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Goal: keep a dashboard of the wallets you care about, their aggregate P&L and their live positions. This recipe uses the batch endpoint for the numbers and the positions board for current holdings. All requests need a Bearer key. See Authentication.

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1. Aggregate P&L in one call

POST /api/v1/traders/batch takes up to 25 wallets (by address or trd_ id) and returns a full profile for each. This is the clean path for portfolio totals: 
import os, requests

BASE = "https://api.0xinsider.com/api/v1"
H = {"Authorization": f"Bearer {os.environ['OXINSIDER_API_KEY']}"}

wallets = ["0x204f...", "0x863...", "0x885..."]
batch = requests.post(
    f"{BASE}/traders/batch",
    json={"traders": wallets, "expand": ["trust"]},
    headers=H,
).json()

book = []
for item in batch["data"]:
    if item["status"] == "ok":
        t = item["data"]
        book.append({
            "wallet": t["address"],
            "name": t["username"],
            "grade": t["grade"],
            "total_pnl": t["pnl"]["total"],
            "unrealized": t["pnl"]["unrealized"],
            "last_30d": t["pnl"]["last_30d"],
        })
    else:
        print("failed:", item["input"], item["error"]["message"])

print("portfolio P&L:", sum(b["total_pnl"] for b in book))
Each item reports its own status (ok or error), so one bad wallet does not fail the batch. For more than 25 wallets, split into batches of 25.

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2. Current positions

There is no per-trader open-positions endpoint. The positions board is global, filterable by grade, size, side, and category, but not by wallet, so scan it and intersect on your wallet set: 
wallet_set = set(w.lower() for w in wallets)

def positions_for_book(min_size=1000):
    held, cursor = [], None
    while True:
        params = {"limit": 100, "min_size": min_size}
        if cursor:
            params["cursor"] = cursor
        page = requests.get(f"{BASE}/positions", params=params, headers=H).json()
        held += [p for p in page["data"] if p["trader"]["address"].lower() in wallet_set]
        if not page.get("has_more"):
            return held
        cursor = page["next_cursor"]

for p in positions_for_book():
    print(p["trader"]["address"][:10], p["market"]["outcome_label"],
          p["side"], f'${p["current_value_usd"]:,.0f}', p["freshness"])
Check each position’s freshness (trust) before you trust the value. fresh is live; stale means the provider read is past its window.

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3. Refresh cadence

  • Pull batch P&L on a slow loop (minutes). It is the heavier call.
  • Scan the positions board on whatever cadence your dashboard needs; it is cursor-paginated and cheap per page.
  • For a specific wallet-and-market pair, the position timeline gives exact entry and exit events.

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Scope and limits

Tracking N specific wallets means scanning the global positions board and filtering, because there is no “open positions for wallet X” endpoint. If your set is large, raise min_size so the board scan stays cheap and you only track meaningful positions. Aggregate P&L via batch is exact; the live position list is a board intersection.