feat: introduce eager loading functions

[lukapeschke]

What

This introduces eager loading functions that make use of the calamine's new DataTypeRef.

This prevents some allocations, resulting in a lower memory footprint.

Caveats

• The API is kinda rough for now, it will probably need some cleaning (I mostly wanted to check if the memory gain was interesting here).

• The functions need to be eager because DataTypeRef has an explicit lifetime, which is not allowed by PyO3 (lifetimes are hard to enforce on the python side: https://pyo3.rs/v0.20.0/class.html#no-lifetime-parameters)

• In order for this to work, some changes are needed in calamine, and we don't know if this is something the library maintainers had in mind. PR and discussion: refactor: make DataTypeRef public and introduce a DataTypeTrait trait tafia/calamine#390

Gains

While the speed stays roughly the same (it was even 3~5% faster on my machine on several tests), the memory footprint decreases by almost 25%. . This means that we're almost as good as pandas memory-wise 🥳 (they still beat us by a few MBs), while being about 10 times faster

Before

After

Pandas

[lukapeschke]

Some work is still required in calamine: tafia/calamine#409

[lukapeschke]

Okay well just noticed that the API changed so we actually need to use workshet_range_ref in case Sheets are the Xlsx variant

[PrettyWood]

Glad to see tafia/calamine#409 has been merged. Hopefully we get a new release soon 👍

[lukapeschke]

new data

main

import argparse
from time import sleep
import fastexcel


def get_args() -> argparse.Namespace:
    parser = argparse.ArgumentParser()
    parser.add_argument("file")
    parser.add_argument("-c", "--column", type=str, nargs="+", help="the columns to use")
    return parser.parse_args()


def main():
    args = get_args()
    excel_file = fastexcel.read_excel(args.file)
    use_columns = args.column or None

    for sheet_name in excel_file.sheet_names:
        arrow_data = excel_file.load_sheet_by_name(sheet_name, use_columns=use_columns).to_arrow()
        # sleeping to be really visible on the resulting graph
        sleep(1)
        arrow_data.to_pandas()


if __name__ == "__main__":
    main()

this branch

import argparse
from time import sleep
import fastexcel


def get_args() -> argparse.Namespace:
    parser = argparse.ArgumentParser()
    parser.add_argument("file")
    parser.add_argument("-c", "--column", type=str, nargs="+", help="the columns to use")
    return parser.parse_args()


def main():
    args = get_args()
    excel_file = fastexcel.read_excel(args.file)
    use_columns = args.column or None

    for sheet_name in excel_file.sheet_names:
        arrow_data = excel_file.load_sheet_eager(sheet_name)
        # sleeping to be really visible on the resulting graph
        sleep(1)
        arrow_data.to_pandas()


if __name__ == "__main__":
    main()

[PrettyWood]

New benchmark looks great 😃

[lukapeschke]

Good news, looks like we should be able to have lazy-by-ref once a new calamine version is out 🥳

Benchmarks with the latest version:

iterations	owned	by ref
1
20

[lukapeschke]

calamine 0.25.0 should be released soon, meaning I should finally be able to finish this 🙂 tafia/calamine#435