💡 Summary
Shioaji is a comprehensive trading API for accessing Taiwan's financial markets using Python.
🎯 Target Audience
🤖 AI Roast: “The README suggests network access for trading operations, which poses risks like unauthorized access and data leaks. Implementing API key management and secure storage practices c”
The README suggests network access for trading operations, which poses risks like unauthorized access and data leaks. Implementing API key management and secure storage practices can mitigate these risks.
Shioaji


Shioaji is a trading API provided by Sinopac that offers a comprehensive and user-friendly platform for accessing the Taiwan financial markets. With Shioaji, you can trade a variety of financial instruments including stocks, futures, and options using your favorite Python packages such as numpy, scipy, pandas, pytorch, or tensorflow to build your own custom trading models. The platform is easy to use and intuitive, with advanced charting tools, real-time market data, and a customizable interface that allows you to tailor your trading experience to your specific needs. Shioaji is fast and efficient, with a high-performance core implemented in C++ and using FPGA event broker technology, and it is the first Python trading API in Taiwan that is compatible with Linux and Mac, making it a truly cross-platform solution. Whether you are a beginner looking to get started in the world of trading or an experienced trader looking for a more powerful platform, Shioaji has something to offer. Sign up for a free account today and start trading with confidence.
✨ First Taiwan trading API with AI coding agent skill support — Claude Code & Codex CLI
AI Coding Agent Skills
Shioaji is the first Taiwan trading API with AI coding agent skill support. Get AI-assisted guidance on using the Shioaji API.
Claude Code
claude plugin marketplace add Sinotrade/Shioaji claude plugin install shioaji
OpenAI Codex CLI
In a Codex session, use the skill-installer:
$skill-installer install shioaji from Sinotrade/Shioaji --path skills/shioaji
Installation
Binaries
simple using pip to install
pip install shioaji
update shioaji with
pip install -U shioaji
uv
using uv to install
uv add shioaji
install speed version
uv add shioaji --extra speed
Docker Image
simple run with interactive mode in docker
docker run -it sinotrade/shioaji:latest
run with jupyter lab or notebook
docker run -p 8888:8888 sinotrade/shioaji:jupyter
Quickstarts
Initialization
import shioaji as sj api = sj.Shioaji() accounts = api.login("YOUR_TOKEN", "YOUR_SECRET_KEY") api.activate_ca( ca_path="/c/your/ca/path/Sinopac.pfx", ca_passwd="YOUR_CA_PASSWORD", )
Just import our API library like other popular python library and new the instance to start using our API. Login your account and activate the certification then you can start placing order.
Streaming Market Data
api.quote.subscribe(api.Contracts.Stocks["2330"], quote_type="tick") api.quote.subscribe(api.Contracts.Stocks["2330"], quote_type="bidask") api.quote.subscribe(api.Contracts.Futures["TXFC0"], quote_type="tick")
Subscribe the real time market data. Simplely pass contract into quote subscribe function and give the quote type will receive the streaming data.
Place Order
contract = api.Contracts.Stocks["2890"] order = api.Order( price=9.6, quantity=1, action="Buy", price_type="LMT", order_type="ROD", order_lot="Common", account=api.stock_account, ) # or order = api.Order( price=9.6, quantity=1, action=sj.constant.Action.Buy, price_type=sj.constant.StockPriceType.LMT, order_type=sj.constant.OrderType.ROD, order_lot=sj.constant.StockOrderLot.Common, account=api.stock_account, ) trade = api.place_order(contract, order)
Like the above subscribing market data using the contract, then need to define the order. Pass them into place_order function, then it will return the trade that describe the status of your order.
Conclusion
This quickstart demonstrates how easy to use our package for native Python users. Unlike many other trading API is hard for Python developer. We focus on making more pythonic trading API for our users.
More usage detail on document.
Communication
Releases and Contributing
Shioaji has a 14 day release cycle. See the release change log. Please let us know if you encounter a bug by filing an issue.
We appreciate all suggestions. If you have any idea want us to implement, please discuss with us in gitter.
The Team
Shioaji is currently maintained by Sally, Yvictor, CC.Chiao and Po Chien Yang with major contributions.
Pros
- User-friendly interface for Python developers.
- Supports a wide range of financial instruments.
- Real-time market data streaming.
- Cross-platform compatibility.
Cons
- Limited to Taiwan's financial markets.
- May require additional setup for advanced features.
- Documentation could be more detailed.
- Dependency on external libraries.
Related Skills
pytorch
S“It's the Swiss Army knife of deep learning, but good luck figuring out which of the 47 installation methods is the one that won't break your system.”
agno
S“It promises to be the Kubernetes for agents, but let's see if developers have the patience to learn yet another orchestration layer.”
nuxt-skills
S“It's essentially a well-organized cheat sheet that turns your AI assistant into a Nuxt framework parrot.”
Disclaimer: This content is sourced from GitHub open source projects for display and rating purposes only.
Copyright belongs to the original author Sinotrade.
