Hyperliquid HIP-3 markets API: stocks, oil, gold, indices and more

import os, requests
from datetime import datetime, timedelta, timezone

start = (datetime.now(timezone.utc) - timedelta(days=30)).strftime("%Y-%m-%dT%H:00:00Z")
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/funding-rates",
    params={"symbol": "xyz:CL", "start": start, "limit": 5000},
    headers={"X-API-KEY": os.environ["VIKE_API_KEY"]},
    timeout=30,
)
r.raise_for_status()
hours = [h for h in r.json()["items"] if h["funding_rate"] is not None]
mean = sum(h["funding_rate"] for h in hours) / len(hours)
longs_paid = sum(h["funding_rate"] > 0 for h in hours)
print(f"{len(hours)} hours, mean {mean:+.5%} an hour, {mean * 8760:+.1%} a year")
print(f"longs paid in {longs_paid} hours, shorts in {len(hours) - longs_paid}")
print(f"open interest now ${hours[0]['open_interest_usd']:,.0f}")

# Printed on 2026-11-05:
# 720 hours, mean -0.00122% an hour, -10.7% a year
# longs paid in 354 hours, shorts in 366
# open interest now $162,761,667

import os, requests
from datetime import datetime, timedelta, timezone

start = (datetime.now(timezone.utc) - timedelta(days=30)).strftime("%Y-%m-%dT00:00:00Z")
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/ohlcv",
    params={"symbol": "xyz:NVDA", "interval": "1d", "start": start},
    headers={"X-API-KEY": os.environ["VIKE_API_KEY"]},
    timeout=30,
)
r.raise_for_status()
bars = r.json()["candles"]
print(f"{len(bars)} days, close {bars[0]['close']} to {bars[-1]['close']}, ${sum(b['volume_usd'] for b in bars):,.0f} traded")
for b in bars[-3:]:
    day = datetime.fromtimestamp(b["ts"] / 1000, timezone.utc).date()
    print(day, b["open"], b["high"], b["low"], b["close"], f"${b['volume_usd']:,.0f}")

# Printed on 2026-11-05:
# 31 days, close 239.96 to 183.55, $3,034,834,065 traded
# 2026-11-03 203.7 211.01 202.57 208.1 $241,231,849
# 2026-11-04 208.12 210.99 199.84 201.25 $167,161,588
# 2026-11-05 201.22 201.36 181.78 183.55 $222,178,641

import os, requests
from datetime import datetime, timedelta, timezone

start = (datetime.now(timezone.utc) - timedelta(days=30)).strftime("%Y-%m-%dT%H:00:00Z")
rows, cursor = [], ""
while True:
    r = requests.get(
        "https://data.vike.io/v1/hyperliquid/liquidations",
        params={"symbol": "io:ANTH", "start": start, "limit": 5000, "cursor": cursor},
        headers={"X-API-KEY": os.environ["VIKE_API_KEY"]},
        timeout=30,
    )
    r.raise_for_status()
    rows += r.json()["liquidations"]
    cursor = r.json()["nextCursor"]
    if not cursor:
        break
longs = sum(x["size_usd"] for x in rows if x["side"] == "long")
shorts = sum(x["size_usd"] for x in rows if x["side"] == "short")
print(f"{len(rows)} liquidations: ${longs:,.0f} of longs, ${shorts:,.0f} of shorts")
for x in sorted(rows, key=lambda x: -x["size_usd"])[:3]:
    print(x["liq_ts"][:16], x["side"], f"${x['size_usd']:,.0f}", "at", x["mark_price"])

# Printed on 2026-11-05:
# 444 liquidations: $3,166,520 of longs, $304,203 of shorts
# 2026-10-30T10:17 long $514,121 at 1737.1
# 2026-11-05T15:30 long $301,817 at 1756.2
# 2026-11-03T20:51 long $173,648 at 1768.3

import os, requests
from datetime import datetime, timedelta, timezone

start = (datetime.now(timezone.utc) - timedelta(days=30)).strftime("%Y-%m-%dT%H:00:00Z")
r = requests.get(
    "https://data.vike.io/v1/hl-cohorts/symbols/xyz:GOLD/cohort-metrics",
    params={"axis": "size", "start": start, "hours": 720},
    headers={"X-API-KEY": os.environ["VIKE_API_KEY"]},
    timeout=60,
)
r.raise_for_status()
rows = r.json()["metrics"]
hours = sorted({x["ts"] for x in rows})
for ts in (hours[0], hours[-1]):
    print(ts[:16])
    for x in rows:
        if x["ts"] == ts and "whale" in x["cohort"]:
            long_usd = x["total_position_value_long"]
            short_usd = x["total_position_value"] - long_usd
            print(f"  {x['cohort']:9} long ${long_usd:>13,.0f}  short ${short_usd:>13,.0f}  bias {x['bias']:+.2f}")

# Printed on 2026-11-05:
# 2026-10-06T19:00
#   4x whale  long $   22,615,125  short $   75,440,244  bias -0.54
#   3x whale  long $      986,704  short $    1,361,144  bias -0.16
#   2x whale  long $   18,222,922  short $    9,770,433  bias +0.30
#   whale     long $   12,369,936  short $   10,638,557  bias +0.08
# 2026-11-05T17:00
#   4x whale  long $   14,028,041  short $   88,885,547  bias -0.73
#   3x whale  long $      763,936  short $    1,770,058  bias -0.40
#   2x whale  long $    6,112,927  short $    8,682,894  bias -0.17
#   whale     long $   29,620,460  short $   18,076,151  bias +0.24