, you can have a directory structure like so:
some_directory/
bar.py # `import bar`
foo/
__init__.py # `import foo`
__main__.py
baz.py # `import foo.baz
spam/
__init__.py # `import foo.spam`
eggs.py # `import foo.spam.eggs`
setup.py
setup.py conventionally holds metadata information about the source code within, such as:
what dependencies are needed to install named "install_requires"
what name should be used for package management (install/uninstall "name"), I suggest this match your primary python package name in our case foo, though substituting underscores for hyphens is popular
licensing information
maturity tags (alpha/beta/etc),
audience tags (for developers, for machine learning, etc),
single-page documentation content (like a README),
shell names (names you type at user shell like bash, or names you find in a graphical user shell like a start menu),
a list of python modules this package will install (and uninstall)
a defacto "run tests" entry point python ./setup.py test
Its very expansive, it can even compile c extensions on the fly if a source module is being installed on a development machine. For a every-day example I recommend the PYPA Sample Repository's setup.py
If you are releasing a build artifact, eg a copy of the code that is meant to run nearly identical computers, a requirements.txt file is a popular way to snapshot exact dependency information, where "install_requires" is a good way to capture minimum and maximum compatible versions. However, given that the target machines are nearly identical anyway, I highly recommend creating a tarball of an entire python prefix. This can be tricky, too detailed to get into here. Check out pip install's --target option, or virtualenv aka venv for leads.
back to the example
how to import a file one directory up:
From foo/spam/eggs.py, if we wanted code from foo/baz we could ask for it by its absolute namespace:
import foo.baz
If we wanted to reserve capability to move eggs.py into some other directory in the future with some other relative baz implementation, we could use a relative import like:
import ..baz

Here's a three-step, somewhat minimalist version of ThorSummoner's answer for the sake of clarity. It doesn't quite do what I want (I'll explain at the bottom), but it works okay.
Step 1: Make directory and setup.py
filepath_to/project_name/
setup.py
In setup.py, write:
import setuptools
setuptools.setup(name='project_name')
Step 2: Install this directory as a package
Run this code in console:
python -m pip install --editable filepath_to/project_name
Instead of python, you may need to use python3 or something, depending on how your python is installed. Also, you can use -e instead of --editable.
Now, your directory will look more or less like this. I don't know what the egg stuff is.
filepath_to/project_name/
setup.py
test_3.egg-info/
dependency_links.txt
PKG-INFO
SOURCES.txt
top_level.txt
This folder is considered a python package and you can import from files in this parent directory even if you're writing a script anywhere else on your computer.
Step 3. Import from above
Let's say you make two files, one in your project's main directory and another in a sub directory. It'll look like this:
filepath_to/project_name/
top_level_file.py
subdirectory/
subfile.py
setup.py |
test_3.egg-info/ |----- Ignore these guys
... |
Now, if top_level_file.py looks like this:
x = 1
Then I can import it from subfile.py, or really any other file anywhere else on your computer.
# subfile.py OR some_other_python_file_somewhere_else.py
import random # This is a standard package that can be imported anywhere.
import top_level_file # Now, top_level_file.py works similarly.
print(top_level_file.x)
This is different than what I was looking for: I hoped python had a one-line way to import from a file above. Instead, I have to treat the script like a module, do a bunch of boilerplate, and install it globally for the entire python installation to have access to it. It's overkill. If anyone has a simpler method than doesn't involve the above process or importlib shenanigans, please let me know.

Polished answer of #alex-martelli with pathlib:
import pathlib
import sys
_parentdir = pathlib.Path(__file__).parent.parent.resolve()
sys.path.insert(0, str(_parentdir))
import module_in_parent_dir
sys.path.remove(str(_parentdir))

To run python /myprogram/submodule/mymodule.py which imports /myprogram/mainmodule.py, e.g., via
from mainmodule import *
on Linux (e.g., in the python Docker image), I had to add the program root directory to PYTHONPATH:
export PYTHONPATH=/myprogram

It is 2022 and none of the answers really worked for me. Here is what worked in the end
import sys
sys.path.append('../my_class')
import my_class
My directory structure:
src
--my_class.py
notebooks
-- mynotebook.ipynb
I imported my_class from mynotebook.ipynb.

You can use the sys.path.append() method to add the directory containing the package to the list of paths searched for modules. For example, if the package is located two directories above the current directory, you can use the following code:
import sys
sys.path.append("../../")
if the package is location one directory above the current directory, you can use below code:
import sys
sys.path.append("..")

Python is a modular system
Python doesn't rely on a file system
To load python code reliably, have that code in a module, and that module installed in python's library.
Installed modules can always be loaded from the top level namespace with import <name>
There is a great sample project available officially here: https://github.com/pypa/sampleproject
Basically, you can have a directory structure like so:
the_foo_project/
setup.py
bar.py # `import bar`
foo/
__init__.py # `import foo`
baz.py # `import foo.baz`
faz/ # `import foo.faz`
__init__.py
daz.py # `import foo.faz.daz` ... etc.
.
Be sure to declare your setuptools.setup() in setup.py,
official example: https://github.com/pypa/sampleproject/blob/master/setup.py
In our case we probably want to export bar.py and foo/__init__.py, my brief example:
setup.py
#!/usr/bin/env python3
import setuptools
setuptools.setup(
...
py_modules=['bar'],
packages=['foo'],
...
entry_points={},
# Note, any changes to your setup.py, like adding to `packages`, or
# changing `entry_points` will require the module to be reinstalled;
# `python3 -m pip install --upgrade --editable ./the_foo_project
)
.
Now we can install our module into the python library;
with pip, you can install the_foo_project into your python library in edit mode,
so we can work on it in real time
python3 -m pip install --editable=./the_foo_project
# if you get a permission error, you can always use
# `pip ... --user` to install in your user python library
.
Now from any python context, we can load our shared py_modules and packages
foo_script.py
#!/usr/bin/env python3
import bar
import foo
print(dir(bar))
print(dir(foo))

Confused about packing python projects

I've been coding in Python for long, but never actually tried to pack a piece of code so that I can share it. I started reading
https://python-packaging.readthedocs.io/en/latest/.
I started with the simplest possible case, say I want to share a module named 'clipper', and the only important thing is a class called Clipper. It seems in case I use setuptools I should create somewhere folders
clipper/clipper
and inside the inner clipper, place a file __init__.py
with the definition of class Clipper. So far so good. Theoretically, after installing the package, the way to use the class would be:
import clipper
cl = clipper.Clipper()
My problem is, I am assuming that while I am developing and before any installation, the same code should work. I mean, the previous code should create an instance of the object. But how would that work? How should I set PYTHONPATH so that the previous import would actually work?
Maybe I got something really wrong, I thought packing would be easier compared to coding, but I've spent some time and I don't get it. Any help, please?

Rather than modifying your Python path, install the packaged module as an editable version and your environment will handle this for you. When you have it running as an editable version you'll be able to make changes to the code on your local development instance.
For example, assuming you have Pip you can run the following command in the first 'clipper' folder (the same folder as the setup.py file you created during packaging):
pip install -e .
-e means editable
the . means install the package located in the current folder.
More detail here in an SO answer from 2015: "pip install --editable ./" vs "python setup.py develop"

Your directory tree would look a bit like this:
~/clipper/
setup.py
clipper/
__init__.py
clipper.py
The setup.py file contains information telling Python how to 'parse' your package. Things like the name of your project, the version and what packages to include are defined here. For your example, setup.py may look like this:
from distutils.core import setup
setup(
name="Clipper",
# A name for your package, typically your project name
description="My first package",
# A short description
version="1.0.0",
# A version specification
packages=["clipper"]
# A list of packages to include
)
Within clipper, clipper.py contains the actual Clipper class:
class Clipper(object):
def __init__(self):
pass
def foo(self):
print("Invoked foo!")
__init__.py is a special type of file. It defines the public interface for interacting with your package. Typically, it imports all public functions and classes:
from .clipper import Clipper
Finally, to turn this into a proper package, run python3 setup.py sdist. This creates the source distribution for your package and allows you to import it 1. Let's try that now. Navigate back to ~/clipper/ and start Python:
>>> from clipper import Clipper
>>> c = Clipper()
>>> c.foo()
Invoked foo!
>>>
And here's 'real' example of what a package directory would look like:
~/calculator/
setup.py
calculator/
__init__.py
add.py
substract.py
setup.py
from distutils.core import setup
setup(
name="Calculator",
description="Calculate stuff!",
version="1.0.0",
packages=["calculator"]
)
__init__.py
from .add import *
from .substract import *
add.py
def add(a, b):
"""Return `a` + `b`."""
return a + b
substract.py
def substract(a, b):
"""Return `a` - `b`."""
return a - b
For more information, see the Python tutorial on packaging.
1 You may get some warnings about missing information, but you can ignore that for now.

Python Namespace Packages in Python3

The topic of namespace packages seems a bit confusing for the uninitiated, and it doesn't help that prior versions of Python have implemented it in a few different ways or that a lot of the Q&A on StackOverflow are dated. I am looking for a solution in Python 3.5 or later.
#The scenario:
I'm in the process of refactoring a bunch of Python code into modules and submodules, and working to get each of these projects set up to operate independently of each other while sitting in the same namespace.
We're eventually going to be using an internal PyPi server, serving these packages to our internal network and don't want to confuse them with external (public) PyPi packages.
Example: I have 2 modules, and I would like to be able to perform the following:
from org.client.client1 import mod1
from org.common import config
The reflected modules would be separated as such:
Repository 1:
org_client_client1_mod1/
setup.py
mod1/
__init__.py
somefile.py
Repository 2:
org_common_config/
setup.py
config/
__init__.py
someotherfile.py
My Git repositories are already setup as org_client_client1_mod1 and org_common_config, so I just need to perform the setup on the packaging and __init__.py files, I believe.
Questions:
#1
With the __init__.py, which of these should I be using (if any)?:
from pkgutil import extend_path
__path__ = extend_path(__path__, __name__)
Or:
import pkg_resources
pkg_resources.declare_namespace(__name__)
#2
With setup.py, do I still need to add the namespace_modules parameter, and if so, would I use namespace_modules=['org.common'],
or namespace_modules=['org', 'common']?
#3
Could I forgo all of the above by just implementing this differently somehow? Perhaps something simpler or more "pythonic"?

Late to the party, but never hurts to help fellow travellers down the namespace path in Python!
#1:
With the __init__.py, which of these should I be using (if any)?:
It depends, There are three ways to do namespace packages as listed here:
Use native namespace packages. This type of namespace package is defined in PEP 420 and is available in Python 3.3 and later. This is recommended if packages in your namespace only ever need to support Python 3 and installation via pip.
Use pkgutil-style namespace packages. This is recommended for new packages that need to support Python 2 and 3 and installation via both pip and python setup.py install.
Use pkg_resources-style namespace packages. This method is recommended if you need compatibility with packages already using this method or if your package needs to be zip-safe.
If you are using #2 (pkgutil-style) or #3 (pkg_resources-style), then you will have to use the corresponding style for __init__.py files. If you use native namespaces then no __init__.py in the namespace directory.
#2:
With setup.py, do I still need to add the namespace_modules parameter, and if so, would I use namespace_modules=['org.common'], or namespace_modules=['org', 'common']?
If your choice of namespace package is not native style, then yes, you will need namespace_packages in your setup().
#3:
Could I forgo all of the above by just implementing this differently somehow? Perhaps something simpler or more "pythonic"?
Since you ended up down to a complex topic in python, it seems you know what you are doing, what you want and identified that creating a Python Namespace package is the way to do it. This would be considered a pythonic way to solve a problem.
Adding to your questions, here are a few things I discovered:
I read PEP420, the Python Packaging guide and spent a lot of time understanding the namespace packages, and I generally understood how it worked. I read through a couple of answers here, here, here, and this thread on SO as well - the example here and on the Git link shared by Rob.
My problem however was after I created my package. As all the instructions and sample code explicitly listed the package in the setuptools.setup(package=[]) function, my code failed. My sub-packages/directories were not included. Digging deeper, I found out that setuptools has a find_namespace_package() function that helps in adding sub-packages too
EDIT:
Link to find_namespace_packages() (setuptools version greater than 40.1.0): https://setuptools.readthedocs.io/en/latest/setuptools.html#find-namespace-packages
EDIT (08/09/2019):
To complete the answer, let me also restructure with an example.
The following solution is assuming Python 3.3+ which has support for implicit namespace packages
Since you are looking for a solution for Python version 3.5 or later, let's take the code samples provided and elaborate further.
Let's assume the following:
Namespace/Python package name : org
Distribution packages: org_client, org_common
Python: 3.3+
setuptools: 40.1.0
For you to do the following
from org.client.client1 import mod1
from org.common import config
And keeping your top level directories the same, viz. org_client_client1_mod1 and org_common_config, you can change your structure to the following
Repository 1:
org_client_client1_mod1/
setup.py
org/
client/
client1/
__init__.py
submod1/
__init__.py
mod1/
__init__.py
somefile.py
file1.py
Updated setup.py
from setuptools import find_namespace_packages, setup
setup(
name="org_client",
...
packages=find_namespace_packages(), # Follows similar lookup as find_packages()
...
)
Repository 2:
org_common_config/
setup.py
org/
common/
__init__.py
config/
__init__.py
someotherfile.py
Updated setup.py:
from setuptools import find_namespace_packages, setup
setup(
name="org_common",
...
packages=find_namespace_packages(), # Follows similar lookup as find_packages()
...
)
To install (using pip):
(venv) $ pip3 install org_common_config/
(venv) $ pip3 install org_client_client1_mod1/
Updated pip list will show the following:
(venv) $ pip3 list
...
org_client
org_common
...
But they won't be importable, for importing you will have to follow org.client and org.common notation.
To understand why, you can browse here (assuming inside venv):
(venv) $ cd venv/lib/python3.5/site-packages/
(venv) $ ls -l | grep org
You'll see that there's no org_client or org_common directories, they are interpreted as a namespace package.
(venv) $ cd venv/lib/python3.5/site-packages/org/
(venv) $ ls -l
client/
common/
...

This is a tough subject. All the -'s, _'s, and __init__.py's everywhere don't exactly make it easy on us.
First, I'll answer your questions:
With the __init__.py, which of these should I be using (if any)?
__init__.py can be completely empty, it just needs to be in the correct place. Namely (pun) they should be in any subpackage containing python code (excluding setup.py.) Follow those rules and you should be fine.
With setup.py, do I still need to add the namespace_modules parameter, and if so, would I use namespace_modules=['org.common'], or namespace_modules=['org', 'common']?
Nope! Only name= and packages=. However, note the format of the packages= arg compared against the directory structure.
Here's the format of the package= arg:
Here's the corresponding directory structure:
Could I forgo all of the above by just implementing this differently somehow? Perhaps something simpler or more "pythonic"?
If you want to be able to install multiple features individually, but under the same top-level namespace, you're on the right track.
I'll spend the rest of this answer re-implementing your namespace package in native format:
I'll put all helpful documentation I've been able to find at the bottom of the post.
K so I'm going to assume you want native namespace packages. First let's look at the current structure of your 2 repos:
org_client_client1_mod1/
setup.py
mod1/
__init__.py
somefile.py
&
org_common_config/
setup.py
config/
__init__.py
someotherfile.py
This^ would be too easy!!!
To get what you want:
My brain isn't elastic enough to know if we can go 3-levels deep with namespace packages, but to do what you want, here's what I'm pretty sure you'd want to do:
org-client/
setup.py
org/
client/
client1/
__init__.py
mod1/
__init__.py
somefile.py
&
org-common-but-also-note-this-name-doesnt-matter/
setup.py
org/
common/
__init__.py
config/
__init__.py
someotherfile.py
Basically then the key is going to be specifying the correct name= & packages= args to stuptools.setup() inside of each setup.py.
These are going to be:
name='org_client',
...
packages=['org.client']
&
name='org_common'
...
packages['org.common']
respectively.
Then just install each one with pip install . inside each top-level dir.
Installing the first one will give you access to the somefile.py module, and installing the second will give you access to someotherfile.py. It also won't get confused about you trying to install 2 packages named org in the same environment.
K so the most helpful section of the docs: https://packaging.python.org/guides/packaging-namespace-packages/#packaging-namespace-packages
And then here's how I actually came to understand this: https://github.com/pypa/sample-namespace-packages/tree/master/native

Let sphinx use version from setup.py

If I do sphinx-quickstart I get asked about the version of the project.
I want to avoid to have two places for the version of my project.
How to do this in the python packing world?

The easiest (and probably cleanest) way is to define __version__ for the __init__.py of your top-level package, and then import that package and read the version in both setup.py and your Sphinx project's conf.py.
So lets say your project is called myproject.
Move your current version out of setup.py, and make it a variable in myproject/__init__.py instead:
myproject/__init__.py:
# import foo
# ...
__version__ = '1.5'
Import myproject in your project's setup.py, and replace the hardcoded version with myproject.__version__:
setup.py:
from setuptools import setup
from myproject import __version__
project = "myproject"
setup(
name=project,
version=__version__,
# ...
)
In your Sphinx project's conf.py, do the same. So edit the generated conf.py along these lines:
docs/conf.py:
from myproject import __version__
# ...
# The short X.Y version.
version = __version__
# The full version, including alpha/beta/rc tags.
release = version
For an example of a library that does this pretty much exactly like this, have a look at the requests module (__init__.py | setup.py | conf.py).
This will take care of the auto-generated texts where the project version is used (like the links to the front page of the documentation). If you want to use your version in specific custom places, you can use the rst_epilog directive to dynamically insert configuration values defined in conf.py.

Maybe an even cleaner option is to actually build sphinx from the setup.py command as described in http://www.sphinx-doc.org/en/master/setuptools.html:
setup.py
# this is only necessary when not using setuptools/distribute
from sphinx.setup_command import BuildDoc
cmdclass = {'build_sphinx': BuildDoc}
name = 'My project'
version = '1.2'
release = '1.2.0'
setup(
name=name,
author='Bernard Montgomery',
version=release,
cmdclass=cmdclass,
# these are optional and override conf.py settings
command_options={
'build_sphinx': {
'project': ('setup.py', name),
'version': ('setup.py', version),
'release': ('setup.py', release),
'source_dir': ('setup.py', 'doc')}},
)
Then build documentation using
$ python setup.py build_sphinx
Benefits:
Makes setup.py the single source of version number
Avoids having to make packages out of your project folders unnecessarily

You could have a look at bumpversion module:
"A small command line tool to simplify releasing software by updating all version strings in your source code by the correct increment"
You may use a configuration file .bumpversion.cfg for complex multi-file operations.

Another way is integrating setuptools_scm in your project. This way you can
from setuptools_scm import get_version
version = get_version()
in your conf.py

Here is a straightforward solution, ironically from the setuptools_scm PyPI page:
# contents of docs/conf.py
from importlib.metadata import version
release = version('myproject')
# for example take major/minor
version = '.'.join(release.split('.')[:2])
Here is their explanation why it is discouraged to use their package from Sphinx:
The underlying reason is, that services like Read the Docs sometimes change the working directory for good reasons and using the installed metadata prevents using needless volatile data there.

Extract Information from pyproject.toml
If you use a pyproject.toml you could also parse it in the conf.py with tomli or use the equivalent tomllib when you are on python ^3.11.
Like this you can extract the information from the pyproject.toml and use it in your sphinx documentation configuration.
Here a short incomplete example using tomli, assuming conf.py
is located at <project-root>/docs/source/conf.py:
# conf.py
import tomli
with open("../../pyproject.toml", "rb") as f:
toml = tomli.load(f)
# -- Project information -----------------------------------------------------
pyproject = toml["tool"]["poetry"]
project = pyproject["name"]
version = pyproject["version"]
release = pyproject["version"]
copyright = ...
author = ...
# and the rest of the configuration