UnicornFy
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A Python SDK by LUCIT to convert received raw data from crypto exchange API endpoints into well-formed python dictionaries.
Part of 'UNICORN Binance Suite'.
Get help with the integration of the UNICORN Binance Suite modules!
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', '0.14.2']}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
it on
GitHub!
Installation and Upgrade
The module requires Python 3.7 and runs smoothly up to and including Python 3.12.
Anaconda packages are available from Python version 3.8 and higher, but only in the latest version!
For the PyPy interpreter we offer packages only from Python version 3.9 and higher.
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:
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.
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-fyUpdate
pip install unicorn-fy --upgradeA Conda Package of the latest version with conda from Anaconda
The unicorn-fy 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
conda config --add channels conda-forge
conda config --add channels lucit
conda install -c lucit unicorn-fyUpdate
conda update -c lucit unicorn-fyFrom source of the latest release with PIP from GitHub
Linux, macOS, ...
Run in bash:
pip install https://github.com/LUCIT-Systems-and-Development/unicorn-fy/archive/$(curl -s https://api.github.com/repos/lucit-systems-and-development/unicorn-fy/releases/latest | grep -oP '"tag_name": "\K(.*)(?=")').tar.gz --upgradeWindows
Use the below command with the version (such as 0.14.2) you determined here:
pip install https://github.com/LUCIT-Systems-and-Development/unicorn-fy/archive/0.14.2.tar.gz --upgradeFrom 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/LUCIT-Systems-and-Development/unicorn-fy/tarball/master --upgradeConda 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://unicorn-fy.docs.lucit.tech/changelog.html
Documentation
Examples
Project Homepage
https://www.lucit.tech/unicorn-fy.html
Wiki
https://github.com/LUCIT-Systems-and-Development/unicorn-fy/wiki
Social
Receive Notifications
To receive notifications on available updates you can
the repository on GitHub, write your
own script
with using
is_update_available()
or you use the
monitoring API service.
Follow us on GitHub, Medium, YouTube, LinkedIn, X or Facebook!
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 don't find an issue related to your topic, please open a new issue: https://github.com/LUCIT-Systems-and-Development/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 
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.
Do you have any questions? We will be happy to answer them in our chat - usually you will receive an answer within a few minutes during our opening hours.