polars-mem-engine 0.54.4

use polars_core::utils::accumulate_dataframes_vertical;
use pyo3::exceptions::PyStopIteration;
use pyo3::prelude::*;
use pyo3::types::{PyBytes, PyNone};
use pyo3::{IntoPyObjectExt, PyTypeInfo, intern};

use self::python_dsl::PythonScanSource;
use super::*;

pub(crate) struct PythonScanExec {
    pub(crate) options: PythonOptions,
    pub(crate) predicate: Option<Arc<dyn PhysicalExpr>>,
    pub(crate) predicate_serialized: Option<Vec<u8>>,
}

impl PythonScanExec {
    /// Get the output schema. E.g. the schema the plugins produce, not consume.
    fn get_schema(&self) -> &SchemaRef {
        self.options
            .output_schema
            .as_ref()
            .unwrap_or(&self.options.schema)
    }

    fn check_schema(&self, df: &DataFrame) -> PolarsResult<()> {
        if self.options.validate_schema {
            let output_schema = self.get_schema();
            polars_ensure!(df.schema() == output_schema, SchemaMismatch: "user provided schema: {:?} doesn't match the DataFrame schema: {:?}", output_schema, df.schema());
        }
        Ok(())
    }

    fn finish_df(
        &self,
        py: Python,
        df: Bound<'_, PyAny>,
        state: &mut ExecutionState,
    ) -> PolarsResult<DataFrame> {
        let df = python_df_to_rust(py, df)?;
        py.detach(|| {
            self.check_schema(&df)?;

            if let Some(pred) = &self.predicate {
                let mask = pred.evaluate(&df, state)?;
                df.filter(mask.bool()?)
            } else {
                Ok(df)
            }
        })
    }
}

impl Executor for PythonScanExec {
    fn execute(&mut self, state: &mut ExecutionState) -> PolarsResult<DataFrame> {
        state.should_stop()?;
        #[cfg(debug_assertions)]
        {
            if state.verbose() {
                eprintln!("run PythonScanExec")
            }
        }
        let with_columns = self.options.with_columns.take();
        let n_rows = self.options.n_rows.take();
        RAYON.block_on(|| {
            Python::attach(|py| {
                let python_scan_function = self.options.scan_fn.take().unwrap().0;
                let python_scan_function = python_scan_function.bind(py);

                let with_columns = with_columns
                    .as_ref()
                    .map(|cols| cols.iter().map(|s| s.as_str()).collect::<Vec<_>>());
                let mut could_serialize_predicate = true;

                let predicate = match &self.options.predicate {
                    PythonPredicate::PyArrow{predicate, has_residual} => {
                        if *has_residual {
                            // This will ensure we apply post-apply-predicate
                            could_serialize_predicate = false;
                        }

                        predicate.into_bound_py_any(py).unwrap()},
                    PythonPredicate::None => None::<()>.into_bound_py_any(py).unwrap(),
                    PythonPredicate::Polars(_) => {
                        assert!(self.predicate.is_some(), "should be set");

                        match &self.predicate_serialized {
                            None => {
                                could_serialize_predicate = false;
                                PyNone::get(py).to_owned().into_any()
                            },
                            Some(buf) => PyBytes::new(py, buf).into_any(),
                        }
                    },
                };

                match self.options.python_source {
                    PythonScanSource::Cuda => {
                        let args = (
                            with_columns,
                            predicate,
                            n_rows,
                            // If this boolean is true, callback should return
                            // a dataframe and list of timings [(start, end,
                            // name)]
                            state.has_node_timer(),
                        );
                        let result = python_scan_function.call1(args)?;
                        let df = if state.has_node_timer() {
                            let df = result.get_item(0);
                            let timing_info: Vec<(u64, u64, String)> = result.get_item(1)?.extract()?;
                            state.record_raw_timings(&timing_info);
                            df?
                        } else {
                            result
                        };
                        self.finish_df(py, df, state)
                    },
                    PythonScanSource::IOPlugin | PythonScanSource::Pyarrow => {
                        // If there are filters, take smaller chunks to ensure we can keep memory
                        // pressure low.
                        let batch_size = if self.predicate.is_some() {
                            Some(100_000usize)
                        } else {
                            None
                        };
                        let args = (with_columns, predicate, n_rows, batch_size);

                        let generator_init = python_scan_function.call1(args)?;
                        let generator = generator_init.get_item(0).map_err(
                            |_| polars_err!(ComputeError: "expected tuple got {}", generator_init),
                        )?;
                        let can_parse_predicate = generator_init.get_item(1).map_err(
                            |_| polars_err!(ComputeError: "expected tuple got {}", generator),
                        )?;
                        let can_parse_predicate = can_parse_predicate.extract::<bool>().map_err(
                            |_| polars_err!(ComputeError: "expected bool got {}", can_parse_predicate),
                        )? && could_serialize_predicate;

                        let mut chunks = vec![];
                        loop {
                            match generator.call_method0(intern!(py, "__next__")) {
                                Ok(out) => {
                                    let mut df = python_df_to_rust(py, out)?;
                                    if let (Some(pred), false) = (&self.predicate, can_parse_predicate)
                                    {
                                        py.detach(|| {
                                            let mask = pred.evaluate(&df, state)?;
                                            df = df.filter(mask.bool()?)?;
                                            PolarsResult::Ok(())
                                        })?
                                    }
                                    chunks.push(df)
                                },
                                Err(err) if err.matches(py, PyStopIteration::type_object(py))? => break,
                                Err(err) => {
                                    polars_bail!(ComputeError: "caught exception during execution of a Python source, exception: {}", err)
                                },
                            }
                        }
                        if chunks.is_empty() {
                            return Ok(DataFrame::empty_with_schema(self.get_schema().as_ref()));
                        }
                        let df = accumulate_dataframes_vertical(chunks)?;

                        self.check_schema(&df)?;
                        Ok(df)
                    },
                }
            })
        })
    }
}