[GitHub] [arrow-datafusion] kszucs commented on a change in pull request #856: Rework the python bindings [WIP]

[GitBox <gi...@apache.org>]

kszucs commented on a change in pull request #856:
URL: https://github.com/apache/arrow-datafusion/pull/856#discussion_r686931737



##########
File path: python/src/pyarrow.rs
##########
@@ -0,0 +1,205 @@
+// 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 std::convert::TryFrom;
+use std::sync::Arc;
+
+use libc::uintptr_t;
+use pyo3::exceptions::PyNotImplementedError;
+use pyo3::prelude::*;
+use pyo3::types::PyList;
+
+use datafusion::arrow::array::{make_array_from_raw, ArrayRef};
+use datafusion::arrow::datatypes::{DataType, Field, Schema};
+use datafusion::arrow::ffi;
+use datafusion::arrow::ffi::FFI_ArrowSchema;
+use datafusion::arrow::record_batch::RecordBatch;
+use datafusion::scalar::ScalarValue;
+
+use crate::errors::DataFusionError;
+
+pub trait PyArrowConvert: Sized {
+    fn from_pyarrow(value: &PyAny) -> PyResult<Self>;
+    fn to_pyarrow(&self, py: Python) -> PyResult<PyObject>;
+}
+
+impl PyArrowConvert for DataType {

Review comment:
       I'm going to try adding this module to `arrow-rs` as an optional one, so we can implement the `PyO3` conversion traits, like `FromPyObject` directly for the arrow types. 
   This will further reduce the required conversion boilerplate in the python bindinds. 
   
   For example we should be able to write
   ```rust
   fn create_dataframe(
           &mut self,
           partitions: Vec<Vec<RecordBatch>>,
       ) -> PyResult<PyDataFrame> {
           // partitions are going to be converted by PyO3 automatically
   ```
   
   instead of
   
   ```rust
   fn create_dataframe(
           &mut self,
           partitions: Vec<Vec<&PyAny>>,
       ) -> PyResult<PyDataFrame> {
           let partitions: Vec<Vec<RecordBatch>> = partitions
               .into_iter()
               .map(|batches| {
                   batches
                       .into_iter()
                       .map(RecordBatch::from_pyarrow)
                       .collect::<PyResult<_>>()
               })
               .collect::<PyResult<_>>()?;
   ```




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