greenflow - RAPIDS Financial Services Algorithms
greenflow - Graph Computation Toolkit
What is greenflow?
greenflow is a tool that helps you to organize the workflows.
- It define a TaskGraph file format
.gq.yamlthat describes the workflow. It can be edited easily by
- Dynamically compute the input-output ports compatibility, dataframe columns names and types, ports types to prevent connection errors.
- Nodes can have multiple output ports that can be used to generate different output types. E.g. some data loader Node provides both
dask_cudfoutput ports. The multiple GPUs distributed computation computation is automatically enabled by switching to the
- Provides the standard API to extend your computation Nodes.
- The composite node can encapsulate the TaskGraph into a single node for easy reuse. The composite node can be exported as a regular greenflow node without any coding.
- greenflow can be extended by writing a plugin with a set of nodes for a particular domain. Check
These examples can be used as-is or, as they are open source, can be extended to suit your environments.
Binary pip installation
To install the greenflow graph computation library, run:
pip install greenflow
greenflow at the root directory:
pip install .
greenflow node plugins can be registered in two ways:
- (Recommended)Write a external plugin using 'entry point' to register it. Check the
externaldirectory for details
- Register the plugin in
greenflowrcfile. Check the
System environmentfor details
There are a few system environment that the user can overwrite.
The custom module files are specified in the
GREENFLOW_CONFIG enviroment variable points to the location of this file. By default, it points to
In the example
greenflowrc, system environment variable
MODULEPATH is used to point to the paths of the module files.
To start the jupyterlab, please make sure
MODULEPATH is set properly.
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
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