Orderbook

A fast L2/L3 orderbook data structure, in C, for Python

Installation

Python 3.12+ supported. In general, uv is preferred and will be utilized throughout this document.

To add it to a project uv add order-book or, to install it into an environment directly, uv pip install order-book

Installing from a checkout of this repository: uv pip install . (note a C compiler is required).

Basic Usage

from decimal import Decimal

import requests
from order_book import OrderBook

ob = OrderBook()

# get some orderbook data
data = requests.get("https://api.exchange.coinbase.com/products/BTC-USD/book?level=2").json()

ob.bids = {Decimal(price): size for price, size, _ in data['bids']}
ob.asks = {Decimal(price): size for price, size, _ in data['asks']}

# OR

for side in data:
    # there is additional data we need to ignore
    if side in {'bids', 'asks'}:
        ob[side] = {Decimal(price): size for price, size, _ in data[side]}


# Data is accessible by .index(), which returns a tuple of (price, size) at that level in the book
price, size = ob.bids.index(0)
print(f"Best bid price: {price} size: {size}")

price, size = ob.asks.index(0)
print(f"Best ask price: {price} size: {size}")

print(f"The spread is {ob.asks.index(0)[0] - ob.bids.index(0)[0]}\n\n")

# Negative indexes work as well, so the worst bid/ask is index -1
print(f"Worst bid: {ob.bids.index(-1)}")

# Data is accessible via iteration
# Note: bids/asks are iterators

print("Top 10 bids")
for count, price in enumerate(ob.bids):
    if count == 10:
        break
    print(f"Price: {price} Size: {ob.bids[price]}")


print("\n\nTop 10 asks")
for count, price in enumerate(ob.asks):
    if count == 10:
        break
    print(f"Price: {price} Size: {ob.asks[price]}")


# Membership tests and len() work as expected
print(f"\nBest bid still in book: {ob.bids.index(0)[0] in ob.bids}")
print(f"Bid levels: {len(ob.bids)}, ask levels: {len(ob.asks)}, both sides: {len(ob)}")


# Data can be exported to a sorted dictionary
# In Python3.7+ dictionaries remain in insertion ordering. The
# dict returned by .to_dict() has had its keys inserted in sorted order
print("\n\nTop 3 asks, as a dictionary")
print(dict(list(ob.asks.to_dict().items())[:3]))


# Data can also be exported as an ordered list
# .to_list() returns a list of (price, size) tuples
print("\nTop 5 Asks")
print(ob.asks.to_list()[:5])
print("\nTop 5 Bids")
print(ob.bids.to_list()[:5])


# .keys() returns the sorted prices as a tuple
print("\nTop 5 ask prices")
print(ob.asks.keys()[:5])


# The entire book can be exported at once. The keys are 'bid' and 'ask' (singular)
book = ob.to_dict()
print(f"\nto_dict() keys: {list(book)}")

Both sides accept any of bid, bids, BID, BIDS (and the ask equivalents), as attributes or as keys:

from order_book import OrderBook

ob = OrderBook()

ob.bids[100] = "1.5"     # attribute access
ob['bids'][99] = "2.0"   # key access
ob['BID'][98] = "0.5"    # case does not matter

print(ob.bid.to_list())  # [(100, '1.5'), (99, '2.0'), (98, '0.5')]

# assigning a dict to a side replaces that side wholesale
ob.asks = {101: "1.0", 102: "3.0"}
print(ob.asks.to_list())  # [(101, '1.0'), (102, '3.0')]

# levels are removed with del
del ob.asks[101]
print(ob.asks.to_list())  # [(102, '3.0')]

Max Depth

max_depth limits how many levels are visible. len(), iteration, keys(), index(), to_dict() and to_list() all respect it.

from order_book import OrderBook

ob = OrderBook(max_depth=3)
ob.bids = {price: price for price in range(10)}

print(len(ob.bids))        # 3
print(ob.bids.to_list())   # [(9, 9), (8, 8), (7, 7)]
print(ob.max_depth)        # 3

By default the levels beyond max_depth are still retained internally, they are just hidden. Pass max_depth_strict=True to have them deleted as the book is updated, which caps memory use but means out-of-depth levels can no longer be accessed:

from order_book import OrderBook

ob = OrderBook(max_depth=3, max_depth_strict=True)
for price in range(10):
    ob.bids[price] = price

print(ob.bids.to_list())   # [(9, 9), (8, 8), (7, 7)]

try:
    del ob.bids[0]         # level 0 was dropped, not merely hidden
except KeyError:
    print("level 0 is gone")

Checksums

Several exchanges publish a CRC32 checksum of the top of book so clients can detect a desynchronized book. Construct the book with checksum_format set to the exchange, then compare ob.checksum() against the value the exchange sent.

Supported formats: KRAKEN, OKX (and its alias OKCOIN), and BITGET.

from decimal import Decimal

from order_book import OrderBook

ob = OrderBook(checksum_format='KRAKEN')

ob.bids = {Decimal(f"{100 - i}.{i:02d}"): Decimal(f"{i + 1}.5") for i in range(10)}
ob.asks = {Decimal(f"{101 + i}.{i:02d}"): Decimal(f"{i + 1}.5") for i in range(10)}

print(ob.checksum())

Type conversion

to_dict() on either an OrderBook or a SortedDict accepts from_type and to_type keyword arguments, which convert keys and values as the dictionary is built. from_type restricts the conversion to values of that type; omit it to convert everything.

from order_book import OrderBook

ob = OrderBook()
ob.bids = {'1.1': 2, '3.3': 4}
ob.asks = {'5.5': 6, '7.7': 8}

print(ob.to_dict(from_type=str, to_type=float))
# {'bid': {3.3: 4, 1.1: 2}, 'ask': {5.5: 6, 7.7: 8}}
# note the bid side is in descending order, as always

API Summary

OrderBook(max_depth=0, max_depth_strict=False, checksum_format=None)

SortedDict(data=None, ordering='ASC', max_depth=0, truncate=False)

Main Features

• Sides maintained in correct order
• Can perform orderbook checksums
• Supports max depth and depth truncation

Running code coverage

The script coverage.sh will compile the source using the -coverage CFLAG, run the unit tests, and build a coverage report in HTML. It manages its own environment via uv, so it can be run directly.

Note that it rebuilds .venv with an instrumented, unoptimized-for-timing build, so re-run uv pip install ".[tests]" afterwards to get back to a normal development environment.

Running the performance tests

You can run the performance tests like so: uv run perf/performance_test.py. The program will profile the time to run for random data samples of various sizes as well as the construction of a sorted orderbook using live L2 orderbook data from Coinbase.

The performance of constructing a sorted orderbook (using live data from Coinbase) using this C library, versus a pure Python sorted dictionary library:

The performance of constructing sorted dictionaries using the same libraries, as well as the cost of building unsorted, python dictionaies for dictionaries of random floating point data:

This represents a roughly 2x speedup compared to a pure python implementation, and in many cases is close to the performance of an unsorted python dictionary.

For other performance metrics, run performance_test.py as well as the other performance tests in perf/

Changelog

0.7.0 (2026-08-05)

• Update: Modernize project (uv, pyproject.toml, etc)
• Update: Update readme, tests, examples, etc
• Update: revamp wheel building

0.6.1 (2024-04-22)

• Update: to_list's behavior matches that of to_dict (respects max_depth, if set).
• Update: resolve build warnings on some compilers.

0.6.0 (2022-10-19)

• Update: Drop support for python 3.7
• Feature: to_list method
• Bugfix: Initialize iterator correctly

0.5.0 (2022-08-23)

• Bugfix: fix segmentation fault when calculating checksum on empty orderbook
• Bugfix: fix missing reference decrement
• Performance: Improvement to marking dirty keys

0.4.3 (2022-05-29)

• Bugfix: handle scientific notation of small values in Kraken checksum
• Update: calculate Kraken checksum on order books less than 10 levels deep
• Bugfix: fix occasional incorrect checksums for OKX, FTX and Bitget

0.4.2 (2022-04-17)

• Update: OKEx renamed OKX (for checksum validation)
• Feature: Add support for orderbook checksums with Bitget

0.4.1 (2021-10-12)

• Bugfix: unnecessary reference counting prevented sorted dictionaries from being deallocated
• Bugfix: setting ordering on a sorted dict before checking that it was created successfully

0.4.0 (2021-09-16)

• Feature: changes to code and setup.py to enable compiling on windows
• Feature: add from_type/to_type kwargs to the to_dict methods, allowing for type conversion when creating the dictionary

0.3.2 (2021-09-04)

• Bugfix: depth was incorrectly ignored when converting sorteddict to python dict

0.3.1 (2021-09-01)

• Bugfix: truncate and max_depth not being passed from orderbook to sorteddict object correctly
• Feature: let checksum_format kwarg be set to None

0.3.0 (2021-07-16)

• Update classifiers to indicate this projects only supports MacOS/Linux
• Bugfix: Using less than the minimum number of levels for a checksum with Kraken not raising error correctly
• Update: add del examples to test code

0.2.1 (2021-03-29)

• Bugfix: Invalid deallocation of python object

0.2.0 (2021-03-12)

• Feature: Add branch prediction hints around error handling code
• Bugfix: Fix regression from adding branch predictors
• Bugfix: Fix error corner case when iterating twice on an empty dataset
• Feature: Add contains function for membership test
• Bugfix: Fix issues around storing L3 data
• Feature: Enhance testing, add in L3 book test cases

0.1.1 (2021-02-12)

• Feature: Checksum support for orderbooks
• Feature: FTX checksum support
• Feature: Kraken checksum support
• Feature: OkEX/OKCoin checksum support
• Perf: Use CRC32 table to improve performance of checksum code

0.1.0 (2021-01-18)

• Minor: Use enums to make code more readable
• Bugfix: Add manifest file to ensure headers and changes file are included in sdist builds
• Feature: Add support for max depth and depth truncation

0.0.2 (2020-12-27)

• Bugfix: Fix sorted dictionary arg parsing
• Feature: Coverage report generation for C library
• Bugfix: Fix reference counting in index method in SortedDict
• Feature: New unit tests to improve SortedDict coverage
• Feature: Modularize files
• Feature: Add ability to set bids/asks to dictionaries via attributes or [ ]
• Docs: Update README with simple usage example

0.0.1 (2020-12-26)

• Initial Release