Rust polars scan_parquet is much slower than python when reading from s3

Question

I am using polars to read a parquet file from S3 as a dataframe:

use cloud::AmazonS3ConfigKey as Key;
use eyre::Result;
use polars::prelude::*;
use dotenvy::dotenv;

fn lazyframe_from_s3_key(key: &str) -> Result<LazyFrame> {
    let access_key_id = std::env::var("aws_access_key_id")?;
    let secret_access_key = std::env::var("aws_secret_access_key")?;
    let region = std::env::var("aws_region")?;
    let cloud_options = cloud::CloudOptions::default().with_aws([
        (Key::AccessKeyId, access_key_id),
        (Key::SecretAccessKey, secret_access_key),
        (Key::Region, region),
    ]);
    let args = ScanArgsParquet {
        cloud_options: Some(cloud_options),
        ..Default::default()
    };

    let df = LazyFrame::scan_parquet(key, args)?
        .with_streaming(true);
    Ok(df)
}

macro_rules! time {
    ($msg:expr, $($stmts:stmt);+) => {
        let now = std::time::Instant::now();
        $($stmts)*
        println!("{}: {:.2?}", $msg, now.elapsed());
    };
}

pub fn dataframe_from_s3_key(key: &str) -> Result<DataFrame> {
    time!("lazyframe scan",
          let lf = lazyframe_from_s3_key(key)?);
    time!("lazyframe collect",
          let df = lf.collect()?);
    Ok(df)
}

fn main() -> Result<()> {
    dotenv()?;
    let df = dataframe_from_s3_key("s3://xxx/test.parquet")?;
    dbg!(&df);
    
    Ok(())
}

When I run this on a 60MB parquet file, it takes ~30s, almost all that time in the collect() call When I do the equivalent in Python:

import polars as pl

df = pl.scan_parquet("s3://xxx/test.parquet").collect()

it takes only about 5s. What is Python polars doing that I'm not? How can I get the Rust version to load as quickly?