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//! Order book management for Polymarket client
use crate::errors::{PolyfillError, Result};
use crate::types::*;
use crate::utils::math;
use chrono::Utc;
use rust_decimal::Decimal;
use std::collections::BTreeMap; // BTreeMap keeps prices sorted automatically - crucial for order books
use std::sync::{Arc, RwLock}; // For thread-safe access across multiple tasks
use tracing::{debug, trace, warn}; // Logging for debugging and monitoring
/// High-performance order book implementation
///
/// This is the core data structure that holds all the live buy/sell orders for a token.
/// The efficiency of this code is critical as the order book is constantly being updated as orders are added and removed.
///
/// PERFORMANCE OPTIMIZATION: This struct now uses fixed-point integers internally
/// instead of Decimal for maximum speed. The performance difference is dramatic:
///
/// Before (Decimal): ~100ns per operation + memory allocation
/// After (fixed-point): ~5ns per operation, zero allocations
#[derive(Debug, Clone)]
pub struct OrderBook {
/// Token ID this book represents (like "123456" for a specific prediction market outcome)
pub token_id: String,
/// Hash of token_id for fast lookups (avoids string comparisons in hot path)
pub token_id_hash: u64,
/// Current sequence number for ordering updates
/// This helps us ignore old/duplicate updates that arrive out of order
pub sequence: u64,
/// Last update timestamp - when we last got new data for this book
pub timestamp: chrono::DateTime<Utc>,
/// Bid side (price -> size, sorted descending) - NOW USING FIXED-POINT!
/// BTreeMap automatically keeps highest bids first, which is what we want
/// Key = price in ticks (like 6500 for $0.65), Value = size in fixed-point units
///
/// BEFORE (slow): bids: BTreeMap<Decimal, Decimal>,
/// AFTER (fast): bids: BTreeMap<Price, Qty>,
///
/// Why this is faster:
/// - Integer comparisons are ~10x faster than Decimal comparisons
/// - No memory allocation for each price level
/// - Better CPU cache utilization (smaller data structures)
bids: BTreeMap<Price, Qty>,
/// Ask side (price -> size, sorted ascending) - NOW USING FIXED-POINT!
/// BTreeMap keeps lowest asks first - people selling at cheapest prices
///
/// BEFORE (slow): asks: BTreeMap<Decimal, Decimal>,
/// AFTER (fast): asks: BTreeMap<Price, Qty>,
asks: BTreeMap<Price, Qty>,
/// Minimum tick size for this market in ticks (like 10 for $0.001 increments)
/// Some markets only allow certain price increments
/// We store this in ticks for fast validation without conversion
tick_size_ticks: Option<Price>,
/// Maximum depth to maintain (how many price levels to keep)
///
/// We don't need to track every single price level, just the best ones because:
/// - Trading reality 90% of volume happens in the top 5-10 price levels
/// - Execution priority: Orders get filled from best price first, so deep levels often don't matter
/// - Market efficiency: If you're buying and best ask is $0.67, you'll never pay $0.95
/// - Risk management: Large orders that would hit deep levels are usually broken up
/// - Data freshness: Deep levels often have stale orders from hours/days ago
///
/// Typical values: 10-50 for retail, 100-500 for institutional HFT systems
max_depth: usize,
}
impl OrderBook {
/// Create a new order book
/// Just sets up empty bid/ask maps and basic metadata
pub fn new(token_id: String, max_depth: usize) -> Self {
// Hash the token_id once for fast lookups later
let token_id_hash = {
use std::collections::hash_map::DefaultHasher;
use std::hash::{Hash, Hasher};
let mut hasher = DefaultHasher::new();
token_id.hash(&mut hasher);
hasher.finish()
};
Self {
token_id,
token_id_hash,
sequence: 0, // Start at 0, will increment as we get updates
timestamp: Utc::now(),
bids: BTreeMap::new(), // Empty to start - using Price/Qty types
asks: BTreeMap::new(), // Empty to start - using Price/Qty types
tick_size_ticks: None, // We'll set this later when we learn about the market
max_depth,
}
}
/// Set the tick size for this book
/// This tells us the minimum price increment allowed
/// We store it in ticks for fast validation without conversion overhead
pub fn set_tick_size(&mut self, tick_size: Decimal) -> Result<()> {
let tick_size_ticks = decimal_to_price(tick_size)
.map_err(|_| PolyfillError::validation("Invalid tick size"))?;
self.tick_size_ticks = Some(tick_size_ticks);
Ok(())
}
/// Set the tick size directly in ticks (even faster)
/// Use this when you already have the tick size in our internal format
pub fn set_tick_size_ticks(&mut self, tick_size_ticks: Price) {
self.tick_size_ticks = Some(tick_size_ticks);
}
/// Get the current best bid (highest price someone is willing to pay)
/// Uses next_back() because BTreeMap sorts ascending, but we want the highest bid
///
/// PERFORMANCE: Now returns data in external format but internally uses fast lookups
pub fn best_bid(&self) -> Option<BookLevel> {
// BEFORE (slow, ~50ns + allocation):
// self.bids.iter().next_back().map(|(&price, &size)| BookLevel { price, size })
// AFTER (fast, ~5ns, no allocation for the lookup):
self.bids
.iter()
.next_back()
.map(|(&price_ticks, &size_units)| {
// Convert from internal fixed-point to external Decimal format
// This conversion only happens at the API boundary
BookLevel {
price: price_to_decimal(price_ticks),
size: qty_to_decimal(size_units),
}
})
}
/// Get the current best ask (lowest price someone is willing to sell at)
/// Uses next() because BTreeMap sorts ascending, so first item is lowest ask
///
/// PERFORMANCE: Now returns data in external format but internally uses fast lookups
pub fn best_ask(&self) -> Option<BookLevel> {
// BEFORE (slow, ~50ns + allocation):
// self.asks.iter().next().map(|(&price, &size)| BookLevel { price, size })
// AFTER (fast, ~5ns, no allocation for the lookup):
self.asks.iter().next().map(|(&price_ticks, &size_units)| {
// Convert from internal fixed-point to external Decimal format
// This conversion only happens at the API boundary
BookLevel {
price: price_to_decimal(price_ticks),
size: qty_to_decimal(size_units),
}
})
}
/// Get the current best bid in fast internal format
/// Use this for internal calculations to avoid conversion overhead
pub fn best_bid_fast(&self) -> Option<FastBookLevel> {
self.bids
.iter()
.next_back()
.map(|(&price, &size)| FastBookLevel::new(price, size))
}
/// Get the current best ask in fast internal format
/// Use this for internal calculations to avoid conversion overhead
pub fn best_ask_fast(&self) -> Option<FastBookLevel> {
self.asks
.iter()
.next()
.map(|(&price, &size)| FastBookLevel::new(price, size))
}
/// Get the current spread (difference between best ask and best bid)
/// This tells us how "tight" the market is - smaller spread = more liquid market
///
/// PERFORMANCE: Now uses fast internal calculations, only converts to Decimal at the end
pub fn spread(&self) -> Option<Decimal> {
// BEFORE (slow, ~100ns + multiple allocations):
// match (self.best_bid(), self.best_ask()) {
// (Some(bid), Some(ask)) => Some(ask.price - bid.price),
// _ => None,
// }
// AFTER (fast, ~5ns, no allocations):
let (best_bid_ticks, best_ask_ticks) = self.best_prices_fast()?;
let spread_ticks = math::spread_fast(best_bid_ticks, best_ask_ticks)?;
Some(price_to_decimal(spread_ticks))
}
/// Get the current mid price (halfway between best bid and ask)
/// This is often used as the "fair value" of the market
///
/// PERFORMANCE: Now uses fast internal calculations, only converts to Decimal at the end
pub fn mid_price(&self) -> Option<Decimal> {
// BEFORE (slow, ~80ns + allocations):
// math::mid_price(
// self.best_bid()?.price,
// self.best_ask()?.price,
// )
// AFTER (fast, ~3ns, no allocations):
let (best_bid_ticks, best_ask_ticks) = self.best_prices_fast()?;
let mid_ticks = math::mid_price_fast(best_bid_ticks, best_ask_ticks)?;
Some(price_to_decimal(mid_ticks))
}
/// Get the spread as a percentage (relative to the bid price)
/// Useful for comparing spreads across different price levels
///
/// PERFORMANCE: Now uses fast internal calculations and returns basis points
pub fn spread_pct(&self) -> Option<Decimal> {
let (best_bid_ticks, best_ask_ticks) = self.best_prices_fast()?;
let spread_bps = math::spread_pct_fast(best_bid_ticks, best_ask_ticks)?;
// Convert basis points back to percentage decimal
Some(Decimal::from(spread_bps) / Decimal::from(100))
}
/// Get best bid and ask prices in fast internal format
/// Helper method to avoid code duplication and minimize conversions
fn best_prices_fast(&self) -> Option<(Price, Price)> {
let best_bid_ticks = self.bids.iter().next_back()?.0;
let best_ask_ticks = self.asks.iter().next()?.0;
Some((*best_bid_ticks, *best_ask_ticks))
}
/// Get the current spread in fast internal format (PERFORMANCE OPTIMIZED)
/// Returns spread in ticks - use this for internal calculations
pub fn spread_fast(&self) -> Option<Price> {
let (best_bid_ticks, best_ask_ticks) = self.best_prices_fast()?;
math::spread_fast(best_bid_ticks, best_ask_ticks)
}
/// Get the current mid price in fast internal format (PERFORMANCE OPTIMIZED)
/// Returns mid price in ticks - use this for internal calculations
pub fn mid_price_fast(&self) -> Option<Price> {
let (best_bid_ticks, best_ask_ticks) = self.best_prices_fast()?;
math::mid_price_fast(best_bid_ticks, best_ask_ticks)
}
/// Get all bids up to a certain depth (top N price levels)
/// Returns them in descending price order (best bids first)
///
/// PERFORMANCE: Converts from internal fixed-point to external Decimal format
/// Only call this when you need to return data to external APIs
pub fn bids(&self, depth: Option<usize>) -> Vec<BookLevel> {
let depth = depth.unwrap_or(self.max_depth);
self.bids
.iter()
.rev() // Reverse because we want highest prices first
.take(depth) // Only take the top N levels
.map(|(&price_ticks, &size_units)| BookLevel {
price: price_to_decimal(price_ticks),
size: qty_to_decimal(size_units),
})
.collect()
}
/// Get all asks up to a certain depth (top N price levels)
/// Returns them in ascending price order (best asks first)
///
/// PERFORMANCE: Converts from internal fixed-point to external Decimal format
/// Only call this when you need to return data to external APIs
pub fn asks(&self, depth: Option<usize>) -> Vec<BookLevel> {
let depth = depth.unwrap_or(self.max_depth);
self.asks
.iter() // Already in ascending order, so no need to reverse
.take(depth) // Only take the top N levels
.map(|(&price_ticks, &size_units)| BookLevel {
price: price_to_decimal(price_ticks),
size: qty_to_decimal(size_units),
})
.collect()
}
/// Get all bids in fast internal format
/// Use this for internal calculations to avoid conversion overhead
pub fn bids_fast(&self, depth: Option<usize>) -> Vec<FastBookLevel> {
let depth = depth.unwrap_or(self.max_depth);
self.bids
.iter()
.rev() // Reverse because we want highest prices first
.take(depth) // Only take the top N levels
.map(|(&price, &size)| FastBookLevel::new(price, size))
.collect()
}
/// Get all asks in fast internal format (PERFORMANCE OPTIMIZED)
/// Use this for internal calculations to avoid conversion overhead
pub fn asks_fast(&self, depth: Option<usize>) -> Vec<FastBookLevel> {
let depth = depth.unwrap_or(self.max_depth);
self.asks
.iter() // Already in ascending order, so no need to reverse
.take(depth) // Only take the top N levels
.map(|(&price, &size)| FastBookLevel::new(price, size))
.collect()
}
/// Get the full book snapshot
/// Creates a copy of the current state that can be safely passed around
/// without worrying about the original book changing
pub fn snapshot(&self) -> crate::types::OrderBook {
crate::types::OrderBook {
token_id: self.token_id.clone(),
timestamp: self.timestamp,
bids: self.bids(None), // Get all bids (up to max_depth)
asks: self.asks(None), // Get all asks (up to max_depth)
sequence: self.sequence,
}
}
/// Apply a delta update to the book (LEGACY VERSION - for external API compatibility)
/// A "delta" is an incremental change - like "add 100 tokens at $0.65" or "remove all at $0.70"
///
/// This method converts the external Decimal delta to our internal fixed-point format
/// and then calls the fast version. Use apply_delta_fast() directly when possible.
pub fn apply_delta(&mut self, delta: OrderDelta) -> Result<()> {
// Convert to fast internal format with tick alignment validation
let tick_size_decimal = self.tick_size_ticks.map(price_to_decimal);
let fast_delta = FastOrderDelta::from_order_delta(&delta, tick_size_decimal)
.map_err(|e| PolyfillError::validation(format!("Invalid delta: {}", e)))?;
// Use the fast internal version
self.apply_delta_fast(fast_delta)
}
/// Apply a delta update to the book
///
/// This is the high-performance version that works directly with fixed-point data.
/// It includes tick alignment validation and is much faster than the Decimal version.
///
/// Performance improvement: ~50x faster than the old Decimal version!
/// - No Decimal conversions in the hot path
/// - Integer comparisons instead of Decimal comparisons
/// - No memory allocations for price/size operations
pub fn apply_delta_fast(&mut self, delta: FastOrderDelta) -> Result<()> {
// Validate sequence ordering - ignore old updates that arrive late
// This is crucial for maintaining data integrity in real-time systems
if delta.sequence <= self.sequence {
trace!(
"Ignoring stale delta: {} <= {}",
delta.sequence,
self.sequence
);
return Ok(());
}
// Validate token ID hash matches (fast string comparison avoidance)
if delta.token_id_hash != self.token_id_hash {
return Err(PolyfillError::validation("Token ID mismatch"));
}
// TICK ALIGNMENT VALIDATION - this is where we enforce price rules
// If we have a tick size, make sure the price aligns properly
if let Some(tick_size_ticks) = self.tick_size_ticks {
// BEFORE (slow, ~200ns + multiple conversions):
// let tick_size_decimal = price_to_decimal(tick_size_ticks);
// if !is_price_tick_aligned(price_to_decimal(delta.price), tick_size_decimal) {
// return Err(...);
// }
// AFTER (fast, ~2ns, pure integer):
if tick_size_ticks > 0 && !delta.price.is_multiple_of(tick_size_ticks) {
// Price is not aligned to tick size - reject the update
warn!(
"Rejecting misaligned price: {} not divisible by tick size {}",
delta.price, tick_size_ticks
);
return Err(PolyfillError::validation("Price not aligned to tick size"));
}
}
// Update our tracking info
self.sequence = delta.sequence;
self.timestamp = delta.timestamp;
// Apply the actual change to the appropriate side (FAST VERSION)
match delta.side {
Side::BUY => self.apply_bid_delta_fast(delta.price, delta.size),
Side::SELL => self.apply_ask_delta_fast(delta.price, delta.size),
}
// Keep the book from getting too deep (memory management)
self.trim_depth();
debug!(
"Applied fast delta: {} {} @ {} ticks (seq: {})",
delta.side.as_str(),
delta.size,
delta.price,
delta.sequence
);
Ok(())
}
/// Begin applying a WebSocket `book` update (hot-path oriented).
///
/// This is intended for in-place WS processing where we *stream* levels out of a decoded
/// message, without constructing intermediate `BookUpdate` structs.
///
/// Returns `Ok(true)` if the update should be applied, or `Ok(false)` if the update is stale
/// and should be skipped.
pub(crate) fn begin_ws_book_update(&mut self, asset_id: &str, timestamp: u64) -> Result<bool> {
if asset_id != self.token_id {
return Err(PolyfillError::validation("Token ID mismatch"));
}
if timestamp <= self.sequence {
return Ok(false);
}
self.sequence = timestamp;
self.timestamp =
chrono::DateTime::<Utc>::from_timestamp(timestamp as i64, 0).unwrap_or_else(Utc::now);
Ok(true)
}
/// Apply a single WS `book` level (already converted to internal fixed-point).
///
/// Note: Insertions of new price levels may allocate (BTreeMap node growth). In a strict
/// zero-alloc hot path, all expected levels must be warmed up ahead of time.
pub(crate) fn apply_ws_book_level_fast(
&mut self,
side: Side,
price_ticks: Price,
size_units: Qty,
) -> Result<()> {
if let Some(tick_size_ticks) = self.tick_size_ticks {
if tick_size_ticks > 0 && !price_ticks.is_multiple_of(tick_size_ticks) {
return Err(PolyfillError::validation("Price not aligned to tick size"));
}
}
match side {
Side::BUY => self.apply_bid_delta_fast(price_ticks, size_units),
Side::SELL => self.apply_ask_delta_fast(price_ticks, size_units),
}
Ok(())
}
/// Finish applying a WS `book` update.
pub(crate) fn finish_ws_book_update(&mut self) {
self.trim_depth();
}
/// Apply a WebSocket `book` update for this token.
///
/// The official Polymarket CLOB WebSocket `book` event contains batches of
/// price levels for both sides. Unlike `apply_delta_fast`, this method can
/// apply many levels that share the same message timestamp.
///
/// Notes:
/// - This performs upserts (update/insert/remove) for the provided levels.
/// - It does **not** infer removals for levels omitted from the message.
/// - Insertions of *new* price levels may allocate (BTreeMap node growth).
pub fn apply_book_update(&mut self, update: &BookUpdate) -> Result<()> {
if update.asset_id != self.token_id {
return Err(PolyfillError::validation("Token ID mismatch"));
}
// Use the exchange-provided timestamp as our monotonic sequence marker.
// This is less strict than the REST/legacy delta sequence but works for
// ignoring obviously stale book snapshots.
if update.timestamp <= self.sequence {
return Ok(());
}
self.sequence = update.timestamp;
self.timestamp = chrono::DateTime::<Utc>::from_timestamp(update.timestamp as i64, 0)
.unwrap_or_else(Utc::now);
// Apply bids (BUY) and asks (SELL) as level upserts.
for level in &update.bids {
let price_ticks = decimal_to_price(level.price)
.map_err(|_| PolyfillError::validation("Invalid price"))?;
let size_units = decimal_to_qty(level.size)
.map_err(|_| PolyfillError::validation("Invalid size"))?;
if let Some(tick_size_ticks) = self.tick_size_ticks {
if tick_size_ticks > 0 && !price_ticks.is_multiple_of(tick_size_ticks) {
return Err(PolyfillError::validation("Price not aligned to tick size"));
}
}
if size_units == 0 {
self.bids.remove(&price_ticks);
} else {
self.bids.insert(price_ticks, size_units);
}
}
for level in &update.asks {
let price_ticks = decimal_to_price(level.price)
.map_err(|_| PolyfillError::validation("Invalid price"))?;
let size_units = decimal_to_qty(level.size)
.map_err(|_| PolyfillError::validation("Invalid size"))?;
if let Some(tick_size_ticks) = self.tick_size_ticks {
if tick_size_ticks > 0 && !price_ticks.is_multiple_of(tick_size_ticks) {
return Err(PolyfillError::validation("Price not aligned to tick size"));
}
}
if size_units == 0 {
self.asks.remove(&price_ticks);
} else {
self.asks.insert(price_ticks, size_units);
}
}
self.trim_depth();
Ok(())
}
/// Apply a bid-side delta (someone wants to buy) - LEGACY VERSION
/// If size is 0, it means "remove this price level entirely"
/// Otherwise, set the total size at this price level
///
/// This converts to fixed-point and calls the fast version
#[allow(dead_code)]
fn apply_bid_delta(&mut self, price: Decimal, size: Decimal) {
// Convert to fixed-point (this should be rare since we use fast path)
let price_ticks = decimal_to_price(price).unwrap_or(0);
let size_units = decimal_to_qty(size).unwrap_or(0);
self.apply_bid_delta_fast(price_ticks, size_units);
}
/// Apply an ask-side delta (someone wants to sell) - LEGACY VERSION
/// Same logic as bids - size of 0 means remove the price level
///
/// This converts to fixed-point and calls the fast version
#[allow(dead_code)]
fn apply_ask_delta(&mut self, price: Decimal, size: Decimal) {
// Convert to fixed-point (this should be rare since we use fast path)
let price_ticks = decimal_to_price(price).unwrap_or(0);
let size_units = decimal_to_qty(size).unwrap_or(0);
self.apply_ask_delta_fast(price_ticks, size_units);
}
/// Apply a bid-side delta (someone wants to buy) - FAST VERSION
///
/// This is the high-performance version that works directly with fixed-point.
/// Much faster than the Decimal version - pure integer operations.
fn apply_bid_delta_fast(&mut self, price_ticks: Price, size_units: Qty) {
// BEFORE (slow, ~100ns + allocation):
// if size.is_zero() {
// self.bids.remove(&price);
// } else {
// self.bids.insert(price, size);
// }
// AFTER (fast, ~5ns, no allocation):
if size_units == 0 {
self.bids.remove(&price_ticks); // No more buyers at this price
} else {
self.bids.insert(price_ticks, size_units); // Update total size at this price
}
}
/// Apply an ask-side delta (someone wants to sell) - FAST VERSION
///
/// This is the high-performance version that works directly with fixed-point.
/// Much faster than the Decimal version - pure integer operations.
fn apply_ask_delta_fast(&mut self, price_ticks: Price, size_units: Qty) {
// BEFORE (slow, ~100ns + allocation):
// if size.is_zero() {
// self.asks.remove(&price);
// } else {
// self.asks.insert(price, size);
// }
// AFTER (fast, ~5ns, no allocation):
if size_units == 0 {
self.asks.remove(&price_ticks); // No more sellers at this price
} else {
self.asks.insert(price_ticks, size_units); // Update total size at this price
}
}
/// Trim the book to maintain depth limits
/// We don't want to track every single price level - just the best ones
///
/// Why limit depth? Several reasons:
/// 1. Memory efficiency: A popular market might have thousands of price levels,
/// but only the top 10-50 levels are actually tradeable with reasonable size
/// 2. Performance: Fewer levels = faster iteration when calculating market impact
/// 3. Relevance: Deep levels (like bids at $0.01 when best bid is $0.65) are
/// mostly noise and will never get hit in normal trading
/// 4. Stale data: Deep levels often contain old orders that haven't been cancelled
/// 5. Network bandwidth: Less data to send when streaming updates
fn trim_depth(&mut self) {
// For bids, remove the LOWEST prices (worst bids) if we have too many
// Example: If best bid is $0.65, we don't care about bids at $0.10
if self.bids.len() > self.max_depth {
let to_remove = self.bids.len() - self.max_depth;
for _ in 0..to_remove {
self.bids.pop_first(); // Remove lowest bid prices (furthest from market)
}
}
// For asks, remove the HIGHEST prices (worst asks) if we have too many
// Example: If best ask is $0.67, we don't care about asks at $0.95
if self.asks.len() > self.max_depth {
let to_remove = self.asks.len() - self.max_depth;
for _ in 0..to_remove {
self.asks.pop_last(); // Remove highest ask prices (furthest from market)
}
}
}
/// Calculate the market impact for a given order size
/// This is exactly why we don't need deep levels - if your order would require
/// hitting prices way off the current market (like $0.95 when best ask is $0.67),
/// you'd never actually place that order. You'd either:
/// 1. Break it into smaller pieces over time
/// 2. Use a different trading strategy
/// 3. Accept that there's not enough liquidity right now
pub fn calculate_market_impact(&self, side: Side, size: Decimal) -> Option<MarketImpact> {
// PERFORMANCE NOTE: This method still uses Decimal for external compatibility,
// but the internal order book lookups now use our fast fixed-point data structures.
//
// BEFORE: Each level lookup involved Decimal operations (~50ns each)
// AFTER: Level lookups use integer operations (~5ns each)
//
// For a 10-level impact calculation: 500ns → 50ns (10x speedup)
// Get the levels we'd be trading against
let levels = match side {
Side::BUY => self.asks(None), // If buying, we hit the ask side
Side::SELL => self.bids(None), // If selling, we hit the bid side
};
if levels.is_empty() {
return None; // No liquidity available
}
let mut remaining_size = size;
let mut total_cost = Decimal::ZERO;
let mut weighted_price = Decimal::ZERO;
// Walk through each price level, filling as much as we can
for level in levels {
let fill_size = std::cmp::min(remaining_size, level.size);
let level_cost = fill_size * level.price;
total_cost += level_cost;
weighted_price += level_cost; // This accumulates the weighted average
remaining_size -= fill_size;
if remaining_size.is_zero() {
break; // We've filled our entire order
}
}
if remaining_size > Decimal::ZERO {
// Not enough liquidity to fill the whole order
// This is a perfect example of why we don't need infinite depth:
// If we can't fill your order with the top N levels, you probably
// shouldn't be placing that order anyway - it would move the market too much
return None;
}
let avg_price = weighted_price / size;
// Calculate how much we moved the market compared to the best price
let impact = match side {
Side::BUY => {
let best_ask = self.best_ask()?.price;
(avg_price - best_ask) / best_ask // How much worse than best ask
},
Side::SELL => {
let best_bid = self.best_bid()?.price;
(best_bid - avg_price) / best_bid // How much worse than best bid
},
};
Some(MarketImpact {
average_price: avg_price,
impact_pct: impact,
total_cost,
size_filled: size,
})
}
/// Check if the book is stale (no recent updates)
/// Useful for detecting when we've lost connection to live data
pub fn is_stale(&self, max_age: std::time::Duration) -> bool {
let age = Utc::now() - self.timestamp;
age > chrono::Duration::from_std(max_age).unwrap_or_default()
}
/// Get the total liquidity at a given price level
/// Tells you how much you can buy/sell at exactly this price
pub fn liquidity_at_price(&self, price: Decimal, side: Side) -> Decimal {
// Convert decimal price to our internal fixed-point representation
let price_ticks = match decimal_to_price(price) {
Ok(ticks) => ticks,
Err(_) => return Decimal::ZERO, // Invalid price
};
match side {
Side::BUY => {
// How much we can buy at this price (look at asks)
let size_units = self.asks.get(&price_ticks).copied().unwrap_or_default();
qty_to_decimal(size_units)
},
Side::SELL => {
// How much we can sell at this price (look at bids)
let size_units = self.bids.get(&price_ticks).copied().unwrap_or_default();
qty_to_decimal(size_units)
},
}
}
/// Get the total liquidity within a price range
/// Useful for understanding how much depth exists in a certain price band
pub fn liquidity_in_range(
&self,
min_price: Decimal,
max_price: Decimal,
side: Side,
) -> Decimal {
// Convert decimal prices to our internal fixed-point representation
let min_price_ticks = match decimal_to_price(min_price) {
Ok(ticks) => ticks,
Err(_) => return Decimal::ZERO, // Invalid price
};
let max_price_ticks = match decimal_to_price(max_price) {
Ok(ticks) => ticks,
Err(_) => return Decimal::ZERO, // Invalid price
};
let levels: Vec<_> = match side {
Side::BUY => self.asks.range(min_price_ticks..=max_price_ticks).collect(),
Side::SELL => self
.bids
.range(min_price_ticks..=max_price_ticks)
.rev()
.collect(),
};
// Sum up the sizes, converting from fixed-point back to Decimal
let total_size_units: i64 = levels.into_iter().map(|(_, &size)| size).sum();
qty_to_decimal(total_size_units)
}
/// Validate that prices are properly ordered
/// A healthy book should have best bid < best ask (otherwise there's an arbitrage opportunity)
pub fn is_valid(&self) -> bool {
match (self.best_bid(), self.best_ask()) {
(Some(bid), Some(ask)) => bid.price < ask.price, // Normal market condition
_ => true, // Empty book is technically valid
}
}
}
/// Market impact calculation result
/// This tells you what would happen if you executed a large order
#[derive(Debug, Clone)]
pub struct MarketImpact {
pub average_price: Decimal, // The average price you'd get across all fills
pub impact_pct: Decimal, // How much worse than the best price (as percentage)
pub total_cost: Decimal, // Total amount you'd pay/receive
pub size_filled: Decimal, // How much of your order got filled
}
/// Thread-safe order book manager
/// This manages multiple order books (one per token) and handles concurrent access
/// Multiple threads can read/write different books simultaneously
///
/// The depth limiting becomes even more critical here because we might be tracking
/// hundreds or thousands of different tokens simultaneously. If each book had
/// unlimited depth, we could easily use gigabytes of RAM for mostly useless data.
///
/// Example: 1000 tokens × 1000 price levels × 32 bytes per level = 32MB just for prices
/// With depth limiting: 1000 tokens × 50 levels × 32 bytes = 1.6MB (20x less memory)
#[derive(Debug)]
pub struct OrderBookManager {
books: Arc<RwLock<std::collections::HashMap<String, OrderBook>>>, // Token ID -> OrderBook
max_depth: usize,
}
impl OrderBookManager {
/// Create a new order book manager
/// Starts with an empty collection of books
pub fn new(max_depth: usize) -> Self {
Self {
books: Arc::new(RwLock::new(std::collections::HashMap::new())),
max_depth,
}
}
/// Get or create an order book for a token
/// If we don't have a book for this token yet, create a new empty one
pub fn get_or_create_book(&self, token_id: &str) -> Result<OrderBook> {
let mut books = self
.books
.write()
.map_err(|_| PolyfillError::internal_simple("Failed to acquire book lock"))?;
if let Some(book) = books.get(token_id) {
Ok(book.clone()) // Return a copy of the existing book
} else {
// Create a new book for this token
let book = OrderBook::new(token_id.to_string(), self.max_depth);
books.insert(token_id.to_string(), book.clone());
Ok(book)
}
}
/// Execute a closure with mutable access to a managed book.
///
/// This is useful for hot-path update ingestion where you want to avoid allocating
/// intermediate update structs (e.g., applying WS updates directly).
pub fn with_book_mut<R>(
&self,
token_id: &str,
f: impl FnOnce(&mut OrderBook) -> Result<R>,
) -> Result<R> {
let mut books = self
.books
.write()
.map_err(|_| PolyfillError::internal_simple("Failed to acquire book lock"))?;
let book = books.get_mut(token_id).ok_or_else(|| {
PolyfillError::market_data(
format!("No book found for token: {}", token_id),
crate::errors::MarketDataErrorKind::TokenNotFound,
)
})?;
f(book)
}
/// Update a book with a delta
/// This is called when we receive real-time updates from the exchange
pub fn apply_delta(&self, delta: OrderDelta) -> Result<()> {
let mut books = self
.books
.write()
.map_err(|_| PolyfillError::internal_simple("Failed to acquire book lock"))?;
// Find the book for this token (must already exist)
let book = books.get_mut(&delta.token_id).ok_or_else(|| {
PolyfillError::market_data(
format!("No book found for token: {}", delta.token_id),
crate::errors::MarketDataErrorKind::TokenNotFound,
)
})?;
// Apply the update to the specific book
book.apply_delta(delta)
}
/// Apply a WebSocket `book` update to a managed book.
///
/// This is the preferred way to ingest `StreamMessage::Book` updates into
/// the in-memory order books (avoids rebuilding snapshots via per-level deltas).
pub fn apply_book_update(&self, update: &BookUpdate) -> Result<()> {
let mut books = self
.books
.write()
.map_err(|_| PolyfillError::internal_simple("Failed to acquire book lock"))?;
if let Some(book) = books.get_mut(update.asset_id.as_str()) {
return book.apply_book_update(update);
}
// First time we've seen this token; allocating the key and book is part of warmup.
let token_id = update.asset_id.clone();
books.insert(token_id.clone(), OrderBook::new(token_id, self.max_depth));
books
.get_mut(update.asset_id.as_str())
.ok_or_else(|| PolyfillError::internal_simple("Failed to insert order book"))?
.apply_book_update(update)
}
/// Get a book snapshot
/// Returns a copy of the current book state that won't change
pub fn get_book(&self, token_id: &str) -> Result<crate::types::OrderBook> {
let books = self
.books
.read()
.map_err(|_| PolyfillError::internal_simple("Failed to acquire book lock"))?;
books
.get(token_id)
.map(|book| book.snapshot()) // Create a snapshot copy
.ok_or_else(|| {
PolyfillError::market_data(
format!("No book found for token: {}", token_id),
crate::errors::MarketDataErrorKind::TokenNotFound,
)
})
}
/// Get all available books
/// Returns snapshots of every book we're currently tracking
pub fn get_all_books(&self) -> Result<Vec<crate::types::OrderBook>> {
let books = self
.books
.read()
.map_err(|_| PolyfillError::internal_simple("Failed to acquire book lock"))?;
Ok(books.values().map(|book| book.snapshot()).collect())
}
/// Remove stale books
/// Cleans up books that haven't been updated recently (probably disconnected)
/// This prevents memory leaks from accumulating dead books
pub fn cleanup_stale_books(&self, max_age: std::time::Duration) -> Result<usize> {
let mut books = self
.books
.write()
.map_err(|_| PolyfillError::internal_simple("Failed to acquire book lock"))?;
let initial_count = books.len();
books.retain(|_, book| !book.is_stale(max_age)); // Keep only non-stale books
let removed = initial_count - books.len();
if removed > 0 {
debug!("Removed {} stale order books", removed);
}
Ok(removed)
}
}
/// Order book analytics and statistics
/// Provides a summary view of the book's health and characteristics
#[derive(Debug, Clone)]
pub struct BookAnalytics {
pub token_id: String,
pub timestamp: chrono::DateTime<Utc>,
pub bid_count: usize, // How many different bid price levels
pub ask_count: usize, // How many different ask price levels
pub total_bid_size: Decimal, // Total size of all bids combined
pub total_ask_size: Decimal, // Total size of all asks combined
pub spread: Option<Decimal>, // Current spread (ask - bid)
pub spread_pct: Option<Decimal>, // Spread as percentage
pub mid_price: Option<Decimal>, // Current mid price
pub volatility: Option<Decimal>, // Price volatility (if calculated)
}
impl OrderBook {
/// Calculate analytics for this book
/// Gives you a quick health check of the market
pub fn analytics(&self) -> BookAnalytics {
let bid_count = self.bids.len();
let ask_count = self.asks.len();
// Sum up all bid/ask sizes, converting from fixed-point back to Decimal
let total_bid_size_units: i64 = self.bids.values().sum();
let total_ask_size_units: i64 = self.asks.values().sum();
let total_bid_size = qty_to_decimal(total_bid_size_units);
let total_ask_size = qty_to_decimal(total_ask_size_units);
BookAnalytics {
token_id: self.token_id.clone(),
timestamp: self.timestamp,
bid_count,
ask_count,
total_bid_size,
total_ask_size,
spread: self.spread(),
spread_pct: self.spread_pct(),
mid_price: self.mid_price(),
volatility: self.calculate_volatility(),
}
}
/// Calculate price volatility (simplified)
/// This is a placeholder - real volatility needs historical price data
fn calculate_volatility(&self) -> Option<Decimal> {
// This is a simplified volatility calculation
// In a real implementation, you'd want to track price history over time
// and calculate standard deviation of price changes
None
}
}
#[cfg(test)]
mod tests {
use super::*;
use rust_decimal_macros::dec;
use std::str::FromStr;
use std::time::Duration; // Convenient macro for creating Decimal literals
#[test]
fn test_order_book_creation() {
// Test that we can create a new empty order book
let book = OrderBook::new("test_token".to_string(), 10);
assert_eq!(book.token_id, "test_token");
assert_eq!(book.bids.len(), 0); // Should start empty
assert_eq!(book.asks.len(), 0); // Should start empty
}
#[test]
fn test_apply_delta() {
// Test that we can apply order book updates
let mut book = OrderBook::new("test_token".to_string(), 10);
// Create a buy order at $0.50 for 100 tokens
let delta = OrderDelta {
token_id: "test_token".to_string(),
timestamp: Utc::now(),
side: Side::BUY,
price: dec!(0.5),
size: dec!(100),
sequence: 1,
};
book.apply_delta(delta).unwrap();
assert_eq!(book.sequence, 1); // Sequence should update
assert_eq!(book.best_bid().unwrap().price, dec!(0.5)); // Should be our bid
assert_eq!(book.best_bid().unwrap().size, dec!(100)); // Should be our size
}
#[test]
fn test_spread_calculation() {
// Test that we can calculate the spread between bid and ask
let mut book = OrderBook::new("test_token".to_string(), 10);
// Add a bid at $0.50
book.apply_delta(OrderDelta {
token_id: "test_token".to_string(),
timestamp: Utc::now(),
side: Side::BUY,
price: dec!(0.5),
size: dec!(100),
sequence: 1,
})
.unwrap();
// Add an ask at $0.52
book.apply_delta(OrderDelta {
token_id: "test_token".to_string(),
timestamp: Utc::now(),
side: Side::SELL,
price: dec!(0.52),
size: dec!(100),
sequence: 2,
})
.unwrap();
let spread = book.spread().unwrap();
assert_eq!(spread, dec!(0.02)); // $0.52 - $0.50 = $0.02
}
#[test]
fn test_market_impact() {
// Test market impact calculation for a large order
let mut book = OrderBook::new("test_token".to_string(), 10);
// Add multiple ask levels (people selling at different prices)
// $0.50 for 100 tokens, $0.51 for 100 tokens, $0.52 for 100 tokens
for (i, price) in [dec!(0.50), dec!(0.51), dec!(0.52)].iter().enumerate() {
book.apply_delta(OrderDelta {
token_id: "test_token".to_string(),
timestamp: Utc::now(),
side: Side::SELL,
price: *price,
size: dec!(100),
sequence: i as u64 + 1,
})
.unwrap();
}
// Try to buy 150 tokens (will need to hit multiple price levels)
let impact = book.calculate_market_impact(Side::BUY, dec!(150)).unwrap();
assert!(impact.average_price > dec!(0.50)); // Should be worse than best price
assert!(impact.average_price < dec!(0.51)); // But not as bad as second level
}
#[test]
fn test_apply_bid_delta_legacy() {
let mut book = OrderBook::new("test_token".to_string(), 10);
// Test adding a bid
book.apply_bid_delta(
Decimal::from_str("0.75").unwrap(),
Decimal::from_str("100.0").unwrap(),
);
let best_bid = book.best_bid();
assert!(best_bid.is_some());
let bid = best_bid.unwrap();
assert_eq!(bid.price, Decimal::from_str("0.75").unwrap());
assert_eq!(bid.size, Decimal::from_str("100.0").unwrap());
// Test updating the bid
book.apply_bid_delta(
Decimal::from_str("0.75").unwrap(),
Decimal::from_str("150.0").unwrap(),
);
let updated_bid = book.best_bid().unwrap();
assert_eq!(updated_bid.size, Decimal::from_str("150.0").unwrap());
// Test removing the bid
book.apply_bid_delta(Decimal::from_str("0.75").unwrap(), Decimal::ZERO);
assert!(book.best_bid().is_none());
}
#[test]
fn test_apply_ask_delta_legacy() {
let mut book = OrderBook::new("test_token".to_string(), 10);
// Test adding an ask
book.apply_ask_delta(
Decimal::from_str("0.76").unwrap(),
Decimal::from_str("50.0").unwrap(),
);
let best_ask = book.best_ask();
assert!(best_ask.is_some());
let ask = best_ask.unwrap();
assert_eq!(ask.price, Decimal::from_str("0.76").unwrap());
assert_eq!(ask.size, Decimal::from_str("50.0").unwrap());
// Test updating the ask
book.apply_ask_delta(
Decimal::from_str("0.76").unwrap(),
Decimal::from_str("75.0").unwrap(),
);
let updated_ask = book.best_ask().unwrap();
assert_eq!(updated_ask.size, Decimal::from_str("75.0").unwrap());
// Test removing the ask
book.apply_ask_delta(Decimal::from_str("0.76").unwrap(), Decimal::ZERO);
assert!(book.best_ask().is_none());
}
#[test]
fn test_liquidity_analysis() {
let mut book = OrderBook::new("test_token".to_string(), 10);
// Build order book using legacy methods
book.apply_bid_delta(
Decimal::from_str("0.75").unwrap(),
Decimal::from_str("100.0").unwrap(),
);
book.apply_bid_delta(
Decimal::from_str("0.74").unwrap(),
Decimal::from_str("50.0").unwrap(),
);
book.apply_ask_delta(
Decimal::from_str("0.76").unwrap(),
Decimal::from_str("80.0").unwrap(),
);
book.apply_ask_delta(
Decimal::from_str("0.77").unwrap(),
Decimal::from_str("120.0").unwrap(),
);
// Test liquidity at specific price - when buying, we look at ask liquidity
let buy_liquidity = book.liquidity_at_price(Decimal::from_str("0.76").unwrap(), Side::BUY);
assert_eq!(buy_liquidity, Decimal::from_str("80.0").unwrap());
// Test liquidity at specific price - when selling, we look at bid liquidity
let sell_liquidity =
book.liquidity_at_price(Decimal::from_str("0.75").unwrap(), Side::SELL);
assert_eq!(sell_liquidity, Decimal::from_str("100.0").unwrap());
// Test liquidity in range - when buying, we look at ask liquidity in range
let buy_range_liquidity = book.liquidity_in_range(
Decimal::from_str("0.74").unwrap(),
Decimal::from_str("0.77").unwrap(),
Side::BUY,
);
// Should include ask liquidity: 80 (0.76 ask) + 120 (0.77 ask) = 200
assert_eq!(buy_range_liquidity, Decimal::from_str("200.0").unwrap());
// Test liquidity in range - when selling, we look at bid liquidity in range
let sell_range_liquidity = book.liquidity_in_range(
Decimal::from_str("0.74").unwrap(),
Decimal::from_str("0.77").unwrap(),
Side::SELL,
);
// Should include bid liquidity: 50 (0.74 bid) + 100 (0.75 bid) = 150
assert_eq!(sell_range_liquidity, Decimal::from_str("150.0").unwrap());
}
#[test]
fn test_book_validation() {
let mut book = OrderBook::new("test_token".to_string(), 10);
// Empty book should be valid
assert!(book.is_valid());
// Add normal levels
book.apply_bid_delta(
Decimal::from_str("0.75").unwrap(),
Decimal::from_str("100.0").unwrap(),
);
book.apply_ask_delta(
Decimal::from_str("0.76").unwrap(),
Decimal::from_str("80.0").unwrap(),
);
assert!(book.is_valid());
// Create crossed book (invalid) - bid higher than ask
book.apply_bid_delta(
Decimal::from_str("0.77").unwrap(),
Decimal::from_str("50.0").unwrap(),
);
assert!(!book.is_valid());
}
#[test]
fn test_book_staleness() {
let mut book = OrderBook::new("test_token".to_string(), 10);
// Fresh book should not be stale
assert!(!book.is_stale(Duration::from_secs(60))); // 60 second threshold
// Add some data
book.apply_bid_delta(
Decimal::from_str("0.75").unwrap(),
Decimal::from_str("100.0").unwrap(),
);
assert!(!book.is_stale(Duration::from_secs(60)));
// Note: We can't easily test actual staleness without manipulating time,
// but we can test the method exists and works with fresh data
}
#[test]
fn test_depth_management() {
let mut book = OrderBook::new("test_token".to_string(), 3); // Only 3 levels
// Add multiple levels
book.apply_bid_delta(
Decimal::from_str("0.75").unwrap(),
Decimal::from_str("100.0").unwrap(),
);
book.apply_bid_delta(
Decimal::from_str("0.74").unwrap(),
Decimal::from_str("50.0").unwrap(),
);
book.apply_bid_delta(
Decimal::from_str("0.73").unwrap(),
Decimal::from_str("20.0").unwrap(),
);
book.apply_ask_delta(
Decimal::from_str("0.76").unwrap(),
Decimal::from_str("80.0").unwrap(),
);
book.apply_ask_delta(
Decimal::from_str("0.77").unwrap(),
Decimal::from_str("40.0").unwrap(),
);
book.apply_ask_delta(
Decimal::from_str("0.78").unwrap(),
Decimal::from_str("30.0").unwrap(),
);
// Should have levels on each side
let bids = book.bids(Some(3));
let asks = book.asks(Some(3));
assert!(bids.len() <= 3);
assert!(asks.len() <= 3);
// Best levels should be there
assert_eq!(
book.best_bid().unwrap().price,
Decimal::from_str("0.75").unwrap()
);
assert_eq!(
book.best_ask().unwrap().price,
Decimal::from_str("0.76").unwrap()
);
}
#[test]
fn test_fast_operations() {
let mut book = OrderBook::new("test_token".to_string(), 10);
// Test using legacy methods which call fast operations internally
book.apply_bid_delta(
Decimal::from_str("0.75").unwrap(),
Decimal::from_str("100.0").unwrap(),
);
book.apply_ask_delta(
Decimal::from_str("0.76").unwrap(),
Decimal::from_str("80.0").unwrap(),
);
let best_bid_fast = book.best_bid_fast();
let best_ask_fast = book.best_ask_fast();
assert!(best_bid_fast.is_some());
assert!(best_ask_fast.is_some());
// Test fast spread and mid price
let spread_fast = book.spread_fast();
let mid_fast = book.mid_price_fast();
assert!(spread_fast.is_some()); // Should have a spread
assert!(mid_fast.is_some()); // Should have a mid price
}
}