.. _install: Installing ========== There are different ways to install Verde: .. tab-set:: .. tab-item:: pip Using the `pip `__ package manager: .. code:: bash python -m pip install verde .. tab-item:: conda/mamba Using the `conda package manager `__ (or ``mamba``) that comes with the Anaconda/Miniconda distribution: .. code:: bash conda install verde --channel conda-forge .. tab-item:: Development version You can use ``pip`` to install the latest **unreleased** version from GitHub (**not recommended** in most situations): .. code:: bash 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 :ref:`python-versions` if you require support for older versions. .. _dependencies: 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 :class:`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