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use std::borrow::Cow;
use std::fmt::{Display, Formatter};
use std::sync::Arc;
use polars_core::prelude::*;
#[cfg(feature = "serde")]
use serde::{Deserialize, Serialize};
use crate::prelude::*;
#[derive(Clone, Debug)]
#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
pub enum FunctionNode {
#[cfg_attr(feature = "serde", serde(skip))]
Opaque {
function: Arc<dyn DataFrameUdf>,
schema: Option<Arc<dyn UdfSchema>>,
predicate_pd: bool,
projection_pd: bool,
#[cfg_attr(feature = "serde", serde(skip))]
fmt_str: &'static str,
},
#[cfg_attr(feature = "serde", serde(skip))]
Pipeline {
function: Arc<dyn DataFrameUdfMut>,
schema: SchemaRef,
},
Unnest {
columns: Arc<Vec<Arc<str>>>,
},
FastProjection {
columns: Arc<Vec<Arc<str>>>,
},
DropNulls {
subset: Arc<Vec<String>>,
},
Rechunk,
}
impl PartialEq for FunctionNode {
fn eq(&self, other: &Self) -> bool {
use FunctionNode::*;
match (self, other) {
(FastProjection { columns: l }, FastProjection { columns: r }) => l == r,
(DropNulls { subset: l }, DropNulls { subset: r }) => l == r,
(Rechunk, Rechunk) => true,
_ => false,
}
}
}
impl FunctionNode {
pub(crate) fn schema<'a>(
&self,
input_schema: &'a SchemaRef,
) -> PolarsResult<Cow<'a, SchemaRef>> {
use FunctionNode::*;
match self {
Opaque { schema, .. } => match schema {
None => Ok(Cow::Borrowed(input_schema)),
Some(schema_fn) => {
let output_schema = schema_fn.get_schema(input_schema)?;
Ok(Cow::Owned(output_schema))
}
},
Pipeline { schema, .. } => Ok(Cow::Owned(schema.clone())),
FastProjection { columns } => {
let schema = columns
.iter()
.map(|name| {
let name = name.as_ref();
input_schema
.get_field(name)
.ok_or_else(|| PolarsError::NotFound(name.to_string().into()))
})
.collect::<PolarsResult<Schema>>()?;
Ok(Cow::Owned(Arc::new(schema)))
}
DropNulls { .. } => Ok(Cow::Borrowed(input_schema)),
Rechunk => Ok(Cow::Borrowed(input_schema)),
Unnest { columns: _columns } => {
#[cfg(feature = "dtype-struct")]
{
let mut new_schema = Schema::with_capacity(input_schema.len() * 2);
for (name, dtype) in input_schema.iter() {
if _columns.iter().any(|item| item.as_ref() == name.as_str()) {
if let DataType::Struct(flds) = dtype {
for fld in flds {
new_schema
.with_column(fld.name().clone(), fld.data_type().clone())
}
} else {
return Err(PolarsError::ComputeError(
format!("expected struct dtype, got: '{:?}'", dtype).into(),
));
}
} else {
new_schema.with_column(name.clone(), dtype.clone())
}
}
Ok(Cow::Owned(Arc::new(new_schema)))
}
#[cfg(not(feature = "dtype-struct"))]
{
panic!("activate feature 'dtype-struct'")
}
}
}
}
pub(crate) fn allow_predicate_pd(&self) -> bool {
use FunctionNode::*;
match self {
Opaque { predicate_pd, .. } => *predicate_pd,
FastProjection { .. } | DropNulls { .. } | Rechunk | Unnest { .. } => true,
Pipeline { .. } => unimplemented!(),
}
}
pub(crate) fn allow_projection_pd(&self) -> bool {
use FunctionNode::*;
match self {
Opaque { projection_pd, .. } => *projection_pd,
FastProjection { .. } | DropNulls { .. } | Rechunk | Unnest { .. } => true,
Pipeline { .. } => unimplemented!(),
}
}
pub(crate) fn additional_projection_pd_columns(&self) -> &[Arc<str>] {
use FunctionNode::*;
match self {
Unnest { columns } => columns.as_slice(),
_ => &[],
}
}
pub fn evaluate(&mut self, mut df: DataFrame) -> PolarsResult<DataFrame> {
use FunctionNode::*;
match self {
Opaque { function, .. } => function.call_udf(df),
FastProjection { columns } => df.select(columns.as_slice()),
DropNulls { subset } => df.drop_nulls(Some(subset.as_slice())),
Rechunk => {
df.as_single_chunk_par();
Ok(df)
}
Unnest { columns: _columns } => {
#[cfg(feature = "dtype-struct")]
{
df.unnest(_columns.as_slice())
}
#[cfg(not(feature = "dtype-struct"))]
{
panic!("activate feature 'dtype-struct'")
}
}
Pipeline { function, .. } => Arc::get_mut(function).unwrap().call_udf(df),
}
}
}
impl Display for FunctionNode {
fn fmt(&self, f: &mut Formatter<'_>) -> std::fmt::Result {
use FunctionNode::*;
match self {
Opaque { fmt_str, .. } => write!(f, "{}", fmt_str),
FastProjection { columns } => {
write!(f, "FAST_PROJECT: ")?;
let columns = columns.as_slice();
fmt_column_delimited(f, columns, "[", "]")
}
DropNulls { subset } => {
write!(f, "DROP_NULLS by: ")?;
let subset = subset.as_slice();
fmt_column_delimited(f, subset, "[", "]")
}
Rechunk => write!(f, "RECHUNK"),
Unnest { columns } => {
write!(f, "UNNEST by:")?;
let columns = columns.as_slice();
fmt_column_delimited(f, columns, "[", "]")
}
Pipeline { .. } => write!(f, "PIPELINE"),
}
}
}