You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: ffi.rs
    path of file: ./repos/Daft/src/daft-table/src
    
    the code of the file until where you have to start completion: use pyo3::exceptions::PyValueError;

use pyo3::prelude::*;
use pyo3::types::PyList;
use pyo3::{PyAny, PyObject, PyResult, Python};

use crate::Table;
use common_error::DaftResult;
use daft_core::{
    schema::SchemaRef,
    series::Series,
    utils::arrow::{cast_array_for_daft_if_needed, cast_array_from_daft_if_needed},
};

pub fn record_batches_to_table(
    py: Python,
    batches: &[&PyAny],
    schema: SchemaRef,
) -> PyResult<Table> {
    if batches.is_empty() {
        return Ok(Table::empty(Some(schema))?);
    }

    let names = schema.names();
    let num_batches = batches.len();
    // First extract all the ar
    
pub fn table_to_record_batch(table: &Table, py: Python, pyarrow: &PyModule) -> PyResult<PyObject> {
    let mut arrays = Vec::with_capacity(table.num_columns());
    let mut names: Vec<String> = Vec::with_capacity(table.num_columns());

    for i in 0..table.num_columns() {
        let s = table.get_column_by_index(i)?;
        let arrow_array = s.to_arrow();
        let arrow_array = cast_array_from_daft_if_needed(arrow_array.to_boxed());
        let py_array = daft_core::ffi::to_py_array(arrow_array, py, pyarrow)?;
        arrays.push(py_array);
        names.push(s.name().to_string());
    }

    let record = pyarrow
        .getattr(pyo3::intern!(py, "RecordBatch"))?
        .call_method1(pyo3::intern!(py, "from_arrays"), (arrays, names.to_vec()))?;

    Ok(record.to_object(py))
}