Chart a market's price

What you’ll get

A PNG step chart of one market’s Yes ask over up to 90 days, drawn from GET /v1/markets/{venue}/{id}/quotes. Where the window reaches back before asks were recorded, the line continues as archived hourly or daily closes, drawn dashed so the two are not confused. On 2026-09-17 a Super Bowl market gave 40 recorded points since 2026-09-14 and no archived ones.

Prerequisites

An API key in ROUTEUR_API_KEY
Python 3 with requests and matplotlib
A market: MARKET_ID=KXSB-27-LAR is used below

Read the quote history

Asks are recorded each time they change, oldest first. The first point is the last change before the window, so a chart can start at its left edge.

curl "https://api.routeur.app/v1/markets/kalshi/KXSB-27-LAR/quotes?days=90" -H "X-API-Key: $ROUTEUR_API_KEY"

The first and last points, observed 2026-09-17 12:48 UTC:

{ "data": [
  { "yes_ask_usd": "0.13", "no_ask_usd": "0.88", "observed_at": "2026-09-14T17:30:06.508223Z" },
  { "yes_ask_usd": "0.13", "no_ask_usd": "0.89", "observed_at": "2026-09-14T21:31:06.47361Z" },
  ...
  { "yes_ask_usd": "0.13", "no_ask_usd": "0.89", "observed_at": "2026-09-17T09:45:53.132177Z" }
] }

A point from before recording began has price_usd and source (venue or archive) instead of asks.

Draw it

A step chart is the honest shape: each price holds until the next change.

Python

import os
from datetime import datetime

import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
import requests

API = "https://api.routeur.app"
venue, market_id = os.environ.get("VENUE", "kalshi"), os.environ["MARKET_ID"]
headers = {"X-API-Key": os.environ["ROUTEUR_API_KEY"]}

res = requests.get(f"{API}/v1/markets/{venue}/{market_id}/quotes", params={"days": 90}, headers=headers, timeout=30)
res.raise_for_status()
quotes = res.json()["data"]

recorded, archived = [], []
for q in quotes:
    at = datetime.fromisoformat(q["observed_at"].replace("Z", "+00:00"))
    if q.get("yes_ask_usd"):
        recorded.append((at, float(q["yes_ask_usd"])))
    elif q.get("price_usd"):
        archived.append((at, float(q["price_usd"])))

print(f"{len(quotes)} points: {len(recorded)} recorded asks, {len(archived)} archived closes")
if quotes:
    print(f"first {quotes[0]['observed_at']}  last {quotes[-1]['observed_at']}")
    latest = quotes[-1]
    print(f"latest: Yes ask {latest.get('yes_ask_usd')}, Yes bid {latest.get('yes_bid_usd')}, No ask {latest.get('no_ask_usd')}")

fig, ax = plt.subplots(figsize=(10, 4))
if archived:
    ax.step(*zip(*archived), where="post", linestyle="--", label="Closing price (archived history)")
if recorded:
    ax.step(*zip(*recorded), where="post", label="Yes ask (recorded)")
ax.set_ylim(0, 1)
ax.set_ylabel("Price per $1 contract")
ax.set_title(f"{venue}:{market_id}")
ax.legend()
fig.autofmt_xdate()
plt.savefig("chart.png", dpi=120, bbox_inches="tight")
print("wrote chart.png")

MARKET_ID=KXSB-27-LAR python3 chart.py

Output observed 2026-09-17 12:48 UTC:

40 points: 40 recorded asks, 0 archived closes
first 2026-09-14T17:30:06.508223Z  last 2026-09-17T09:45:53.132177Z
latest: Yes ask 0.13, Yes bid None, No ask 0.89
wrote chart.png

The chart shows a flat line at 13¢ with brief dips to 12¢: the Rams’ Super Bowl price over three days.

Add the top of the book, if the market's book is recorded

Asks say what it cost to buy; the book says how much was there. GET /v1/markets/{venue}/{id}/book/history returns the best bid and ask, mid, spread and 5¢ depth per step, kept for 30 days, for markets whose book is recorded from the venue feed.

curl "https://api.routeur.app/v1/markets/kalshi/KXBTCD-26SEP1717-T76249.99/book/history?step=5m" -H "X-API-Key: $ROUTEUR_API_KEY"

{ "at": "2026-09-17T12:40:00Z", "yes_bid_usd": "0.75", "yes_ask_usd": "0.76", "mid_usd": "0.755", "microprice_usd": "0.752288",
  "spread_usd": "0.01", "yes_depth_5c_usd": "27467.05", "no_depth_5c_usd": "7189.42", "imbalance": "0.585103", "changes": 98 }

Plot yes_bid_usd and yes_ask_usd as a band around the ask line, and yes_depth_5c_usd on a second axis, to see when a move happened on size and when it happened on nothing.

Read the result

Field	Meaning
`yes_ask_usd`, `no_ask_usd`	The top-of-book asks when they changed, per contract that pays $1.
`yes_bid_usd`, `no_bid_usd`	The best resting bids. Only the latest point can carry them, and on 2026-09-17 it did not. Read `GET /v1/markets/{venue}/{id}` for the current bids.
`observed_at`	When the change was recorded. Kalshi is read every 15 minutes, Polymarket every 30, so a point is at most that stale.
`price_usd`, `source`	On points from before asks were recorded: the closing Yes price of the hour or day, from the venue’s own archive or imported history.

Pitfalls

At most 5,000 points per request. For a busy market over 90 days, ask for fewer days and stitch the windows.
Asks, not trades. The line is what it cost to buy, not what traded. GET /v1/markets/{venue}/{id}/trades has the fills.
A quiet line can hide an empty book. A 13¢ ask that never moves may be one resting order. Check liquidity, volume_24h_usd and book_yes_depth_5c_usd on the market before reading anything into it.
Archived closes are not asks. They are the day’s or hour’s last price, with no spread. Never mix the two in one series; the dashed line keeps them apart.

History: how quotes and trades are recorded, and how far back each goes.
Slippage at size: the full book at one moment, and what a $1,000 order would pay.
Stream consumer: the quotes and books topics push the same changes as they are recorded.
GET /v1/markets/{venue}/{id}/book?at=: the whole book as it stood at any moment in the last 90 days.

What you’ll get

Prerequisites

Read the result

Pitfalls

Related