from contexttimer import Timer
from dask import dataframe as dd
from dask.distributed import Client
import pandas as pd

if __name__ == '__main__':
    loops: int = 10
    client = Client(n_workers=loops)
    df: dd.DataFrame = dd.read_csv("data/womens-shoes.csv.xz", low_memory=False, dtype={"asins": "object", "prices.offer": "object", "upc": "object", "weight": "object"})
    pf = pd.read_csv("data/womens-shoes.csv.xz")
    af = pd.read_csv("data/womens-shoes.csv.xz", engine="pyarrow")

    # Dask Dataframe (±4800ms)
    with Timer() as timer:
        for i in range(loops):
            df2 = df.sort_values("prices.amountMin", ascending=bool(i % 2)).compute()
            print(df2["prices.amountMin"].iloc[0])
    print(timer.elapsed)

    # Pandas Dataframe (±35ms)
    with Timer() as timer:
        for i in range(loops):
            df2 = pf.sort_values("prices.amountMin", ascending=bool(i % 2))
            print(df2["prices.amountMin"].iloc[0])
    print(timer.elapsed)

    # Pandas PyArrow Dataframe (±29ms)
    with Timer() as timer:
        for i in range(loops):
            df2 = af.sort_values("prices.amountMin", ascending=bool(i % 2))
            print(df2["prices.amountMin"].iloc[0])
    print(timer.elapsed)