Standard Installation

The recommended (and most straightforward) method for users to install apexpy is through PyPI. From the command line use pip 1:

pip install apexpy

You should be able to import apexpy and run basic conversions as shown in the examples. If you get errors or warnings upon importing, see below for more advanced options and troubleshooting.

Tested environments

The package has been tested with the following setups (others might work, too):

  • Windows (64 bit Python), Linux (64 bit), and Mac (64 bit)

  • Python 3.7, 3.8, 3.9, 3.10

Advanced Installation

If you cannot install apexpy from the distribtuion available on PyPI, you will have to use one of the following more advanced options. These are generally only recommended if you are planning on developing or modifying the apexpy source code.

The code behind this package is written in Fortran. Because of this, you MUST have a fortran compiler installed on your system before you attempt the following steps. Gfortran is a free compiler that can be installed, if one is not already available on your system. If you are installing this or MinGW in Windows, make sure you install it after installing the Windows Microsoft C++ Build tools. You must also make sure that the compilers and Python that are installed both use the same processing standard (either 32-bit or 64-bit). The apexpy installation has been tested successfully with gfortran 7 and some more recent versions. Earlier versions of gfortran may not work and are not recommended.

Installation also requires a C compiler of the same type as the fortran compiler. GCC is a free compiler that works with Gfortran and can be installed from a variety of sources and standard package managers. It is recommended that you check to see if you have gcc available on your system before installing as it is relatively common and multiple competing versions may cause problems if paths are not managed carefully.

This package requires NumPy, which you can install alone or as a part of SciPy. Some Python distributions come with NumPy/SciPy pre-installed. For Python distributions without NumPy/SciPy, various package managers for different operating systems allow for simple local installation (as directed on the SciPy installation page. Pip should install NumPy automatically when installing apexpy, but if not, install it manually before attempting to install apexpy. apexpy is not compatible with NumPy version 1.19.X, older and newer versions of NumPy work without issue.

IMPORTANT: If you are struggling with installing apexpy and trying some of the following options, it is recommended that you user the --no-cache flag with pip to avoid repeatedly reinstalling the same non-functional build.

Install from GitHub

apexpy can be installed from the source code on GitHub, so long as a fortran compiler is available:

pip install git+

This is advantageous if you would like to install from a particular branch or tag instead of the latest published stable release on PyPI. Do this by appending @target-branch to the end of the above command. For instance, if you would like to install from the develop branch instead of main, the appropriate command would be:

pip install git+

Install without Wheels

Many times, skipping building wheels locally will solve installation problems, but it requires that both libgfortran and gfortran are installed on your system:

pip install --no-binary :apexpy: apexpy

This is the default option for Linux, and so should not be an issue there. On Windows with the Mingw32 compiler, you might find this information useful for helping build apexpy.

Install against an incompatible numpy version

pip install apexpy –no-build-isolation –no-cache

Installation using CI Wheels

If your local set up is essentially identical to one of the CI test environments, then you can use one of the wheel artifacts to install apexpy. The list of artifacts may be found here.

To download an artifact:

  1. If you don’t have a GitHub Personal Access Token, follow these instructions to create one.

  2. Run curl -v -H "Authorization: token <GITHUB-ACCESS-TOKEN>"<ARTIFACT-ID>/zip, where <ITEM> should be replaced with the appropriate item string.

  3. Copy the URL from the Location output produced by the previous command into a browser, which will download a zip archive into your standard download location. Alternatively (or if this doesn’t work) you can use wget to retrieve the archive.

  4. Copy the zip archive into the apexpy/dist directory and unzip.

  5. Check the archive for the expected matrix of *.whl objects

To install, use pip install .

Build from Source

If you intend to modify or contribute to apexpy, you should install apexpy by forking the repository and installing it locally or within a virtual environment. After cloning the fork (see Contributing), you may install by:

cd apexpy
python -m build .
pip install .

Note that the -e flag for pip, which performs what used to be python develop, isn’t used here. That’s because meson currently doesn’t support develop style builds.

If the above command doesn’t work for you (as may be the case for Windows), you can try:

cd apexpy
meson setup build
ninja -j 2 -C build
cd build
meson install

Specifying Compilers

When you install apexpy from the command line you can specify the compilers you would like to use. These can be changed by altering the CC and FC environment variables on your computer:

FC=/path/to/correct/gfortran CC=/path/to/correct/gcc python -m build
pip install .

This can be useful your system has multiple versions of gfortran or gcc and the default is not appropriate (ie., an older version). If using an Intel compiler, you will need to clone the repository locally and uncomment a line at the top of src/fortranapex/igrf.f90 to ensure all necessary libraries are imported.

When All Else Fails

Because the base code is in Fortran, installation can be tricky and different problems can arise even if you already have a compiler installed. The following are a series of installation commands that users have reported working for different system configurations. We have not been able to reproduce some of the issues users report and cannot fully explain why some of the options work, none the less they are recorded here as they may be useful to other users. If you feel like you can provide more insight on the situations where these commands are appropriate or discover a new installation process that works for your system when none of the previously described standard approaches work, please consider contributing to this documentation (see Contributing).

Problems have been encountered when installing in a conda environment. In this case, pip seems to ignore the installed NumPy version when installing. This appears to result in a successful installation that fails upon import or causes a RuntimeError. This happens when the version of NumPy used to build apexpy is newer than the system version of NumPy (NumPy may not be forwards compatible). In this case, try:

pip install apexpy --no-build-isolation --no-cache

Apple Silicon systems require certain compilation flags to deal with memory problems. apexpy may appear to install and import correctly, but then fail with BUS errors when used. In this case, the following command has worked:

CFLAGS="-falign-functions=8 ${CFLAGS}" pip install --no-binary :apexpy: apexpy

If you are on Apple and encounter a library error such as ld: library not found for -lm, you will need to provide an additional linking flag to the Mac OSX SDK library:

LDFLAGS="-L/Library/Developer/CommandLineTools/SDKs/MacOSX.sdk/usr/lib ${LDFLAGS}" pip install .

This example assumes you are building locally from the cloned Git repository. Issues on Mac OS have also been encountered when using clang for CC alongside gfortran. This resulted in a seemly successful installation with apexpy reporting that fortranapex cannot be imported.

Some users have reported unusual behavior when using Anaconda on Apple Silicon systems. Anaconda will attempt to build and install the Intel versions of wheels instead of the M1 versions and run everything through Rosetta. This configuration has not been fully evaluated, but it results in a seemly successful installation with apexpy reporting that fortranapex cannot be imported. Users should confirm that wheels created by conda (both for apexpy and other packages) end in arm64.whl not osx-64.whl. If the later is true, users should consider uninstalling anaconda completely, and instead installing miniconda following these instructions, which has been confirmed to work. WARNING: This will remove any environments you have set up and likely undo all IDE settings, so be cautious and consider backing up your work first!

Windows systems are known to have issues with Fortran-based codes. The Windows testing we do uses miniconda, so we recommend using the Anaconda environment. One problem that has been encountered is a lack of LAPACK/BLAS tools that causes NumPy to not behave as expected. This can be fixed by installing scipy before NumPy and then installing apexpy.


pip is included with Python 2 from v2.7.9 and Python 3 from v3.4. If you don’t have pip, get it here.