SimplePythonDataFrameGraphAdapter

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.

Parameters:

• node_type – The type of the node.

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

Returns:

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

Used to check whether two types are equivalent.

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

Parameters:

• node_type – The type of the node.

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

Returns:

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”.

Parameters:

• node – the Hamilton Node

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

Returns:

the result of exercising the node.