You can install dask with
pip, or by installing from source.
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.
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 everything
pip install dask[array]: Install dask and numpy
pip install dask[bag]: Install dask and cloudpickle
pip install dask[dataframe]: Install dask, numpy, and pandas
pip 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
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
Test dask with
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
py.test dask/tests dask/array/tests