class hamilton.base.SimplePythonDataFrameGraphAdapter

This is the original Hamilton graph adapter. It uses plain python and builds a dataframe result.

This executes the Hamilton dataflow locally on a machine in a single threaded, single process fashion. It assumes a pandas dataframe as a result.

Use this when you want to execute on a single machine, without parallelization, and you want a pandas dataframe as output.

static check_input_type(node_type: Type, input_value: Any) bool

Used to check whether the user inputs match what the execution strategy & functions can handle.

Static purely for legacy reasons.

  • node_type – The type of the node.

  • input_value – An actual value that we want to inspect matches our expectation.


True if the input is valid, False otherwise.

static check_node_type_equivalence(node_type: Type, input_type: Type) bool

Used to check whether two types are equivalent.

Static, purely for legacy reasons.

This is used when the function graph is being created and we’re statically type checking the annotations for compatibility.

  • node_type – The type of the node.

  • input_type – The type of the input that would flow into the node.


True if the types are equivalent, False otherwise.

execute_node(node: Node, kwargs: Dict[str, Any]) Any

Given a node that represents a hamilton function, execute it. Note, in some adapters this might just return some type of “future”.

  • node – the Hamilton Node

  • kwargs – the kwargs required to exercise the node function.


the result of exercising the node.