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