pydantic_graph.beta.node

Core node types for graph construction and execution.

This module defines the fundamental node types used to build execution graphs, including start/end nodes and fork nodes for parallel execution.

StateT module-attribute

StateT = TypeVar('StateT', infer_variance=True) 

Type variable for graph state.

OutputT module-attribute

OutputT = TypeVar('OutputT', infer_variance=True) 

Type variable for node output data.

InputT module-attribute

InputT = TypeVar('InputT', infer_variance=True) 

Type variable for node input data.

StartNode

Bases: Generic[OutputT]

Entry point node for graph execution.

The StartNode represents the beginning of a graph execution flow.

Source code in pydantic_graph/pydantic_graph/beta/node.py

class StartNode(Generic[OutputT]):  """Entry point node for graph execution.  The StartNode represents the beginning of a graph execution flow.  """ id = NodeID('__start__')  """Fixed identifier for the start node.""" 

id class-attribute instance-attribute

id = NodeID('__start__') 

Fixed identifier for the start node.

EndNode

Bases: Generic[InputT]

Terminal node representing the completion of graph execution.

The EndNode marks the successful completion of a graph execution flow and can collect the final output data.

Source code in pydantic_graph/pydantic_graph/beta/node.py

class EndNode(Generic[InputT]):  """Terminal node representing the completion of graph execution.  The EndNode marks the successful completion of a graph execution flow  and can collect the final output data.  """ id = NodeID('__end__')  """Fixed identifier for the end node.""" def _force_variance(self, inputs: InputT) -> None: # pragma: no cover  """Force type variance for proper generic typing.  This method exists solely for type checking purposes and should never be called.  Args:  inputs: Input data of type InputT.  Raises:  RuntimeError: Always, as this method should never be executed.  """ raise RuntimeError('This method should never be called, it is just defined for typing purposes.') 

id class-attribute instance-attribute

id = NodeID('__end__') 

Fixed identifier for the end node.

Fork dataclass

Bases: Generic[InputT, OutputT]

Fork node that creates parallel execution branches.

A Fork node splits the execution flow into multiple parallel branches, enabling concurrent execution of downstream nodes. It can either map a sequence across multiple branches or duplicate data to each branch.

Source code in pydantic_graph/pydantic_graph/beta/node.py

@dataclass class Fork(Generic[InputT, OutputT]):  """Fork node that creates parallel execution branches.  A Fork node splits the execution flow into multiple parallel branches,  enabling concurrent execution of downstream nodes. It can either map  a sequence across multiple branches or duplicate data to each branch.  """ id: ForkID  """Unique identifier for this fork node.""" is_map: bool  """Determines fork behavior.  If True, InputT must be Sequence[OutputT] and each element is sent to a separate branch.  If False, InputT must be OutputT and the same data is sent to all branches.  """ downstream_join_id: JoinID | None  """Optional identifier of a downstream join node that should be jumped to if mapping an empty iterable.""" def _force_variance(self, inputs: InputT) -> OutputT: # pragma: no cover  """Force type variance for proper generic typing.  This method exists solely for type checking purposes and should never be called.  Args:  inputs: Input data to be forked.  Returns:  Output data type (never actually returned).  Raises:  RuntimeError: Always, as this method should never be executed.  """ raise RuntimeError('This method should never be called, it is just defined for typing purposes.') 

id instance-attribute

id: ForkID 

Unique identifier for this fork node.

is_map instance-attribute

is_map: bool 

Determines fork behavior.

If True, InputT must be Sequence[OutputT] and each element is sent to a separate branch. If False, InputT must be OutputT and the same data is sent to all branches.

downstream_join_id instance-attribute

downstream_join_id: JoinID | None 

Optional identifier of a downstream join node that should be jumped to if mapping an empty iterable.