datafusion-python 54.0.0

// 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.

// Re-export Apache Arrow DataFusion dependencies
pub use datafusion::{
    self, common as datafusion_common, logical_expr as datafusion_expr, optimizer,
    sql as datafusion_sql,
};
#[cfg(feature = "substrait")]
pub use datafusion_substrait;
#[cfg(feature = "mimalloc")]
use mimalloc::MiMalloc;
use pyo3::prelude::*;

pub mod analyzer;
pub mod catalog;
pub mod codec;
pub mod common;

pub mod context;
pub mod dataframe;
mod dataset;
mod dataset_exec;
pub mod errors;
pub mod expr;
mod functions;
pub mod metrics;
mod options;
pub mod physical_plan;
mod pyarrow_filter_expression;
pub mod pyarrow_util;
mod record_batch;
mod spark_functions;
pub mod sql;
pub mod store;
pub mod table;
pub mod unparser;

mod array;
#[cfg(feature = "substrait")]
pub mod substrait;
mod udaf;
mod udf;
pub mod udtf;
mod udwf;

// Re-export helpers previously consumed by downstream Rust crates.
// Modules stay private to keep the public Rust API surface small.
pub use udaf::to_rust_accumulator;
pub use udwf::{MultiColumnWindowUDF, PythonFunctionWindowUDF, to_rust_partition_evaluator};

#[cfg(feature = "mimalloc")]
#[global_allocator]
static GLOBAL: MiMalloc = MiMalloc;

/// Low-level DataFusion internal package.
///
/// The higher-level public API is defined in pure python files under the
/// datafusion directory.
#[pymodule]
fn _internal(py: Python, m: Bound<'_, PyModule>) -> PyResult<()> {
    // Initialize logging
    pyo3_log::init();

    // Register the python classes
    m.add_class::<context::PyRuntimeEnvBuilder>()?;
    m.add_class::<context::PySessionConfig>()?;
    m.add_class::<context::PySessionContext>()?;
    m.add_class::<context::PySQLOptions>()?;
    m.add_class::<dataframe::PyDataFrame>()?;
    m.add_class::<dataframe::PyInsertOp>()?;
    m.add_class::<dataframe::PyDataFrameWriteOptions>()?;
    m.add_class::<dataframe::PyParquetColumnOptions>()?;
    m.add_class::<dataframe::PyParquetWriterOptions>()?;
    m.add_class::<udf::PyScalarUDF>()?;
    m.add_class::<udaf::PyAggregateUDF>()?;
    m.add_class::<udwf::PyWindowUDF>()?;
    m.add_class::<udtf::PyTableFunction>()?;
    m.add_class::<sql::logical::PyLogicalPlan>()?;
    m.add_class::<metrics::PyMetricsSet>()?;
    m.add_class::<metrics::PyMetric>()?;
    m.add_class::<physical_plan::PyExecutionPlan>()?;
    m.add_class::<record_batch::PyRecordBatch>()?;
    m.add_class::<record_batch::PyRecordBatchStream>()?;

    let catalog = PyModule::new(py, "catalog")?;
    catalog::init_module(&catalog)?;
    m.add_submodule(&catalog)?;

    // Register `common` as a submodule. Matching `datafusion-common` https://docs.rs/datafusion-common/latest/datafusion_common/
    let common = PyModule::new(py, "common")?;
    common::init_module(&common)?;
    m.add_submodule(&common)?;

    // Register `expr` as a submodule. Matching `datafusion-expr` https://docs.rs/datafusion-expr/latest/datafusion_expr/
    let expr = PyModule::new(py, "expr")?;
    expr::init_module(&expr)?;
    m.add_submodule(&expr)?;

    let unparser = PyModule::new(py, "unparser")?;
    unparser::init_module(&unparser)?;
    m.add_submodule(&unparser)?;

    // Register the functions as a submodule
    let funcs = PyModule::new(py, "functions")?;
    functions::init_module(&funcs)?;
    // Spark-compatible functions live under `functions.spark`.
    let spark_funcs = PyModule::new(py, "spark")?;
    spark_functions::init_module(&spark_funcs)?;
    funcs.add_submodule(&spark_funcs)?;
    m.add_submodule(&funcs)?;

    let store = PyModule::new(py, "object_store")?;
    store::init_module(&store)?;
    m.add_submodule(&store)?;

    let options = PyModule::new(py, "options")?;
    options::init_module(&options)?;
    m.add_submodule(&options)?;

    // Register substrait as a submodule
    #[cfg(feature = "substrait")]
    setup_substrait_module(py, &m)?;

    Ok(())
}

#[cfg(feature = "substrait")]
fn setup_substrait_module(py: Python, m: &Bound<'_, PyModule>) -> PyResult<()> {
    let substrait = PyModule::new(py, "substrait")?;
    substrait::init_module(&substrait)?;
    m.add_submodule(&substrait)?;
    Ok(())
}