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 3.6 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 |
---|---|---|
dev |
|
every feature; testing; building documentation |
dask |
|
the |
dill |
|
the |
examples |
|
the tutorial example code |
full |
|
every non-development feature |
gcp |
|
caching to GCS |
image |
|
automatic de/serialization of
|
matplotlib |
|
the |
standard |
|
graph visualization; |
viz |
|
graph visualization |
Tutorials¶
These two worked examples illustrate the basic mechanics of Bionic.