Practical overview
When it fits
Use it when you want notebook-based examples to learn strategy development and backtesting before considering the SDK's separately described live-execution and vault-management capabilities.
Who it is for
- Developers learning to build and evaluate algorithmic trading strategies.
- Python and data-science practitioners exploring DEX, lending-market or portfolio strategy examples.
Documented uses
- Study example notebooks for price- and indicator-based strategy backtests.
- Compare strategy examples using decentralised-exchange and Binance market data.
- Explore multi-asset portfolio construction and DeFi yield optimisation examples.
Requirements & limits
- The README lists a GitHub account, Python scripting, Pandas, Jupyter Notebook, and basic chart and technical-indicator knowledge as prerequisites.
- GitHub Codespaces offers the documented browser-based route for initial tests without additional software, but is described as slower.
- Local development options include Visual Studio Code, dev containers, PyCharm and other Python editors; some local routes are described as requiring more expertise.
- Repository metadata identifies the project as open source, while no license is listed.
Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.
Choose a development environment for the strategy notebooks
Prepare to work with the repository’s strategy examples in GitHub Codespaces or a local editor.
Before you start
- A GitHub user account
- Basic Python and data-science knowledge, including Python scripting, Pandas, and Jupyter Notebook
- Basic algorithmic-trading knowledge, including price charts, price action, and technical indicators
Steps
Choose GitHub Codespaces to work in a browser; the README says no additional software is needed for first tests there.
Alternatively, choose a local setup: Visual Studio Code Dev Containers, Visual Studio Code, PyCharm, or another Python editor.
Use the repository’s example backtest notebooks as starting points for strategy development and backtesting.
Expected outcome
A selected environment and a set of example notebooks to use as starting points for strategy work.
Guide limitations
- Codespaces is described as suitable for learning but slow.
- The local Visual Studio Code, PyCharm, and other-editor options are described as faster but requiring more expertise; the other-editor option calls for senior Python expertise.
- The available setup guidance does not document the detailed steps for launching or running a notebook.
Sources & review
Source record details
- Source availability
- Active
- Sources checked
- 16 October 2026
- Original website title
- tradingstrategy-ai/getting-started · Official homepage title · retained in its source language