Welcome to GraphEval’s documentation!

GraphEval is a project which aims to simplify the task of evaluating data. It is especially useful if similar tasks should be performed with only slight variations.

This works in three simple steps:

  • First, splitting the whole pipeline into a set of atomic steps, which are called nodes (for example “Do a linear regression”).

  • Compile the nodes to a graph, essentially plugging their in- and outputs together.

  • Request the result you want from the respective node.

The graph takes care of solving the dependencies (i.e. feeding every node with the required data) and eventually loading from and saving to cache. On top of that, results can also be visualized using the matplotlib wrapper proplot by giving every node the knowledge of how to add its results to a figure.

Nodes are inherited from grapheval.node.EvalNode. See there for a quick start.


Indices and tables