Orderbook

Every orderbook endpoint is publicly accessible — no credentials, no wallet, no authentication. Use them to inspect market state before submitting orders.

Client Setup

use openfish_client_sdk::clob::Client;

// Public client -- no auth needed
let client = Client::default(); // https://api.openfish.fun

REST base URL:

https://api.openfish.fun

---

Get the Orderbook

Returns the complete set of resting bid and ask levels for a given token.

use openfish_client_sdk::clob::types::request::OrderBookSummaryRequest;

let token_id = "TOKEN_ID".parse()?;
let request = OrderBookSummaryRequest::builder().token_id(token_id).build();
let book = client.order_book(&request).await?;

println!("Best bid: {:?}", book.bids.first());
println!("Best ask: {:?}", book.asks.first());
println!("Tick size: {:?}", book.tick_size);

REST:

GET /book?token_id=TOKEN_ID

Response

{
  "market": "0xbd31dc8a...",
  "asset_id": "52114319501245...",
  "timestamp": "2025-06-15T08:00:00Z",
  "bids": [
    { "price": "0.48", "size": "1000" },
    { "price": "0.47", "size": "2500" }
  ],
  "asks": [
    { "price": "0.52", "size": "800" },
    { "price": "0.53", "size": "1500" }
  ],
  "min_order_size": "5",
  "tick_size": "0.01",
  "neg_risk": false,
  "hash": "0xabc123..."
}

Field	Description
market	Condition ID of the market
asset_id	Token ID
bids	Buy orders sorted by price (highest first)
asks	Sell orders sorted by price (lowest first)
tick_size	Minimum price increment for this market
min_order_size	Minimum order size
neg_risk	Whether this is a multi-outcome (neg risk) market
hash	Hash of the orderbook state for change detection

Batch Orderbooks

Pull orderbooks for several tokens in a single call:

POST /books
Content-Type: application/json

[
  { "token_id": "TOKEN_A" },
  { "token_id": "TOKEN_B" }
]

---

Prices

Fetch the best available price on a particular side of the book.

use openfish_client_sdk::clob::types::{Side, request::PriceRequest};

let token_id = "TOKEN_ID".parse()?;

let buy_req = PriceRequest::builder().token_id(token_id).side(Side::Buy).build();
let buy_price = client.price(&buy_req).await?;
println!("Best ask (buy price): {}", buy_price.price);

let sell_req = PriceRequest::builder().token_id(token_id).side(Side::Sell).build();
let sell_price = client.price(&sell_req).await?;
println!("Best bid (sell price): {}", sell_price.price);

REST:

# Best price for buying (lowest ask)
GET /price?token_id=TOKEN_ID&side=BUY

# Best price for selling (highest bid)
GET /price?token_id=TOKEN_ID&side=SELL

Batch Prices

POST /prices
Content-Type: application/json

[
  { "token_id": "TOKEN_A", "side": "BUY" },
  { "token_id": "TOKEN_B", "side": "SELL" }
]

---

Midpoints

The midpoint is calculated as the mean of the best bid and best ask. Openfish surfaces this number as the market’s implied probability.

use openfish_client_sdk::clob::types::request::MidpointRequest;

let token_id = "TOKEN_ID".parse()?;
let request = MidpointRequest::builder().token_id(token_id).build();
let midpoint = client.midpoint(&request).await?;
println!("Midpoint: {}", midpoint.mid);

REST:

GET /midpoint?token_id=TOKEN_ID

Response:

{
  "mid": "0.50"
}

Batch Midpoints

POST /midpoints
Content-Type: application/json

[
  { "token_id": "TOKEN_A" },
  { "token_id": "TOKEN_B" }
]

---

Spreads

The spread measures the gap between the best ask and the best bid. Narrower spreads generally signal deeper liquidity.

use openfish_client_sdk::clob::types::request::SpreadRequest;

let token_id = "TOKEN_ID".parse()?;
let request = SpreadRequest::builder().token_id(token_id).build();
let spread = client.spread(&request).await?;
println!("Spread: {}", spread.spread);

REST:

GET /spread?token_id=TOKEN_ID

Response:

{
  "spread": "0.04"
}

Batch Spreads

POST /spreads
Content-Type: application/json

[
  { "token_id": "TOKEN_A" },
  { "token_id": "TOKEN_B" }
]

---

Depth Levels

Full depth information comes from the GET /book response. Both sides contain arrays of price levels, each aggregating all resting size at that price:

• Bids: ordered from highest price down
• Asks: ordered from lowest price up

Each level includes:

Field	Type	Description
price	string	Price at this level
size	string	Total resting size at this price

The engine computes depth from bid_levels() and ask_levels() on the in-memory OrderBook, walking the BTreeMap to aggregate orders at each price point.

---

Last Trade Price

Look up the most recent execution price and trade direction for a token.

use openfish_client_sdk::clob::types::request::LastTradePriceRequest;

let token_id = "TOKEN_ID".parse()?;
let request = LastTradePriceRequest::builder().token_id(token_id).build();
let last = client.last_trade_price(&request).await?;
println!("Last: {} ({})", last.price, last.side);

REST:

GET /last-trade-price?token_id=TOKEN_ID

---

Summary of Endpoints

Endpoint	Method	Description
/book	GET	Full orderbook for one token
/books	POST	Batch orderbooks for multiple tokens
/price	GET	Best price for one token and side
/prices	POST	Batch prices
/midpoint	GET	Midpoint for one token
/midpoints	POST	Batch midpoints
/spread	GET	Spread for one token
/spreads	POST	Batch spreads
/last-trade-price	GET	Most recent trade price

---

Next Steps

• Place Orders — Create and submit orders -> orders/create
• Matching Engine — How orders are matched -> matching-engine