⚡ Bolt: optimize YAML line scanner colon check & zero-alloc key tracking

Closed
JU
7d ago
+43-43

User description

💡 What: Added a fast-path !body.contains(':') pre-test to mapping_colon_index in crates/core/src/config/tun.rs to skip state machine character iteration for non-mapping lines. Replaced HashSet with Vec for small key sets in BlockFrame and FlowContentScan, eliminating heap allocations per sequence item.

🎯 Why: High-frequency scalar YAML extraction routines (extract_mode_from_yaml, extract_secret_from_yaml, extract_tun_enabled_from_yaml) scan thousands of lines across proxy nodes and rules, repeatedly running quote-tracking loops on lines without colons and allocating HashSets for short-lived key frames.

📊 Impact: Reduces line scanning latency and eliminates heap allocations during YAML scalar extractions over large config files.

🔬 Measurement: Verified with cargo bench -p zephyr-core --bench core_bench -- tun_extract and cargo test -p zephyr-core (263 tests passed).

PR created automatically by Jules for task 15749473054294256136 started by @Juwan-Hwang

CodeAnt-AI Description

Speed up YAML configuration value scanning

What Changed

  • Lines without mapping separators are skipped sooner during YAML value scans.
  • Tracking keys and anchors during scans uses fewer temporary allocations.

Impact

✅ Faster scalar reads from YAML configs
✅ Fewer allocations during YAML scans
✅ Faster TUN setting checks

💡 Usage Guide

Checking Your Pull Request

Every time you make a pull request, our system automatically looks through it. We check for security issues, mistakes in how you're setting up your infrastructure, and common code problems. We do this to make sure your changes are solid and won't cause any trouble later.

Talking to CodeAnt AI

Got a question or need a hand with something in your pull request? You can easily get in touch with CodeAnt AI right here. Just type the following in a comment on your pull request, and replace "Your question here" with whatever you want to ask:

@codeant-ai ask: Your question here

This lets you have a chat with CodeAnt AI about your pull request, making it easier to understand and improve your code.

Example

@codeant-ai ask: Can you suggest a safer alternative to storing this secret?

Preserve Org Learnings with CodeAnt

You can record team preferences so CodeAnt AI applies them in future reviews. Reply directly to the specific CodeAnt AI suggestion (in the same thread) and replace "Your feedback here" with your input:

@codeant-ai: Your feedback here

This helps CodeAnt AI learn and adapt to your team's coding style and standards.

Example

@codeant-ai: Do not flag unused imports.

Retrigger review

Ask CodeAnt AI to review the PR again, by typing:

@codeant-ai: review

Check Your Repository Health

To analyze the health of your code repository, visit our dashboard at https://app.codeant.ai. This tool helps you identify potential issues and areas for improvement in your codebase, ensuring your repository maintains high standards of code health.