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:orphan:
.. Reason for orphan: This page is referenced by the installation
instructions, which have moved from Sphinx to https://numpy.org/install.
All install links in Sphinx now point there, leaving no Sphinx references
to this page.
***************************
Troubleshooting ImportError
***************************
.. note::
Since this information may be updated regularly, please ensure you are
viewing the most `up-to-date version <https://numpy.org/devdocs/user/troubleshooting-importerror.html>`_.
ImportError
===========
In certain cases a failed installation or setup issue can cause you to
see the following error message::
IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE!
Importing the numpy c-extensions failed. This error can happen for
different reasons, often due to issues with your setup.
The error also has additional information to help you troubleshoot:
* Your Python version
* Your NumPy version
Please check both of these carefully to see if they are what you expect.
You may need to check your ``PATH`` or ``PYTHONPATH`` environment variables
(see `Check Environment Variables`_ below).
The following sections list commonly reported issues depending on your setup.
If you have an issue/solution that you think should appear please open a
NumPy issue so that it will be added.
There are a few commonly reported issues depending on your system/setup.
If none of the following tips help you, please be sure to note the following:
* how you installed Python
* how you installed NumPy
* your operating system
* whether or not you have multiple versions of Python installed
* if you built from source, your compiler versions and ideally a build log
when investigating further and asking for support.
Using Python from ``conda`` (Anaconda)
--------------------------------------
Please make sure that you have activated your conda environment.
See also the `conda user-guide <https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#activating-an-environment>`_.
If you use an external editor/development environment it will have to be set
up correctly. See below for solutions for some common setups.
Using PyCharm with Anaconda/conda Python
----------------------------------------
There are fairly common issues when using PyCharm together with Anaconda,
please see the `PyCharm support <https://www.jetbrains.com/help/pycharm/conda-support-creating-conda-virtual-environment.html>`_
Using VSCode with Anaconda/conda Python (or environments)
---------------------------------------------------------
A commonly reported issue is related to the environment activation within
VSCode. Please see the `VSCode support <https://code.visualstudio.com/docs/python/environments>`_
for information on how to correctly set up VSCode with virtual environments
or conda.
Using Eclipse/PyDev with Anaconda/conda Python (or environments)
----------------------------------------------------------------
Please see the
`Anaconda Documentation <https://docs.anaconda.com/anaconda/user-guide/tasks/integration/eclipse-pydev/>`_
on how to properly configure Eclipse/PyDev to use Anaconda Python with specific
conda environments.
Raspberry Pi
------------
There are sometimes issues reported on Raspberry Pi setups when installing
using ``pip3 install`` (or ``pip`` install). These will typically mention::
libf77blas.so.3: cannot open shared object file: No such file or directory
The solution will be to either::
sudo apt-get install libatlas-base-dev
to install the missing libraries expected by the self-compiled NumPy
(ATLAS is a possible provider of linear algebra).
*Alternatively* use the NumPy provided by Raspbian. In which case run::
pip3 uninstall numpy # remove previously installed version
apt install python3-numpy
Debug build on Windows
----------------------
Rather than building your project in ``DEBUG`` mode on windows, try
building in ``RELEASE`` mode with debug symbols and no optimization.
Full ``DEBUG`` mode on windows changes the names of the DLLs python
expects to find, so if you wish to truly work in ``DEBUG`` mode you will
need to recompile the entire stack of python modules you work with
including NumPy
All Setups
----------
Occasionally there may be simple issues with old or bad installations
of NumPy. In this case you may just try to uninstall and reinstall NumPy.
Make sure that NumPy is not found after uninstalling.
Development Setup
-----------------
If you are using a development setup, make sure to run ``git clean -xdf``
to delete all files not under version control (be careful not to lose
any modifications you made, e.g. ``site.cfg``).
In many cases files from old builds may lead to incorrect builds.
Check Environment Variables
---------------------------
In general how to set and check your environment variables depends on
your system. If you can open a correct python shell, you can also run the
following in python::
import os
print("PYTHONPATH:", os.environ.get('PYTHONPATH'))
print("PATH:", os.environ.get('PATH'))
This may mainly help you if you are not running the python and/or NumPy
version you are expecting to run.
C-API incompatibility
---------------------------
If you see an error like:
RuntimeError: module compiled against API version v1 but this version of numpy is v2
You may have:
* A bad extension "wheel" (binary install) that should use
`oldest-support-numpy <https://pypi.org/project/oldest-supported-numpy/>`_ (
with manual constraints if necessary) to build their binary packages.
* An environment issue messing with package versions.
* Incompatible package versions somehow enforced manually.
* An extension module compiled locally against a very recent version
followed by a NumPy downgrade.
* A compiled extension copied to a different computer with an
older NumPy version.
The best thing to do if you see this error is to contact
the maintainers of the package that is causing problem
so that they can solve the problem properly.
However, while you wait for a solution, a work around
that usually works is to upgrade the NumPy version::
pip install numpy --upgrade
|
