performance-streaming

name	performance-streaming
description	Optimize high-throughput visualization updates across server broadcast and frontend batching paths

Skill: Performance for Streaming Updates

When to Use

Use this skill when large update volume causes lag, dropped frames, or heavy CPU/network use.

Core Workflow

1. Profile payload size and update frequency from Python client sends.
2. Prefer incremental updates/patches over full pane re-send.
3. Keep server broadcast fanout minimal and environment-scoped.
4. Preserve frontend batching/coalescing behavior for incoming pane updates.
5. Avoid unnecessary pane re-renders by preserving pane identity and memoization assumptions.

Guardrails

• Do not trade correctness for speed in patch generation.
• Keep compare mode and normal mode both stable under load.
• Validate behavior in both WebSocket and polling modes.

Documentation

• Skill reference
• py/visdom/utils/server_utils.py
• py/visdom/server/handlers/socket_handlers.py
• js/main.js
• js/api/ApiProvider.js
• AGENTS.md
• CONTRIBUTING.md

Assets

• See assets/README.md and store templates/resources in assets/.

Tests

• Follow the default flow in references/TESTS.md.