use std::convert::{From, TryFrom};
use std::sync::Arc;
use pyo3::ffi::Py_uintptr_t;
use pyo3::import_exception;
use pyo3::prelude::*;
use pyo3::types::PyList;
use crate::array::{make_array, Array, ArrayData, ArrayRef};
use crate::datatypes::{DataType, Field, Schema};
use crate::error::ArrowError;
use crate::ffi;
use crate::ffi::FFI_ArrowSchema;
use crate::record_batch::RecordBatch;
import_exception!(pyarrow, ArrowException);
pub type PyArrowException = ArrowException;
impl From<ArrowError> for PyErr {
fn from(err: ArrowError) -> PyErr {
PyArrowException::new_err(err.to_string())
}
}
pub trait PyArrowConvert: Sized {
fn from_pyarrow(value: &PyAny) -> PyResult<Self>;
fn to_pyarrow(&self, py: Python) -> PyResult<PyObject>;
}
impl PyArrowConvert for DataType {
fn from_pyarrow(value: &PyAny) -> PyResult<Self> {
let c_schema = FFI_ArrowSchema::empty();
let c_schema_ptr = &c_schema as *const FFI_ArrowSchema;
value.call_method1("_export_to_c", (c_schema_ptr as Py_uintptr_t,))?;
let dtype = DataType::try_from(&c_schema)?;
Ok(dtype)
}
fn to_pyarrow(&self, py: Python) -> PyResult<PyObject> {
let c_schema = FFI_ArrowSchema::try_from(self)?;
let c_schema_ptr = &c_schema as *const FFI_ArrowSchema;
let module = py.import("pyarrow")?;
let class = module.getattr("DataType")?;
let dtype =
class.call_method1("_import_from_c", (c_schema_ptr as Py_uintptr_t,))?;
Ok(dtype.into())
}
}
impl PyArrowConvert for Field {
fn from_pyarrow(value: &PyAny) -> PyResult<Self> {
let c_schema = FFI_ArrowSchema::empty();
let c_schema_ptr = &c_schema as *const FFI_ArrowSchema;
value.call_method1("_export_to_c", (c_schema_ptr as Py_uintptr_t,))?;
let field = Field::try_from(&c_schema)?;
Ok(field)
}
fn to_pyarrow(&self, py: Python) -> PyResult<PyObject> {
let c_schema = FFI_ArrowSchema::try_from(self)?;
let c_schema_ptr = &c_schema as *const FFI_ArrowSchema;
let module = py.import("pyarrow")?;
let class = module.getattr("Field")?;
let dtype =
class.call_method1("_import_from_c", (c_schema_ptr as Py_uintptr_t,))?;
Ok(dtype.into())
}
}
impl PyArrowConvert for Schema {
fn from_pyarrow(value: &PyAny) -> PyResult<Self> {
let c_schema = FFI_ArrowSchema::empty();
let c_schema_ptr = &c_schema as *const FFI_ArrowSchema;
value.call_method1("_export_to_c", (c_schema_ptr as Py_uintptr_t,))?;
let schema = Schema::try_from(&c_schema)?;
Ok(schema)
}
fn to_pyarrow(&self, py: Python) -> PyResult<PyObject> {
let c_schema = FFI_ArrowSchema::try_from(self)?;
let c_schema_ptr = &c_schema as *const FFI_ArrowSchema;
let module = py.import("pyarrow")?;
let class = module.getattr("Schema")?;
let schema =
class.call_method1("_import_from_c", (c_schema_ptr as Py_uintptr_t,))?;
Ok(schema.into())
}
}
impl PyArrowConvert for ArrayData {
fn from_pyarrow(value: &PyAny) -> PyResult<Self> {
let (array_pointer, schema_pointer) =
ffi::ArrowArray::into_raw(unsafe { ffi::ArrowArray::empty() });
value.call_method1(
"_export_to_c",
(
array_pointer as Py_uintptr_t,
schema_pointer as Py_uintptr_t,
),
)?;
let ffi_array =
unsafe { ffi::ArrowArray::try_from_raw(array_pointer, schema_pointer)? };
let data = ArrayData::try_from(ffi_array)?;
Ok(data)
}
fn to_pyarrow(&self, py: Python) -> PyResult<PyObject> {
let array = ffi::ArrowArray::try_from(self.clone())?;
let (array_pointer, schema_pointer) = ffi::ArrowArray::into_raw(array);
let module = py.import("pyarrow")?;
let class = module.getattr("Array")?;
let array = class.call_method1(
"_import_from_c",
(
array_pointer as Py_uintptr_t,
schema_pointer as Py_uintptr_t,
),
)?;
Ok(array.to_object(py))
}
}
impl PyArrowConvert for ArrayRef {
fn from_pyarrow(value: &PyAny) -> PyResult<Self> {
Ok(make_array(ArrayData::from_pyarrow(value)?))
}
fn to_pyarrow(&self, py: Python) -> PyResult<PyObject> {
self.data().to_pyarrow(py)
}
}
impl<T> PyArrowConvert for T
where
T: Array + From<ArrayData>,
{
fn from_pyarrow(value: &PyAny) -> PyResult<Self> {
Ok(ArrayData::from_pyarrow(value)?.into())
}
fn to_pyarrow(&self, py: Python) -> PyResult<PyObject> {
self.data().to_pyarrow(py)
}
}
impl PyArrowConvert for RecordBatch {
fn from_pyarrow(value: &PyAny) -> PyResult<Self> {
let schema = value.getattr("schema")?;
let schema = Arc::new(Schema::from_pyarrow(schema)?);
let arrays = value.getattr("columns")?.downcast::<PyList>()?;
let arrays = arrays
.iter()
.map(ArrayRef::from_pyarrow)
.collect::<PyResult<_>>()?;
let batch = RecordBatch::try_new(schema, arrays)?;
Ok(batch)
}
fn to_pyarrow(&self, py: Python) -> PyResult<PyObject> {
let mut py_arrays = vec![];
let mut py_names = vec![];
let schema = self.schema();
let fields = schema.fields().iter();
let columns = self.columns().iter();
for (array, field) in columns.zip(fields) {
py_arrays.push(array.to_pyarrow(py)?);
py_names.push(field.name());
}
let module = py.import("pyarrow")?;
let class = module.getattr("RecordBatch")?;
let record = class.call_method1("from_arrays", (py_arrays, py_names))?;
Ok(PyObject::from(record))
}
}
macro_rules! add_conversion {
($typ:ty) => {
impl<'source> FromPyObject<'source> for $typ {
fn extract(value: &'source PyAny) -> PyResult<Self> {
Self::from_pyarrow(value)
}
}
impl<'a> IntoPy<PyObject> for $typ {
fn into_py(self, py: Python) -> PyObject {
self.to_pyarrow(py).unwrap()
}
}
};
}
add_conversion!(DataType);
add_conversion!(Field);
add_conversion!(Schema);
add_conversion!(ArrayData);
add_conversion!(RecordBatch);