Synergistic effects of multilingual programming
Quadratic's support for Python, SQL, and Rust creates a unique combination of language strengths: Python as the primary scripting language for calling rich data science libraries (e.g., Pandas, NumPy); SQL for efficient data querying operations; and Rust for system-level, high-performance computational capabilities.
For the technical implementation, the tool uses a sandbox environment to execute the code, which ensures security while maintaining real-time interaction with the spreadsheet data. Users can write Python functions directly in the cell for data conversion, connect to external databases via SQL statements, or even write custom analysis algorithms using Rust. For example, in a stock analysis scenario, an analyst can: use SQL to get real-time market data, Python to calculate technical indicators, Rust to implement high-frequency trading strategy backtesting, and finally use the built-in visualization tools to generate charts.
This multi-language integration breaks through the formulaic limitations of traditional spreadsheets, allowing complex algorithms and customized business logic to be implemented directly in the form environment, increasing data processing power by several orders of magnitude.
This answer comes from the articleQuadratic: an online data analysis form that integrates AI dialog and code executionThe
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