P2-7.9 Supplementary Learning: Checking Local Python Environment Problems¶

Section ID: P2-7.9 Version: v2026.09.15

A missing python command and a failed import numpy occur at different points. The former requires checking how the shell finds commands; the latter requires checking packages in the running Python. Identical Python versions can belong to different virtual environments, so compare executable paths too.

Error Messages and What to Check¶

The Python Command Being Run¶

Check the version of the Python command used in the terminal.

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python --version

On macOS/Linux, python3 --version may work; on Windows, py --version may work depending on installation. One failure does not prove that no interpreter exists.

PATH is the directory list the shell searches for executable files. An installed Python may not be invoked because of the command name, PATH, or execution aliases. For operating-system-specific installation and command checks, see the official links in Installing Python.

The Actual Interpreter and Working Directory¶

Run this code in the notebook kernel or script environment where the error occurred. It prints the current Python executable, environment path, and working directory.

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import os
import sys

print("Python:", sys.executable)
print("Environment:", sys.prefix)
print("Virtual environment:", sys.prefix != sys.base_prefix)
print("Working directory:", os.getcwd())

In a standard venv, sys.prefix differs from sys.base_prefix. This directly checks the environment of the running Python instead of relying on memory of activation. An editor or notebook may select a different interpreter from the terminal.

Different Virtual Environments with the Same Version¶

The following illustrates outputs from Python in two different projects.

The versions match, but the paths identify separate environments. Installation can succeed in A while import numpy fails in B. To run project B, install the required packages in B’s Python. Different paths do not always indicate an error; what matters is whether the selected environment meets the project’s requirements.

pip and Package Locations¶

In a terminal with the intended Python selected, run:

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python -m pip --version
python -m pip show numpy

The first command shows pip’s version and installation location. If NumPy is installed, the second shows its version and Location; otherwise, it reports that the package was not found.

python -m pip runs pip using the Python specified at the start of the command. Run the actual code with the same Python to use that installation. See Installing and Running with the Environment’s Python for directly specifying its path.

If the required NumPy is absent, install it with the same Python.

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python -m pip install numpy

Running this code in that environment prints NumPy’s version and the location of the imported file.

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import numpy as np

print("NumPy:", np.__version__)
print("File:", np.__file__)

If an installation list is provided, use python -m pip install -r requirements.txt to prepare the project requirements instead of installing packages individually.

Permission Errors and Missing Packages¶

Installing packages into a system location can fail due to missing write permissions. Creating a virtual environment in the project folder and installing with its Python can prepare packages without changing system packages.

Permission denied concerns access permissions; ModuleNotFoundError means the running Python cannot find a module. For the latter, check whether installation occurred in another environment, was incomplete, or the imported name is wrong.

Actions Based on Check Results¶

Keep these environment checks with the installation list, data, and execution-location records described in Dependencies and Reproducibility, so later runs can be compared.

Dependency Conflicts and Files with the Same Name¶

An installed package can still conflict with the version another package requires. Select the Python used for execution and check its declared dependencies.

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python -m pip check

Read which package requires what and which version is installed. Resolve conflicts against the project’s installation list and supported versions. No broken requirements found. means declared dependency checks passed; it does not guarantee every import or program execution will succeed.

Another cause is a project file such as numpy.py. Python can search the script’s directory before installed packages and import that file instead of NumPy. If np.file points to the project file, rename the example and rerun in a fresh Python process or restarted kernel. Do not treat AttributeError or circular-import errors automatically as missing packages requiring reinstallation.

Checklist¶

• You can distinguish missing-command errors from missing-package errors.
• You can explain that the same Python version may have different executable paths.
• You can inspect the current environment with sys.executable and sys.prefix.
• You can compare the Python used for installation with the Python running the code.
• You can check package installation and usage locations with pip show and import results.
• You can use error messages to separate command, environment, permission, and file problems.

Sources and References¶

• Python Software Foundation, Python Setup and Usage, Python 3 documentation, checked 2026-07-20. Used as background for the local environment checking order by confirming the documentation structure for platform-specific Python setup and interpreter invocation.
• Python Software Foundation, Using Python on Windows, Python 3 documentation, checked 2026-07-20. Used to confirm that Python execution commands and installation methods on Windows have separate official guidance.
• Python Software Foundation, Using Python on Unix platforms, Python 3 documentation, checked 2026-07-20. Used to confirm that Python execution commands and installation paths on Unix/Linux can differ by environment.

• Python Software Foundation, venv — Creation of virtual environments, Python 3 documentation, checked 2026-07-20. Used to support checking virtual-environment activation together with package installation location.

• Python Software Foundation, sys — System-specific parameters and functions, checked 2026-09-08. Source for sys.executable, sys.prefix, and sys.base_prefix when checking interpreter and virtual-environment paths.

• pip check, Accessed: 2026-09-15.

• Python tutorial: Module search path, Accessed: 2026-09-15.