UnicornFy
Supported Exchanges | Installation | Change Log | Documentation | Examples | Wiki | Social | Notifications | Bugs | Contributing | Disclaimer
Normalizes raw responses from crypto exchange APIs (Binance & co.) into consistent, cleanly-typed Python dictionaries. A transformation layer that makes exchange data interchangeable instead of exchange-specific.
Part of 'UNICORN Binance Suite'.
import unicorn_fy
received_stream_data_json = {"stream": "btcusdt@trade",
"data": {"e": "trade",
"E": 1556876873656,
"s": "BTCUSDT",
"t": 117727701,
"p": "5786.76000000",
"q": "0.03200500",
"b": 341831847,
"a": 341831876,
"T": 1556876873648,
"m": True,
"M": True}}
ufy = unicorn_fy.UnicornFy()
unicorn_fied_stream_data = ufy.binance_com_websocket(received_stream_data_json)
print(unicorn_fied_stream_data)
Output:
{'stream_type': 'btcusdt@trade',
'event_type': 'trade',
'event_time': 1556876873656,
'symbol': 'BTCUSDT',
'trade_id': 117727701,
'price': '5786.76000000',
'quantity': '0.03200500',
'buyer_order_id': 341831847,
'seller_order_id': 341831876,
'trade_time': 1556876873648,
'is_market_maker': True,
'ignore': True,
'unicorn_fied': ['binance', '0.17.2']}
This lib is integrated into
UNICORN Binance WebSocket API
and can be activated by setting parameter
output_default of BinanceWebSocketApiManager() to UnicornFy
or for specific streams with the parameter
output of create_stream() to UnicornFy.
Get the right logger:
logging.getLogger("unicorn_fy")
What are the benefits of UnicornFy
Supported exchanges:
Websockets
REST
None
-
Available as a package via
pipandcondaas precompiled C extension with stub files for improved Intellisense functions and source code for easier debugging of the source code. To the installation. -
Excessively tested on Linux, Mac and Windows
If you like the project, please
Installation and Upgrade
The module requires Python 3.9 and runs smoothly up to and including Python 3.14.
PyPy wheels are available for all supported Python versions.
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 created, the Build and Publish GH+PyPi workflow spins up virtual Windows/Linux/Mac runners, compiles the Cython extensions, builds the wheels and publishes them on GitHub and PyPI. The conda-forge feedstock conda-forge/unicorn-fy-feedstock picks up the new PyPI release automatically and builds the Conda packages on its own infrastructure. 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.
On Raspberry Pi and other architectures for which there are no pre-compiled versions, the package can still be installed with PIP. PIP then compiles the package locally on the target system during installation. Please be patient, this may take some time!
Installation
pip install unicorn-fy
Update
pip install unicorn-fy --upgrade
conda
conda install -c conda-forge unicorn-fy
From source of the latest release with PIP from GitHub
Linux, macOS, ...
Run in bash:
pip install https://github.com/oliver-zehentleitner/unicorn-fy/archive/$(curl -s https://api.github.com/repos/oliver-zehentleitner/unicorn-fy/releases/latest | grep -oP '"tag_name": "\K(.*)(?=")').tar.gz --upgrade
Windows
Use the below command with the version (such as 0.17.2) you determined here:
pip install https://github.com/oliver-zehentleitner/unicorn-fy/archive/0.17.2.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-fy/tarball/master --upgrade
Conda environment, Virtualenv or plain Python
Download the latest release or the current master branch and use:
- ./environment.yml
- ./meta.yaml
- ./pyproject.toml
- ./requirements.txt
- ./setup.py
Change Log
https://oliver-zehentleitner.github.io/unicorn-fy/changelog.html
Documentation
Examples
Project Homepage
https://github.com/oliver-zehentleitner/unicorn-fy
Wiki
https://github.com/oliver-zehentleitner/unicorn-fy/wiki
Social
Receive Notifications
To receive notifications on available updates you can
is_update_available()
or you use the
monitoring API service.
How to report Bugs or suggest Improvements?
List of planned features -
click 
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 don't find an issue related to your topic, please open a new issue: https://github.com/oliver-zehentleitner/unicorn-fy/issues
Contributing
UnicornFy 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 
AI Integration
This project provides a llms.txt file for AI tools (ChatGPT, Claude, Copilot, etc.) with structured
usage instructions, code examples and module routing.
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.
1 maintainer
Release files for unicorn-fy 0.17.2
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twine/6.1.0 CPython/3.13.12
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Transparency logRelease files / unicorn_fy-0.17.2-cp39-cp39-macosx_10_9_universal2.whl
| Download URL | unicorn_fy-0.17.2-cp39-cp39-macosx_10_9_universal2.whl |
|---|---|
| Size | 539.6 kB |
| Tags | CPython 3.9 macOS 10.9+ universal2 (ARM64, x86-64) |
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SHA-256 checksum How to use checksums |
27f9a08b1c00968df7a79efd3bb5d199eb680b724ed046a64a94cb815bcbd2ba
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083f97d1bf6dd32310dc9dd49f30ccc2edaa74b039788e516a5c563ff89eff0c
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Yes |
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twine/6.1.0 CPython/3.13.12
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