Get Started

Installation

Bionic can be installed using pip:

pip install 'bionic[standard]'

The bionic[standard] package includes the core framework as well as the most commonly-used dependencies. There are several other subpackages offering different dependencies, documented below.

You will probably also want to install Graphviz, which Bionic uses to generate visualizations of its workflow graph. Unfortunately Graphviz is not written in Python and can’t be installed by pip. On Mac OS X, you can use Homebrew to install it:

brew install graphviz

If you want your data to be automatically cached to Google Cloud Storage, you’ll also need to have the Google Cloud SDK installed, have access to a GCS bucket, and install the bionic[gcp] subpackage.

Finally, installing LibYAML will improve performance for some workloads. LibYAML is also available via Homebrew:

brew install libyaml

Bionic supports Python 3.7 and above.

Extra Packages

The default bionic PyPI package installs only the minimal dependencies for building and running flows. However, many other dependency configurations are available. Most users will want the bionic[standard] package, which supports common integrations like Matplotlib, as well as graph visualization.

The full set of subpackages is as follows:

Subpackage

Installation Command

Enables

dask

pip install 'bionic[dask]'

the @dask decorator

dev

pip install 'bionic[dev]'

every feature; testing; building documentation

dill

pip install 'bionic[dill]'

the @dillable decorator

examples

pip install 'bionic[examples]'

the tutorial example code

full

pip install 'bionic[full]'

every non-development feature

gcp

pip install 'bionic[gcp]'

caching to GCS

geopandas

pip install 'bionic[geopandas]'

the @geodataframe decorator

image

pip install 'bionic[image]'

automatic de/serialization of PIL.Image objects

matplotlib

pip install 'bionic[matplotlib]'

the @pyplot decorator

parallel

pip install 'bionic[parallel]'

parallel execution

standard

pip install 'bionic[standard]'

graph visualization; Image handling; @pyplot

viz

pip install 'bionic[viz]'

graph visualization

Tutorials

These two worked examples illustrate the basic mechanics of Bionic.