refactor: rename chain_dag to chain_let for semantic clarity

graphistry/compute/ComputeMixin.py

@@ -479,8 +479,8 @@ def chain(self, *args, **kwargs):
     # Preserve original docstring after deprecation notice
     chain.__doc__ = (chain.__doc__ or "") + "\n\n" + (chain_base.__doc__ or "")
 
-    # chain_dag removed from public API - use gfql() instead
-    # (chain_dag_base still available internally for gfql dispatch)
+    # chain_let removed from public API - use gfql() instead
+    # (chain_let_base still available internally for gfql dispatch)
 
     def gfql(self, *args, **kwargs):
         return gfql_base(self, *args, **kwargs)

graphistry/compute/ast.py

@@ -702,10 +702,10 @@ def from_json(cls, d: dict, validate: bool = True) -> 'ASTLet':
 
     def __call__(self, g: Plottable, prev_node_wavefront: Optional[DataFrameT], 
                  target_wave_front: Optional[DataFrameT], engine: Engine) -> Plottable:
-        # Let bindings don't use wavefronts - execute via chain_dag_impl
-        from graphistry.compute.chain_dag import chain_dag_impl
+        # Let bindings don't use wavefronts - execute via chain_let_impl
+        from graphistry.compute.chain_let import chain_let_impl
         from graphistry.Engine import EngineAbstract
-        return chain_dag_impl(g, self, EngineAbstract(engine.value))
+        return chain_let_impl(g, self, EngineAbstract(engine.value))
 
     def reverse(self) -> 'ASTLet':
         raise NotImplementedError("Let reversal not supported")
@@ -934,7 +934,7 @@ def __call__(self, g: Plottable, prev_node_wavefront: Optional[DataFrameT],
                  target_wave_front: Optional[DataFrameT], engine: Engine) -> Plottable:
         raise NotImplementedError(
             "ASTRef cannot be used directly in chain(). "
-            "It must be used within an ASTLet/chain_dag() context."
+            "It must be used within an ASTLet/chain_let() context."
         )
 
     def reverse(self) -> 'ASTRef':
@@ -1050,7 +1050,7 @@ def __call__(self, g: Plottable, prev_node_wavefront: Optional[DataFrameT],
         Raises:
             GFQLTypeError: If method not in safelist or parameters invalid
         """
-        # For chain_dag, we don't use wavefronts, just execute the call
+        # For chain_let, we don't use wavefronts, just execute the call
         from graphistry.compute.call_executor import execute_call
         return execute_call(g, self.function, self.params, engine)
 

graphistry/compute/chain_dag.py → graphistry/compute/chain_let.py

@@ -194,11 +194,7 @@ def execute_node(name: str, ast_obj: ASTObject, g: Plottable,
     """Execute a single node in the DAG
 
     Handles different AST object types:
-<<<<<<< HEAD
     - ASTLet: Recursive let execution
-=======
-    - ASTLet: Recursive DAG execution
->>>>>>> refactor: rename ASTQueryDAG to ASTLet throughout codebase
     - ASTRef: Reference resolution and chain execution
     - ASTNode: Node filtering operations
     - ASTEdge: Edge traversal operations
@@ -219,7 +215,7 @@ def execute_node(name: str, ast_obj: ASTObject, g: Plottable,
     # Handle different AST object types
     if isinstance(ast_obj, ASTLet):
         # Nested let execution
-        result = chain_dag_impl(g, ast_obj, EngineAbstract(engine.value))
+        result = chain_let_impl(g, ast_obj, EngineAbstract(engine.value))
     elif isinstance(ast_obj, ASTRef):
         # Resolve reference from context
         try:
@@ -240,7 +236,7 @@ def execute_node(name: str, ast_obj: ASTObject, g: Plottable,
             # Empty chain - just return the referenced result
             result = referenced_result
     elif isinstance(ast_obj, ASTNode):
-        # For chain_dag, we execute nodes in a simpler way than chain()
+        # For chain_let, we execute nodes in a simpler way than chain()
         # No wavefront propagation - just filter the graph's nodes
         node_obj = cast(ASTNode, ast_obj)  # Help mypy understand the type
         if node_obj.filter_dict or node_obj.query:
@@ -258,7 +254,7 @@ def execute_node(name: str, ast_obj: ASTObject, g: Plottable,
         if node_obj._name:
             result = result.nodes(result._nodes.assign(**{node_obj._name: True}))
     elif isinstance(ast_obj, ASTEdge):
-        # For chain_dag, execute edge operations using hop()
+        # For chain_let, execute edge operations using hop()
         # This is simpler than the full chain() wavefront approach
         result = g.hop(
             nodes=None,  # Start from all nodes
@@ -316,10 +312,10 @@ def execute_node(name: str, ast_obj: ASTObject, g: Plottable,
     return result
 
 
-def chain_dag_impl(g: Plottable, dag: ASTLet, 
+def chain_let_impl(g: Plottable, dag: ASTLet, 
                   engine: Union[EngineAbstract, str] = EngineAbstract.AUTO,
                   output: Optional[str] = None) -> Plottable:
-    """Internal implementation of chain_dag execution
+    """Internal implementation of chain_let execution
 
     Validates DAG, determines execution order, and executes nodes
     in topological order.
@@ -346,7 +342,7 @@ def chain_dag_impl(g: Plottable, dag: ASTLet,
 
     # Resolve engine
     engine_concrete = resolve_engine(engine, g)
-    logger.debug('chain_dag engine: %s => %s', engine, engine_concrete)
+    logger.debug('chain_let engine: %s => %s', engine, engine_concrete)
 
     # Materialize nodes if needed (following chain.py pattern)
     g = g.materialize_nodes(engine=EngineAbstract(engine_concrete.value))
@@ -392,7 +388,7 @@ def chain_dag_impl(g: Plottable, dag: ASTLet,
         return last_result
 
 
-def chain_dag(self: Plottable, dag: ASTLet,
+def chain_let(self: Plottable, dag: ASTLet,
              engine: Union[EngineAbstract, str] = EngineAbstract.AUTO,
              output: Optional[str] = None) -> Plottable:
     """
@@ -416,7 +412,7 @@ def chain_dag(self: Plottable, dag: ASTLet,
         dag = ASTLet({
             'people': n({'type': 'person'})
         })
-        result = g.chain_dag(dag)
+        result = g.chain_let(dag)
 
     **Example: Linear dependencies**
 
@@ -428,7 +424,7 @@ def chain_dag(self: Plottable, dag: ASTLet,
             'start': n({'type': 'person'}),
             'friends': ASTRef('start', [e(), n()])
         })
-        result = g.chain_dag(dag)
+        result = g.chain_let(dag)
 
     **Example: Diamond pattern**
 
@@ -441,9 +437,9 @@ def chain_dag(self: Plottable, dag: ASTLet,
             'branch2': ASTRef('transactions', [e()]), 
             'merged': g.union(ASTRef('branch1'), ASTRef('branch2'))
         })
-        result = g.chain_dag(dag)  # Returns last executed
+        result = g.chain_let(dag)  # Returns last executed
 
         # Or select specific output
-        people_result = g.chain_dag(dag, output='people')
+        people_result = g.chain_let(dag, output='people')
     """
-    return chain_dag_impl(self, dag, engine, output)
+    return chain_let_impl(self, dag, engine, output)

graphistry/compute/gfql_unified.py

@@ -6,7 +6,7 @@
 from graphistry.util import setup_logger
 from .ast import ASTObject, ASTLet
 from .chain import Chain, chain as chain_impl
-from .chain_dag import chain_dag as chain_dag_impl
+from .chain_let import chain_let as chain_let_impl
 
 logger = setup_logger(__name__)
 
@@ -74,7 +74,7 @@ def gfql(self: Plottable,
     # Dispatch based on type - check specific types before generic
     if isinstance(query, ASTLet):
         logger.debug('GFQL executing as DAG')
-        return chain_dag_impl(self, query, engine, output)
+        return chain_let_impl(self, query, engine, output)
     elif isinstance(query, Chain):
         logger.debug('GFQL executing as Chain')
         if output is not None:

graphistry/compute/validate/validate_schema.py

@@ -168,7 +168,7 @@ def _validate_ref_op(op: ASTRef, g: Plottable, collect_all: bool) -> List[GFQLSc
                 raise
 
     # Note: We don't validate that op.ref exists here since that's handled
-    # by the DAG dependency validation in chain_dag.py
+    # by the DAG dependency validation in chain_let.py
 
     return errors
 

graphistry/compute/validate_schema.py

@@ -172,7 +172,7 @@ def _validate_chainref_op(op: ASTRef, g: Plottable, collect_all: bool) -> List[G
                 raise
 
     # Note: We don't validate that op.ref exists here since that's handled
-    # by the DAG dependency validation in chain_dag.py
+    # by the DAG dependency validation in chain_let.py
 
     return errors
 

graphistry/tests/compute/README_INTEGRATION_TESTS.md

@@ -7,13 +7,13 @@ This directory contains both unit tests (always run) and integration tests (opt-
 ### GPU Tests
 ```bash
 # Enable CUDF/GPU tests
-TEST_CUDF=1 pytest test_chain_dag_gpu.py
+TEST_CUDF=1 pytest test_chain_let_gpu.py
 ```
 
 ### Remote Graph Integration Tests
 ```bash
 # Enable remote Graphistry server tests
-TEST_REMOTE_INTEGRATION=1 pytest test_chain_dag_remote_integration.py
+TEST_REMOTE_INTEGRATION=1 pytest test_chain_let_remote_integration.py
 
 # Additional configuration for remote tests:
 GRAPHISTRY_USERNAME=myuser         # Username for auth

graphistry/tests/compute/test_call_operations.py

@@ -7,7 +7,7 @@
 from graphistry.tests.test_compute import CGFull
 from graphistry.Engine import Engine, EngineAbstract
 from graphistry.compute.ast import ASTCall, ASTLet, n
-from graphistry.compute.chain_dag import chain_dag_impl
+from graphistry.compute.chain_let import chain_let_impl
 from graphistry.compute.gfql.call_safelist import validate_call_params
 from graphistry.compute.gfql.call_executor import execute_call
 from graphistry.compute.exceptions import ErrorCode, GFQLTypeError, GFQLSyntaxError
@@ -273,7 +273,7 @@ def test_call_in_dag(self, sample_graph):
             'with_degrees': ASTCall('get_degrees', {'col': 'degree'})
         })
 
-        result = chain_dag_impl(sample_graph, dag, EngineAbstract.PANDAS)
+        result = chain_let_impl(sample_graph, dag, EngineAbstract.PANDAS)
 
         # Should have degree column
         assert 'degree' in result._nodes.columns
@@ -282,15 +282,15 @@ def test_call_in_dag(self, sample_graph):
 
     def test_call_referencing_binding(self, sample_graph):
         """Test ASTCall that operates on whole graph (not in chain)."""
-        from graphistry.compute.ast import ASTChainRef
+        from graphistry.compute.ast import ASTRef
 
         # Call operations work on the whole graph, not as part of chains
         dag = ASTLet({
             'users': n({'type': 'user'}),
             'with_degrees': ASTCall('get_degrees', {'col': 'degree'})
         })
 
-        result = chain_dag_impl(sample_graph, dag, EngineAbstract.PANDAS)
+        result = chain_let_impl(sample_graph, dag, EngineAbstract.PANDAS)
 
         # Should have degree column on all nodes
         assert len(result._nodes) == 4  # All nodes
@@ -302,14 +302,14 @@ def test_multiple_calls(self, sample_graph):
         dag1 = ASTLet({
             'with_degrees': ASTCall('get_degrees', {'col': 'deg'})
         })
-        result1 = chain_dag_impl(sample_graph, dag1, EngineAbstract.PANDAS)
+        result1 = chain_let_impl(sample_graph, dag1, EngineAbstract.PANDAS)
         assert 'deg' in result1._nodes.columns
 
         # Then filter - use the graph that has degrees
         dag2 = ASTLet({
             'filtered': ASTCall('filter_nodes_by_dict', {'filter_dict': {'deg': 2}})
         })
-        result2 = chain_dag_impl(result1, dag2, EngineAbstract.PANDAS)
+        result2 = chain_let_impl(result1, dag2, EngineAbstract.PANDAS)
 
         # Should have nodes with degree 2
         assert len(result2._nodes) > 0
@@ -327,7 +327,7 @@ def test_call_execution_error(self, mock_getattr, sample_graph):
         })
 
         with pytest.raises(RuntimeError) as exc_info:
-            chain_dag_impl(sample_graph, dag, EngineAbstract.PANDAS)
+            chain_let_impl(sample_graph, dag, EngineAbstract.PANDAS)
         assert "Failed to execute node 'failing'" in str(exc_info.value)
 
 

graphistry/tests/compute/test_call_operations_gpu.py

@@ -7,7 +7,7 @@
 from graphistry.tests.test_compute import CGFull
 from graphistry.Engine import Engine
 from graphistry.compute.ast import ASTCall, ASTLet, n
-from graphistry.compute.chain_dag import chain_dag_impl
+from graphistry.compute.chain_let import chain_let_impl
 from graphistry.compute.gfql.call_executor import execute_call
 from graphistry.compute.validate.validate_schema import validate_chain_schema
 from graphistry.compute.exceptions import ErrorCode, GFQLTypeError
@@ -171,7 +171,7 @@ def test_layout_cugraph_call(self):
         assert result._nodes['y'].notna().all()
 
     @skip_gpu
-    def test_chain_dag_with_gpu_calls(self):
+    def test_chain_let_with_gpu_calls(self):
         """Test DAG execution with Call operations on GPU."""
         import cudf
 
@@ -199,7 +199,7 @@ def test_chain_dag_with_gpu_calls(self):
             'with_degrees': ASTCall('get_degrees', {'col': 'degree'})
         })
 
-        result = chain_dag_impl(g, dag, Engine.CUDF)
+        result = chain_let_impl(g, dag, Engine.CUDF)
 
         # Should have degrees column
         assert 'degree' in result._nodes.columns