python-imports | Python imports '' blog post | Learning library

You are getting a ModuleNotFoundError because the interpreter is searching for a global module named tata, and not looking in the current directory. You are also repeating this behavior, in your first code block.

In the following snippet you are running main.py as python path/to/main.py

It appears you're using black and double-quote-strings-fixer together

• the former likes double quoted strings in python (you can disable this by configuring black to skip-string-normalization in pyproject.toml)
• the latter likes single quoted strings in python (you can remove it if you'd like double quoted strings)

If two formatters fight, the end result will be a failure as pre-commit checks to make sure everything resolves

disclaimer: I'm the author of pre-commit and pre-commit-hooks

You're probably not accessing main.py from the same folder. Check your working directory. What edition of PyCharm are you using? Can you run it from the terminal? Also, did you try removing the directory prefix so it's just from downloader import ImgurAlbumDownloader?

My final tip would be to follow a conventional project structure where your tests are in a different folder: What is the best project structure for a Python application?

You should create a virtual environment and install the project in order for the test modules to correctly resolve import statements.

In the project root, i.e. the directory project_name which contains a subdirectory project_name and a subdirectory tests, create a setup.py (or pyproject.toml) file for the package metadata. See here for details about that part.

From this same project root directory which is now containing the installer (setup.py), create and activate a venv and install your project:

The difference between math and string is that math is written in C for speed purposes and string module is written in Python and can be found under the python lib dir.

So, when you trying to import string, the local file will override the global string file, but when you try to import math Python will not search for a file, since it's built in the Python interpreter.

You can find the list of all the built-in modules with the following code:

Absolute imports, like import x.y.z or from x.y import z require x to be in your path. In your specific case, myModel is on the path because of your working directory. The sub-packages are not on the path, and can therefore only be accessed by reiterating the root package.

A more intuitive approach might be to use relative paths. This is possible because all your files live in proper packages with __init__ files. Keep in mind that relative paths imply that you have modules that are designed to live in your package structure and not on their own. Otherwise, you may end up causing errors when you try to run some of the modules as standalone scripts.

Change myModel/__init__.py to:

The problem is when you do python code/main.py it makes your current working directory code/, which makes all of your absolute imports incorrect since Python doesn't see above that directory unless you explicitly change a setting like the PYTHONPATH environment variable.

Your best option is to rename main.py to __main__.py and then use python -m code (although do note that package name clashes with a module in the stdlib).

You also don't need the __init__.py in my_app/ unless you're going to treat that entire directory as a package.

And I would consider using relative imports instead of absolute ones (and I would also advise importing to the module and not the object/class in a module in your import statements to avoid circular import issues). For instance, for the from code.module_1.some_code_1 import class_1 line in code.main, I would make it from .module_1 import some_code_1.

I don't know if I missunderstood something but it should work with:

Fundamentally what you've described is a supporting library that goes with a set of applications that run on top of it. They happen to be in the same repository (a "monorepo") but that's okay.

The first step is to take your library and package it up like a normal Python library would be. The Python Packaging User Guide has a section on Packaging and distributing projects, which is mostly relevant; though you're not especially interested in uploading the result to PyPI. You at the very least need the setup.py file described there.

With this reorganization you should be able to do something like