import urllib.request, json, time, pandas as pd
URL="https://api.hyperliquid.xyz/info"
start_ms = int(pd.Timestamp("2026-04-01", tz="UTC").timestamp()*1000)
end_ms   = int(pd.Timestamp("2026-05-01", tz="UTC").timestamp()*1000)
rows=[]; cursor=start_ms
while cursor < end_ms:
    body=json.dumps({"type":"fundingHistory","coin":"BTC","startTime":cursor,"endTime":end_ms}).encode()
    req=urllib.request.Request(URL,data=body,headers={"Content-Type":"application/json"})
    with urllib.request.urlopen(req,timeout=30) as r:
        chunk=json.loads(r.read().decode())
    if not chunk: break
    rows.extend(chunk)
    last=int(chunk[-1].get("time",0))
    if last<=cursor: break
    cursor=last+1
    time.sleep(0.15)
df=pd.DataFrame(rows)
df["ts"]=pd.to_datetime(df["time"].astype("int64"),unit="ms",utc=True)
df["fbps_ann"]=df["fundingRate"].astype(float)*8760*10000
print(f"rows: {len(df)}   expected: 720")
print(f"span: {df.ts.min()} -> {df.ts.max()}")
print(f"fbps_ann: mean={df.fbps_ann.mean():+.1f}  std={df.fbps_ann.std():.1f}  min={df.fbps_ann.min():+.1f}  max={df.fbps_ann.max():+.1f}")
df.to_parquet("/tmp/april_funding_verify.parquet")
print("OK: API returns full April funding cleanly.")