remove PyDFField and related methods

DFField was removed upstream.

Ref: apache/datafusion#9595

Author: Michael-J-Ward

datafusion/__init__.py

@@ -37,7 +37,6 @@
 )
 
 from .common import (
-    DFField,
     DFSchema,
 )
 

datafusion/tests/test_imports.py

@@ -27,7 +27,6 @@
 )
 
 from datafusion.common import (
-    DFField,
     DFSchema,
 )
 
@@ -161,7 +160,7 @@ def test_class_module_is_datafusion():
         assert klass.__module__ == "datafusion.expr"
 
     # schema
-    for klass in [DFField, DFSchema]:
+    for klass in [DFSchema]:
         assert klass.__module__ == "datafusion.common"
 
 

src/common.rs

@@ -18,15 +18,13 @@
 use pyo3::prelude::*;
 
 pub mod data_type;
-pub mod df_field;
 pub mod df_schema;
 pub mod function;
 pub mod schema;
 
 /// Initializes the `common` module to match the pattern of `datafusion-common` https://docs.rs/datafusion-common/18.0.0/datafusion_common/index.html
 pub(crate) fn init_module(m: &PyModule) -> PyResult<()> {
     m.add_class::<df_schema::PyDFSchema>()?;
-    m.add_class::<df_field::PyDFField>()?;
     m.add_class::<data_type::PyDataType>()?;
     m.add_class::<data_type::DataTypeMap>()?;
     m.add_class::<data_type::PythonType>()?;

src/common/df_field.rs

@@ -21,23 +21,19 @@ use std::convert::{From, Into};
 use datafusion::arrow::datatypes::DataType;
 use datafusion::arrow::pyarrow::PyArrowType;
 use datafusion::scalar::ScalarValue;
-use datafusion_common::DFField;
 use datafusion_expr::{
     col,
     expr::{AggregateFunction, InList, InSubquery, ScalarFunction, Sort, WindowFunction},
-    lit,
-    utils::exprlist_to_fields,
-    Between, BinaryExpr, Case, Cast, Expr, GetFieldAccess, GetIndexedField, Like, LogicalPlan,
-    Operator, TryCast,
+    lit, Between, BinaryExpr, Case, Cast, Expr, GetFieldAccess, GetIndexedField, Like, Operator,
+    TryCast,
 };
 
 use crate::common::data_type::{DataTypeMap, RexType};
-use crate::errors::{py_datafusion_err, py_runtime_err, py_type_err, DataFusionError};
+use crate::errors::{py_datafusion_err, py_runtime_err, py_type_err};
 use crate::expr::aggregate_expr::PyAggregateFunction;
 use crate::expr::binary_expr::PyBinaryExpr;
 use crate::expr::column::PyColumn;
 use crate::expr::literal::PyLiteral;
-use crate::sql::logical::PyLogicalPlan;
 
 use self::alias::PyAlias;
 use self::bool_expr::{
@@ -557,41 +553,9 @@ impl PyExpr {
             }
         })
     }
-
-    pub fn column_name(&self, plan: PyLogicalPlan) -> PyResult<String> {
-        self._column_name(&plan.plan()).map_err(py_runtime_err)
-    }
 }
 
 impl PyExpr {
-    pub fn _column_name(&self, plan: &LogicalPlan) -> Result<String, DataFusionError> {
-        let field = Self::expr_to_field(&self.expr, plan)?;
-        Ok(field.qualified_column().flat_name())
-    }
-
-    /// Create a [DFField] representing an [Expr], given an input [LogicalPlan] to resolve against
-    pub fn expr_to_field(
-        expr: &Expr,
-        input_plan: &LogicalPlan,
-    ) -> Result<DFField, DataFusionError> {
-        match expr {
-            Expr::Sort(Sort { expr, .. }) => {
-                // DataFusion does not support create_name for sort expressions (since they never
-                // appear in projections) so we just delegate to the contained expression instead
-                Self::expr_to_field(expr, input_plan)
-            }
-            Expr::Wildcard { .. } => {
-                // Since * could be any of the valid column names just return the first one
-                Ok(input_plan.schema().field(0).clone())
-            }
-            _ => {
-                let fields =
-                    exprlist_to_fields(&[expr.clone()], input_plan).map_err(PyErr::from)?;
-                Ok(fields[0].clone())
-            }
-        }
-    }
-
     fn _types(expr: &Expr) -> PyResult<DataTypeMap> {
         match expr {
             Expr::BinaryExpr(BinaryExpr {