apache · andygrove · Feb 19, 2023 · Feb 19, 2023 · Feb 19, 2023
diff --git a/datafusion/tests/test_imports.py b/datafusion/tests/test_imports.py
@@ -35,6 +35,7 @@
     Expr,
     Projection,
     TableScan,
+    Aggregate,
     Sort,
 )
 
@@ -56,7 +57,7 @@ def test_class_module_is_datafusion():
     ]:
         assert klass.__module__ == "datafusion"
 
-    for klass in [Expr, Projection, TableScan, Sort]:
+    for klass in [Expr, Projection, TableScan, Aggregate, Sort]:
         assert klass.__module__ == "datafusion.expr"
 
     for klass in [DFField, DFSchema]:

diff --git a/src/expr.rs b/src/expr.rs
@@ -24,6 +24,7 @@ use datafusion_expr::{col, lit, Cast, Expr, GetIndexedField};
 
 use datafusion::scalar::ScalarValue;
 
+pub mod aggregate;
 pub mod logical_node;
 pub mod projection;
 pub mod sort;
@@ -144,6 +145,7 @@ pub(crate) fn init_module(m: &PyModule) -> PyResult<()> {
     m.add_class::<PyExpr>()?;
     m.add_class::<table_scan::PyTableScan>()?;
     m.add_class::<projection::PyProjection>()?;
+    m.add_class::<aggregate::PyAggregate>()?;
     m.add_class::<sort::PySort>()?;
     Ok(())
 }
diff --git a/src/expr/aggregate.rs b/src/expr/aggregate.rs
@@ -0,0 +1,106 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements.  See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership.  The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License.  You may obtain a copy of the License at
+//
+//   http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied.  See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+use datafusion_common::DataFusionError;
+use datafusion_expr::logical_plan::Aggregate;
+use pyo3::prelude::*;
+use std::fmt::{self, Display, Formatter};
+
+use crate::common::df_schema::PyDFSchema;
+use crate::expr::logical_node::LogicalNode;
+use crate::expr::PyExpr;
+use crate::sql::logical::PyLogicalPlan;
+
+#[pyclass(name = "Aggregate", module = "datafusion.expr", subclass)]
+#[derive(Clone)]
+pub struct PyAggregate {
+    aggregate: Aggregate,
+}
+
+impl From<Aggregate> for PyAggregate {
+    fn from(aggregate: Aggregate) -> PyAggregate {
+        PyAggregate { aggregate }
+    }
+}
+
+impl TryFrom<PyAggregate> for Aggregate {
+    type Error = DataFusionError;
+
+    fn try_from(agg: PyAggregate) -> Result<Self, Self::Error> {
+        Ok(agg.aggregate)
+    }
+}
+
+impl Display for PyAggregate {
+    fn fmt(&self, f: &mut Formatter) -> fmt::Result {
+        write!(
+            f,
+            "Aggregate
+            \nGroupBy(s): {:?}
+            \nAggregates(s): {:?}
+            \nInput: {:?}
+            \nProjected Schema: {:?}",
+            &self.aggregate.group_expr,
+            &self.aggregate.aggr_expr,
+            self.aggregate.input,
+            self.aggregate.schema
+        )
+    }
+}
+
+#[pymethods]
+impl PyAggregate {
+    /// Retrieves the grouping expressions for this `Aggregate`
+    fn group_by_exprs(&self) -> PyResult<Vec<PyExpr>> {
+        Ok(self
+            .aggregate
+            .group_expr
+            .iter()
+            .map(|e| PyExpr::from(e.clone()))
+            .collect())
+    }
+
+    /// Retrieves the aggregate expressions for this `Aggregate`
+    fn aggregate_exprs(&self) -> PyResult<Vec<PyExpr>> {
+        Ok(self
+            .aggregate
+            .aggr_expr
+            .iter()
+            .map(|e| PyExpr::from(e.clone()))
+            .collect())
+    }
+
+    // Retrieves the input `LogicalPlan` to this `Aggregate` node
+    fn input(&self) -> PyLogicalPlan {
+        PyLogicalPlan::from((*self.aggregate.input).clone())
+    }
+
+    // Resulting Schema for this `Aggregate` node instance
+    fn schema(&self) -> PyDFSchema {
+        (*self.aggregate.schema).clone().into()
+    }
+
+    fn __repr__(&self) -> PyResult<String> {
+        Ok(format!("Aggregate({})", self))
+    }
+}
+
+impl LogicalNode for PyAggregate {
+    fn input(&self) -> Vec<PyLogicalPlan> {
+        vec![PyLogicalPlan::from((*self.aggregate.input).clone())]
+    }
+}