Similar requests
How are you using Legend?
Legend Studio
What problems are you trying to solve?
I have been analyzing the Legend architecture and noticed a gap in high-frequency data visualization. Currently, modelers can define complex data structures, but they lack a native way to visualize streaming data (60fps+) without exporting it to external tools. Standard grids struggle with large, high-velocity datasets.
Describe the solution you would like to see implemented
I propose integrating Perspective (perspective-python) directly into the Legend ecosystem. This would enable a "Live Preview" kernel where users can pipe Legend execution results directly into a high-performance analytics view.
Proof of Concept: I have built a prototype simulating a Legend Execution Feed rendering real-time updates inside a Perspective widget.
GSoC 2026 Proposal: I am looking to develop this integration as a GSoC 2026 project. I would love to discuss the architectural fit with the maintainers.
Describe alternatives you have considered
Currently, users often export data to CSV/Excel for analysis, which loses real-time capabilities. Using standard HTML/JS tables is another alternative, but they lack the performance required for high-frequency financial data.
Documentation, Design, Adoption, Migration Strategy
I will provide a full architectural design document (RFC) as part of the GSoC proposal phase, detailing the widget integration and data piping strategy.
Adoption Plan: Since this introduces a new visualization kernel, it can be released as an experimental feature flag ("Beta View") alongside the existing grid to ensure no disruption to current workflows.
Documentation: I will update the Legend Studio documentation to include a guide on "Streaming Data Visualization" and provide example scripts for connecting Python data feeds to the new grid.
Contribution
Similar requests
How are you using Legend?
Legend Studio
What problems are you trying to solve?
I have been analyzing the Legend architecture and noticed a gap in high-frequency data visualization. Currently, modelers can define complex data structures, but they lack a native way to visualize streaming data (60fps+) without exporting it to external tools. Standard grids struggle with large, high-velocity datasets.
Describe the solution you would like to see implemented
I propose integrating Perspective (perspective-python) directly into the Legend ecosystem. This would enable a "Live Preview" kernel where users can pipe Legend execution results directly into a high-performance analytics view.
Proof of Concept: I have built a prototype simulating a Legend Execution Feed rendering real-time updates inside a Perspective widget.
GSoC 2026 Proposal: I am looking to develop this integration as a GSoC 2026 project. I would love to discuss the architectural fit with the maintainers.
Describe alternatives you have considered
Currently, users often export data to CSV/Excel for analysis, which loses real-time capabilities. Using standard HTML/JS tables is another alternative, but they lack the performance required for high-frequency financial data.
Documentation, Design, Adoption, Migration Strategy
I will provide a full architectural design document (RFC) as part of the GSoC proposal phase, detailing the widget integration and data piping strategy.
Adoption Plan: Since this introduces a new visualization kernel, it can be released as an experimental feature flag ("Beta View") alongside the existing grid to ensure no disruption to current workflows.
Documentation: I will update the Legend Studio documentation to include a guide on "Streaming Data Visualization" and provide example scripts for connecting Python data feeds to the new grid.
Contribution