geoarrow vs geopandas simplify tracts

import httpx
import asyncio
from bs4 import BeautifulSoup
import os
import geopandas as gpd
import pandas as pd
from pathlib import Path
from geoarrow.rust.core import (
    GeoTable,
    write_parquet,
    read_parquet,
)
import time




async def dl_file(url, sem, client):
    async with sem:
        resp = await client.get(url)
        file = url.split("/")[-1]
        with open(f"./tracts/{file}", "wb") as ff:
            ff.write(resp.content)


async def get_tract_data():
    client = httpx.AsyncClient(
    headers={
        "accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8",
        "accept-language": "en-US,en;q=0.9",
        "cache-control": "no-cache",
        "pragma": "no-cache",
        "priority": "u=0, i",
        "sec-ch-ua": '"Not/A)Brand";v="8", "Chromium";v="126", "Brave";v="126"',
        "sec-ch-ua-mobile": "?0",
        "sec-ch-ua-platform": '"Windows"',
        "sec-fetch-dest": "document",
        "sec-fetch-mode": "navigate",
        "sec-fetch-site": "none",
        "sec-fetch-user": "?1",
        "sec-gpc": "1",
        "upgrade-insecure-requests": "1",
        "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/126.0.0.0 Safari/537.36",
    }
)
    census_page = await client.get(
        "https://www.census.gov/cgi-bin/geo/shapefiles/index.php?year=2023&layergroup=Census+Tracts"
    )

    bs_page = BeautifulSoup(census_page.content, "html.parser")

    urls = [
        f"https://www2.census.gov/geo/tiger/TIGER2023/TRACT/tl_2023_{x.attrs['value']}_tract.zip"
        for x in bs_page.find_all("option")
    ]
    try:
        os.mkdir("./tracts")
    except FileExistsError:
        pass
    sem = asyncio.Semaphore(5)
    tasks = set()
    for url in urls:
        tasks.add(asyncio.create_task(dl_file(url, sem, client)))
    await asyncio.wait(tasks)
    all_states = []
    for tract in Path("tracts/2023").iterdir():
        all_states.append(gpd.read_file(tract))
    df = pd.concat(all_states)
    df.to_parquet("tracts2023gpd.parquet")
    geodf = GeoTable.from_geopandas(df)
    write_parquet(geodf, "tracts2023geo.parquet")
    
def main():
    df = read_parquet("tracts2023geo.parquet")
    strt=time.time()
    df.geometry.simplify(0.5)
    print(f"geoarrow simplify took {time.time()-strt} seconds")
    dfgpd = df.to_geopandas()
    strt=time.time()
    dfgpd.geometry.simplify(0.5)
    print(f"geopandas simplify took {time.time()-strt} seconds")