Install Dask¶
You can install dask with conda
, with pip
, or by installing from source.
Anaconda¶
Conda¶
Dask is installed by default in Anaconda:
You can update Dask using the conda command:
conda install dask
This installs Dask and all common dependencies, including Pandas and NumPy.
Dask packages are maintained both on the default channel and on conda-forge.
Optionally, you can obtain a minimal dask installation using the following command:
conda install dask-core
This will install a minimal set of dependencies required to run dask, similar to (but not exactly the same as) pip install dask
below.
Pip¶
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..)
Install from Source¶
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¶
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