//! Benchmarks for result streaming and response building performance
//!
//! Note: These benchmarks simulate streaming operations.
//! Real streaming benchmarks will be added in Phase 3.

use criterion::{criterion_group, criterion_main, BenchmarkId, Criterion, Throughput};

/// Benchmark JSON field name transformation
fn bench_field_transformation(c: &mut Criterion) {
    let mut group = c.benchmark_group("field_transformation");

    for field_count in [10, 50, 100].iter() {
        group.bench_with_input(
            BenchmarkId::from_parameter(field_count),
            field_count,
            |b, &field_count| {
                b.iter(|| {
                    // Simulate transforming N field names from snake_case to camelCase
                    let mut transformed = Vec::with_capacity(*field_count);
                    for i in 0..*field_count {
                        let snake = format!("field_name_{}", i);
                        // Simple simulation of transformation
                        let camel = snake.replace("_", "");
                        transformed.push(camel);
                    }
                    let _result = transformed;
                });
            },
        );
    }
    group.finish();
}

/// Benchmark response serialization
fn bench_response_serialization(c: &mut Criterion) {
    let mut group = c.benchmark_group("response_serialization");

    for object_count in [10, 100, 1000].iter() {
        group.throughput(Throughput::Elements(*object_count as u64));
        group.bench_with_input(
            BenchmarkId::from_parameter(object_count),
            object_count,
            |b, &object_count| {
                b.iter(|| {
                    // Simulate serializing N objects to JSON
                    let mut json_strings = Vec::with_capacity(*object_count);
                    for i in 0..*object_count {
                        let json = format!(r#"{{"id": {}, "name": "Item {}"}}"#, i, i);
                        json_strings.push(json);
                    }
                    let _serialized = json_strings.join(",");
                });
            },
        );
    }
    group.finish();
}

/// Benchmark chunked data processing
fn bench_chunked_processing(c: &mut Criterion) {
    let mut group = c.benchmark_group("chunked_processing");

    for chunk_size in [1024, 8192, 65536].iter() {
        group.throughput(Throughput::Bytes(*chunk_size as u64));
        group.bench_with_input(
            BenchmarkId::from_parameter(chunk_size),
            chunk_size,
            |b, &chunk_size| {
                b.iter(|| {
                    // Simulate processing data in chunks
                    let data = vec![42u8; *chunk_size];
                    let mut checksum = 0u64;
                    for &byte in &data {
                        checksum = checksum.wrapping_add(byte as u64);
                    }
                    let _result = checksum;
                });
            },
        );
    }
    group.finish();
}

/// Benchmark response buffering strategy
fn bench_response_buffering(c: &mut Criterion) {
    c.bench_function("response_buffering", |b| {
        b.iter(|| {
            // Simulate response buffering with capacity management
            let mut buffer = Vec::with_capacity(4096);
            for i in 0..1000 {
                let chunk = format!("chunk_{}", i);
                buffer.extend_from_slice(chunk.as_bytes());

                // Simulate buffer flushing when full
                if buffer.len() > 2048 {
                    buffer.clear();
                }
            }
            let _final_size = buffer.len();
        });
    });
}

criterion_group! {
    name = benches;
    config = Criterion::default()
        .measurement_time(Duration::from_secs(10))
        .sample_size(100);
    targets =
        bench_field_transformation,
        bench_response_serialization,
        bench_chunked_processing,
        bench_response_buffering
}

criterion_main!(benches);
