Another developer and I disagree about whether PYTHONPATH
or sys.path
should be used to allow Python to find a Python package in a user (e.g., development) directory.
We have a Python project with a typical directory structure:
Project setup.py package __init__.py lib.py script.py
In script.py, we need to do import package.lib
. When the package is installed in site-packages, script.py can find package.lib
.
When working from a user directory, however, something else needs to be done. My solution is to set my PYTHONPATH
to include "~/Project"
. Another developer wants to put this line of code in the beginning of script.py:
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
So that Python can find the local copy of package.lib
.
I think this is a bad idea, as this line is only useful for developers or people running from a local copy, but I can't give a good reason why it is a bad idea.
Should we use PYTOHNPATH
, sys.path
, or is either fine?
PYTHONPATH is related to sys. path very closely. PYTHONPATH is an environment variable that you set before running the Python interpreter. PYTHONPATH , if it exists, should contain directories that should be searched for modules when using import .
sys. path is a built-in variable within the sys module. It contains a list of directories that the interpreter will search in for the required module. When a module(a module is a python file) is imported within a Python file, the interpreter first searches for the specified module among its built-in modules.
Python's behavior is greatly influenced by its environment variables. One of those variables is PYTHONPATH. It is used to set the path for the user-defined modules so that it can be directly imported into a Python program. It is also responsible for handling the default search path for Python Modules.
which python is the path to your python interpreter. PYTHONPATH is an environment variable where your Python program can search for modules to import.
If the only reason to modify the path is for developers working from their working tree, then you should use an installation tool to set up your environment for you. virtualenv is very popular, and if you are using setuptools, you can simply run setup.py develop
to semi-install the working tree in your current Python installation.
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