Anaconda Enterprise: Documentation

# Creating Dask arrays from NumPy arrays

We can create Dask arrays from any object that implements NumPy slicing, like a `numpy.ndarray` or on-disk formats like h5py or netCDF Dataset objects. This is particularly useful with on disk arrays that don’t fit in memory but, for simplicity’s sake, we show how this works on a NumPy array.

The following example uses `da.from_array` to create a Dask array from a NumPy array, which isn’t particularly valuable (the NumPy array already works in memory just fine) but is easy to play with.

    >>> import numpy as np
    >>> import dask.array as da
    >>> x = np.arange(1000)
    >>> y = da.from_array(x, chunks=(100))
    >>> y.mean().compute()
    499.5