Installing

There are different ways to install Verde:

pip

Using the pip package manager:

python -m pip install verde

conda/mamba

Using the conda package manager (or mamba) that comes with the Anaconda/Miniconda distribution:

conda install verde --channel conda-forge

Development version

You can use pip to install the latest unreleased version from GitHub (not recommended in most situations):

python -m pip install --upgrade git+https://github.com/fatiando/verde

Note

The commands above should be executed in a terminal. On Windows, use the cmd.exe or the “Anaconda Prompt” app if you’re using Anaconda.

Which Python?

You’ll need Python >= 3.7. See Supported Python versions if you require support for older versions.

Dependencies

The required dependencies should be installed automatically when you install Verde using conda or pip.

Required:

• numpy

• scipy

• pandas

• xarray

• scikit-learn

• pooch

• dask

The following are optional dependencies that can make some parts of the code more efficient if they are installed:

• numba: replaces numpy calculations of predictions and Jacobian matrices in splines with faster and more memory efficient multi-threaded versions.

• pykdtree: replaces scipy.spatial.cKDTree for better performance in near neighbor calculations used in blocked operations, distance masking, etc.

Our examples use other packages as well which are not used within Verde itself. If you wish to run the examples in the documentation, you will also have to install:

• matplotlib

• pygmt for plotting maps

• cartopy for plotting maps

• pyproj for cartographic projections