unicorn-binance-local-depth-cache 2.12.0

A Python SDK for accessing and managing multiple local Binance order books with Python in a simple, fast, flexible, robust and fully featured way. .

UNICORN Binance Local Depth Cache

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A Python SDK for accessing and managing multiple local Binance order books with Python in a simple, fast, flexible, robust and fully functional way.

The organization of the DepthCache takes place in the same asyncio loop as the reception of the websocket data. The full stack of the UBS modules (REST, WebSocket and DepthCache) can be downloaded and installed by PyPi and Anaconda as a Python C extension for maximum performance.

Part of 'UNICORN Binance Suite'.

Using a DepthCache

Create a local DepthCache for Binance with just 3 lines of code

from unicorn_binance_local_depth_cache import BinanceLocalDepthCacheManager, DepthCacheOutOfSync

ubldc = BinanceLocalDepthCacheManager(exchange="binance.com", depth_cache_update_interval=100)
ubldc.create_depthcache("BTCUSDT")

Get the asks and bids

To obtain the complete order book

asks = ubldc.get_asks("BTCUSDT")
bids = ubldc.get_bids("BTCUSDT")

Get the first X elements

asks = ubldc.get_asks("BTCUSDT", limit_count=10)
bids = ubldc.get_bids("BTCUSDT", limit_count=10)

Retain the elements until volume X has been exceeded

asks = ubldc.get_asks("BTCUSDT", threshold_volume=300000)
bids = ubldc.get_bids("BTCUSDT", threshold_volume=300000)

Catch an exception, if the DepthCache is out of sync while accessing its data

try:
    asks = ubldc.get_asks(market="BTCUSDT", limit_count=5, threshold_volume=300000)
    bids = ubldc.get_bids(market="BTCUSDT", limit_count=5, threshold_volume=300000)
except DepthCacheOutOfSync:
    asks = "Out of sync!"
    bids = "Out of sync!"

Stop and delete a DepthCache:

ubldc.stop_depthcache("BTCUSDT")

Stop ubldc after usage to avoid memory leaks

When you instantiate UBLDC with with, ubldc.stop_manager() is automatically executed upon exiting the with-block.

with BinanceWebSocketApiManager() as ubldc:
    ubldc.create_depthcache("BTCUSDT")

Without with, you must explicitly execute ubldc.stop_manager() yourself.

ubldc.stop_manager()

Discover more possibilities.

Connect to a UNICORN Binance DepthCache Cluster

The UNICORN Binance DepthCache Cluster (UBDCC) manages hundreds of DepthCaches with load balancing, automatic failover and self-healing state. It runs locally on a single machine (pip install ubdcc) or scales across a Kubernetes cluster. Access is via REST API from any language — Python users can use the built-in cluster module shown below.

Synchronous

from unicorn_binance_local_depth_cache import BinanceLocalDepthCacheManager, DepthCacheClusterNotReachableError

def main():
    ubldc.cluster.create_depthcaches(exchange="binance.com", markets=['BTCUSDT', 'ETHUSDT'], desired_quantity=2)
    while ubldc.is_stop_request() is False:
        print(ubldc.cluster.get_asks(exchange="binance.com", market='BTCUSDT', limit_count=2))
        
try:
    with BinanceLocalDepthCacheManager(exchange="binance.com", ubdcc_address="127.0.0.1", ubdcc_port=42081) as ubldc:
        try:
            main()
        except KeyboardInterrupt:
            print("\r\nGracefully stopping ...")
except DepthCacheClusterNotReachableError as error_msg:
    print(f"ERROR: {error_msg}")

Asynchronous

from unicorn_binance_local_depth_cache import BinanceLocalDepthCacheManager, DepthCacheClusterNotReachableError

async def main():
    await ubldc.cluster.create_depthcaches_async(exchange="binance.com", 
                                                  markets=['BTCUSDT', 'ETHUSDT'], 
                                                  desired_quantity=2)
    while ubldc.is_stop_request() is False:
        print(await ubldc.cluster.get_asks_async(exchange="binance.com", market='BTCUSDT', limit_count=2))
        
try:
    with BinanceLocalDepthCacheManager(exchange="binance.com", ubdcc_address="127.0.0.1", ubdcc_port=42081) as ubldc:
        try:
            asyncio.run(main())
        except KeyboardInterrupt:
            print("\r\nGracefully stopping ...")
except DepthCacheClusterNotReachableError as error_msg:
    print(f"ERROR: {error_msg}")

Try the cluster examples!

Discover more cluster possibilities ...

Description

The Python package UNICORN Binance Local Depth Cache provides local order books for the Binance Exchanges Binance (+Testnet), Binance Futures (+Testnet), Binance European Options (+Testnet), Binance US and TRBinance.

The algorithm of the DepthCache management was designed according to these instructions:

Since, according to Binance's predefined algorithm, all levels > 1000 would be orphaned and remain forever between valid levels , UBLDC removes them as soon as they exceed the thousandth position.

• Binance Spot: "How to manage a local order book correctly"
• Binance Futures: "How to manage a local order book correctly"
• Binance European Options: "How to manage a local order book correctly"
• Binance US: "Managing a Local Order Book"
• TRBinance: "Diff. Depth Stream"

With create_depthcache()` the DepthCache is started and initialized, i.e. for each DepthCache that is to be created, a separate asyncio coroutine is inserted into the event loop of the stream. As soon as at least one depth update is received via websocket, a REST snapshot is downloaded and the depth updates are applied to it so that it is synchronized in real time. As soon as once this is done, the status of the cache get set to "synchronous".

Data in the DepthCache can be accessed with 'get_asks()' and 'get_bids()'. If the state of the DepthCache is not synchronous during access, the exception 'DepthCacheOutOfSync' is thrown.

The DepthCache will immediately start an automatic re-initialization if a gap in the UpdateID`s is detected (missing update event) or if the websocket connection is interrupted. As soon as this happens the state of the DepthCache is set to "out of sync" and when accessing the cache the exception 'DepthCacheOutOfSync' is thrown.

Why a local DepthCache?

A local DepthCache is the fastest way to access the current order book depth at any time while transferring as little data as necessary. A REST snapshot takes a lot of time and the amount of data that is transferred is relatively large. Continuous full transmission of the order book via websocket is faster, but the amount of data is huge. A local depth_cache is initialized once with a REST snapshot and then handles Diff. Depth updates applied by the websocket connection. By transferring a small amount of data (only the changes), a local depth_cache is kept in sync in real time and also allows extremely fast (local) access to the data without exceeding the Binance request weight limits.

What are the benefits of the UNICORN Binance Local Depth Cache?

• Always know if the cache is in sync! If the DepthCache is out of sync, the exception 'DepthCacheOutOfSync' is thrown or ask with is_depth_cache_synchronized().

• If a depth cache is out of sync it gets refreshed automatically within a few seconds.

• 100% Websocket auto-reconnect!

• Supported Exchanges

Exchange	Exchange string
Binance	binance.com
Binance Testnet	binance.com-testnet
Binance USD-M Futures	binance.com-futures
Binance USD-M Futures Testnet	binance.com-futures-testnet
Binance European Options	binance.com-vanilla-options
Binance European Options Testnet	binance.com-vanilla-options-testnet
Binance US	binance.us
TRBinance	trbinance.com ¹

¹ TRBinance requires an API key even for public REST endpoints (e.g. order book snapshots). Pass api_key and api_secret to BinanceRestApiManager when using exchange="trbinance.com".

• Create multiple depth caches within a single object instance.

• Each DepthCache is managed in an asyncio coroutine.

• Start or stop multiple caches with just one command create_depthcache() or stop_depthcache().

• Control websocket out of sync detection with websocket_ping_interval, websocket_ping_timeout and websocket_close_timeout

• Powered by UNICORN Binance REST API and UNICORN Binance WebSocket API.

• Available as a package via pip and conda as precompiled C extension with stub files for improved Intellisense functions and source code for easier debugging of the source code. To the installation.

If you like the project, please it on GitHub!

Installation and Upgrade

The module requires Python 3.8 and runs smoothly up to and including Python 3.13.

There is no conda support until the migration to conda-forge.

For the PyPy interpreter we offer packages only from Python version 3.9 and higher.

Anaconda packages are available from Python version 3.8 and higher, but only in the latest version!

The current dependencies are listed here.

If you run into errors during the installation take a look here.

Packages are created automatically with GitHub Actions

When a new release is to be created, we start two GitHubActions:

• Build and Publish Anaconda
• Build and Publish GH+PyPi

Both start virtual Windows/Linux/Mac servers provided by GitHub in the cloud with preconfigured environments and create the respective compilations and stub files, pack them into wheels and conda packages and then publish them on GitHub, PYPI and Anaconda. This is a transparent method that makes it possible to trace the source code behind a compilation.

A Cython binary, PyPy or source code based CPython wheel of the latest version with pip from PyPI

Our Cython and PyPy Wheels are available on PyPI, these wheels offer significant advantages for Python developers:

• Performance Boost with Cython Wheels: Cython is a programming language that supplements Python with static typing and C-level performance. By compiling Python code into C, Cython Wheels can significantly enhance the execution speed of Python code, especially in computationally intensive tasks. This means faster runtimes and more efficient processing for users of our package.

• PyPy Wheels for Enhanced Efficiency: PyPy is an alternative Python interpreter known for its speed and efficiency. It uses Just-In-Time (JIT) compilation, which can dramatically improve the performance of Python code. Our PyPy Wheels are tailored for compatibility with PyPy, allowing users to leverage this speed advantage seamlessly.

Both Cython and PyPy Wheels on PyPI make the installation process simpler and more straightforward. They ensure that you get the optimized version of our package with minimal setup, allowing you to focus on development rather than configuration.

Installation

pip install unicorn-binance-local-depth-cache

Update

pip install unicorn-binance-local-depth-cache --upgrade

A Conda Package of the latest version with conda from Anaconda

There is no conda support until the migration to conda-forge.

The unicorn-binance-local-depth-cache package is also available as a Cython version for the linux-64, osx-64 and win-64 architectures with Conda through the lucit channel.

For optimal compatibility and performance, it is recommended to source the necessary dependencies from the conda-forge channel.

Installation

There is no conda support until the migration to conda-forge.

conda config --add channels conda-forge
conda config --add channels lucit
conda install -c lucit unicorn-binance-local-depth-cache

Update

There is no conda support until the migration to conda-forge.

conda update -c lucit unicorn-binance-local-depth-cache

From source of the latest release with PIP from GitHub

Linux, macOS, ...

Run in bash:

pip install https://github.com/oliver-zehentleitner/unicorn-binance-local-depth-cache/archive/$(curl -s https://api.github.com/repos/oliver-zehentleitner/unicorn-binance-local-depth-cache/releases/latest | grep -oP '"tag_name": "\K(.*)(?=")').tar.gz --upgrade

Windows

Use the below command with the version (such as 2.12.0) you determined here:

pip install https://github.com/oliver-zehentleitner/unicorn-binance-local-depth-cache/archive/2.12.0.tar.gz --upgrade

From the latest source (dev-stage) with PIP from GitHub

This is not a release version and can not be considered to be stable!

pip install https://github.com/oliver-zehentleitner/unicorn-binance-local-depth-cache/tarball/master --upgrade

Change Log

https://oliver-zehentleitner.github.io/unicorn-binance-local-depth-cache/changelog.html

Documentation

• General
• Modules

Examples

• Look here!

Project Homepage

https://github.com/oliver-zehentleitner/unicorn-binance-local-depth-cache

Wiki

https://github.com/oliver-zehentleitner/unicorn-binance-local-depth-cache/wiki

Social

• Discussions
• https://t.me/unicorndevs
• https://dev.binance.vision

Receive Notifications

To receive notifications on available updates you can the repository on GitHub, write your own script with using is_update_available().

To receive news (like inspection windows/maintenance) about the Binance API`s subscribe to their telegram groups:

• https://t.me/binance_api_announcements
• https://t.me/binance_api_english
• https://t.me/Binance_USA
• https://t.me/TRBinanceTR
• https://t.me/BinanceExchange

How to report Bugs or suggest Improvements?

List of planned features - click if you need one of them or suggest a new feature!

Before you report a bug, try the latest release. If the issue still exists, provide the error trace, OS and Python version and explain how to reproduce the error. A demo script is appreciated.

If you dont find an issue related to your topic, please open a new issue!

Report a security bug!

Contributing

UNICORN Binance Local Depth Cache is an open source project which welcomes contributions which can be anything from simple documentation fixes and reporting dead links to new features. To contribute follow this guide.

Contributors

We open source!

Disclaimer

This project is for informational purposes only. You should not construe this information or any other material as legal, tax, investment, financial or other advice. Nothing contained herein constitutes a solicitation, recommendation, endorsement or offer by us or any third party provider to buy or sell any securities or other financial instruments in this or any other jurisdiction in which such solicitation or offer would be unlawful under the securities laws of such jurisdiction.

If you intend to use real money, use it at your own risk!

Under no circumstances will we be responsible or liable for any claims, damages, losses, expenses, costs or liabilities of any kind, including but not limited to direct or indirect damages for loss of profits.