You can install dask with conda
, with pip
, or by installing from source.
To install the latest version of Dask from the conda-forge repository using conda:
conda install dask -c conda-forge
This installs dask and all common dependencies, including Pandas and NumPy.
To install Dask with pip
there are a few options, depending on which
dependencies you would like to keep up to date:
pip install dask[complete]
: Install everythingpip install dask[array]
: Install dask and numpypip install dask[bag]
: Install dask and cloudpicklepip install dask[dataframe]
: Install dask, numpy, and pandaspip install dask
: Install only dask, which depends only on the standard library. This is appropriate if you only want the task schedulers.
We do this so that users of the lightweight core dask scheduler aren't required to download the more exotic dependencies of the collections (numpy, pandas, etc..)
To install dask from source, clone the repository from github:
git clone https://github.com/dask/dask.git cd dask python setup.py install
or use pip
locally if you want to install all dependencies as well:
pip install -e .[complete]
You can view the list of all dependencies within the extras_require
field
of setup.py
.
Test dask with py.test
:
cd dask py.test dask
Although please aware that installing dask naively may not install all
requirements by default. Please read the pip
section above that discusses
requirements. You may choose to install the dask[complete]
which includes
all dependencies for all collections. Alternatively you may choose to test
only certain submodules depending on the libraries within your environment.
For example to test only dask core and dask array we would run tests as
follows:
py.test dask/tests dask/array/tests