[xusd320]

• Update rust-toolchain to nightly-2026-02-05
• Change default log level to info in project.rs
• Update package.json deps for with-antd example
• Minor updates to analyze_trace.py

[gemini-code-assist]

Summary of Changes

Hello @xusd320, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request primarily focuses on maintenance and tooling improvements across the project. It updates the Rust toolchain to a newer nightly version and refreshes Node.js dependencies, including adding CSS preprocessor support for an example application. A major enhancement involves a substantial refactor of the Python-based trace analysis script, making it more robust and providing deeper insights into performance characteristics. Additionally, a minor adjustment to the default logging level in a Rust module aims to reduce log output verbosity.

Highlights

• Rust Toolchain Update: The Rust nightly toolchain has been updated to nightly-2026-02-05, ensuring the project uses a more recent and potentially more stable or feature-rich compiler version.
• Enhanced Trace Analysis Script: The analyze_trace.py script received a significant refactor, introducing a multi-pass analysis approach for more accurate thread work calculation, streaming JSON parsing for large files, and a more detailed performance report with improved metrics and action items.
• Logging Configuration Adjustment: The default logging level in crates/pack-napi/src/pack_api/project.rs was changed from trace to info, reducing verbosity in typical operations and focusing on more critical information.
• Node.js Dependency Updates: The package.json for the with-antd example now includes less and less-loader, and the package-lock.json has been extensively updated to reflect these changes, including version bumps for less-loader and standardization of peer dependency flags across many packages.

Changelog

• agents/tools/analyze_trace.py
  • Added detailed design decisions to the script's header comments.
  • Refactored trace analysis into three distinct passes for span pairing, non-overlapping thread work calculation, and task-level statistics.
  • Implemented streaming JSON parsing for large trace files using ijson with a fallback to json.load.
  • Updated the generated performance report to include more comprehensive metrics, assessments, and action items.
  • Introduced a helper function _load_events for flexible trace data loading.
  • Modified the script to accept an optional project_name argument.
• crates/pack-napi/src/pack_api/project.rs
  • Configured ChromeLayerBuilder to explicitly exclude arguments in tracing.
  • Changed the default tracing EnvFilter from "trace" to "info".
• examples/with-antd/package.json
  • Added less and less-loader as new development dependencies.
• package-lock.json
  • Updated less-loader version from 12.3.0 to 12.3.1.
  • Broadened the peer dependency range for @rspack/core in less-loader.
  • Standardized peer: true flags for numerous dependencies, adding it to some and removing it from others, reflecting dependency resolution changes.
• rust-toolchain.toml
  • Updated the Rust nightly channel to nightly-2026-02-05.

Activity

• The pull request was created by xusd320.
• The Rust toolchain was updated to a newer nightly version.
• The analyze_trace.py script underwent a significant refactor to improve performance analysis capabilities.
• Node.js dependencies were updated, including adding less and less-loader to the with-antd example.
• The default logging level in project.rs was adjusted.

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[gemini-code-assist]

Code Review

This pull request primarily involves dependency updates, a Rust toolchain upgrade, and a significant refactoring of the analyze_trace.py script. The script refactoring is a substantial improvement, introducing a more accurate multi-pass analysis for performance metrics and adding streaming JSON parsing to handle large files efficiently. The changes in project.rs to reduce trace log verbosity are also sensible. Overall, the changes enhance correctness, performance, and maintainability. I have one suggestion to further optimize file handling in the Python script.

[github-actions]

📊 Performance Benchmark Report (with-antd)

Utoopack Performance Report

Report ID: utoopack_performance_report_20260210_161300
Generated: 2026-02-10 16:13:00
Trace File: trace_antd.json (0.5GB, 3.18M events)
Test Project: examples/with-antd

---

Executive Summary

Key Findings

Metric	Value	Assessment
Total Wall Time	7,822.8 ms	Baseline
Total Thread Work (de-duped)	24,668.2 ms	Non-overlapping busy time
Effective Parallelism	3.2x	thread_work / wall_time
Working Threads	5	Threads with actual spans
Thread Utilization	63.1%	🆗 Average
Total Spans	1,589,423	All B/E + X events
Meaningful Spans (>= 10us)	498,805	(31.4% of total)
Tracing Noise (< 10us)	1,090,618	(68.6% of total)

Note on Thread Work: Thread work is computed by merging overlapping intervals
per thread, eliminating double-counting from nested spans. This gives the true
wall-clock busy time across all threads.

Workload Distribution by Tier

Category	Tasks	Total Time (ms)	% of Thread Work
P0: Runtime/Resolution	0	0.0	0.0%
P1: I/O & Heavy Tasks	37,833	3,479.4	14.1%
P3: Asset Pipeline	29,009	3,301.1	13.4%
P4: Bridge/Interop	0	0.0	0.0%
Other	431,963	20,762.6	84.2%

Note: Percentages may sum to >100% because task durations include nesting
while thread work is de-duplicated. This is intentional for hotspot attribution.

---

Parallelization Analysis

Thread Utilization

Metric	Value
Working Threads	5
Total Thread Work (de-duped)	24,668.2 ms
Avg Work per Thread	4,933.6 ms
Effective Parallelism	3.15x
Thread Utilization	63.1%

Assessment: With 5 working threads, achieving 3.2x parallelism indicates significant loss of potential parallelism.

---

Top 20 Tasks by Total Duration

Total (ms)	Count	Avg (us)	Max (ms)	% Work	Task Name
7,788.9	177,908	43.8	15.3	31.6%	module
3,962.5	67,581	58.6	210.8	16.1%	process module
3,413.7	34,960	97.6	210.7	13.8%	analyze ecmascript module
2,755.4	24,362	113.1	60.9	11.2%	code generation
1,726.1	56,302	30.7	11.5	7.0%	resolving
1,656.5	60,631	27.3	9.7	6.7%	internal resolving
1,402.4	14,179	98.9	43.5	5.7%	chunking
1,343.8	28,956	46.4	14.0	5.4%	precompute code generation
1,241.9	13,125	94.6	120.7	5.0%	compute async module info
1,026.5	8,030	127.8	60.5	4.2%	parse ecmascript
503.1	4,729	106.4	45.6	2.0%	compute async chunks
289.7	1,936	149.6	20.9	1.2%	generate source map
62.3	129	483.3	19.5	0.3%	make production chunks
61.1	557	109.7	15.0	0.2%	compute binding usage info
59.2	1,858	31.8	11.3	0.2%	collect mergeable modules
56.7	2,165	26.2	0.5	0.2%	read file
33.4	14	2388.0	10.7	0.1%	apply effects
32.8	5	6556.2	19.5	0.1%	compute merged modules
32.2	566	56.9	4.5	0.1%	async reference
29.9	13	2300.8	10.6	0.1%	write file

---

Deep Dive by Tier

Tier 1: Runtime & Resolution (P0)

Focus: Task scheduling and dependency resolution.

Metric	Value	Status
Total Scheduling Time	0.0 ms	✅ Normal
Resolution Hotspots	0 distinct task types	Check Top Tasks

Potential P0 Issues:

• Thread utilization at 63.1% suggests critical path serialization or lock contention.
• 1,090,618 spans < 10us (68.6%) contribute to scheduler pressure.

Tier 2: Physical & Resource Barriers (P1)

Focus: Hardware utilization, I/O, and heavy monoliths.

Metric	Value	Status
I/O Work (Estimated)	3,479.4 ms	✅ Healthy
Large Tasks (> 100ms)	5	Minimal

Tier 3: Architecture & Asset Pipeline (P2-P3)

Focus: Global state and transformation pipeline.

Metric	Value	Status
Asset Processing (P3)	3,301.1 ms	13.4% of work
Bridge Overhead (P4)	0.0 ms	✅ Low

---

Duration Distribution

Range	Count	Percentage
< 10us (noise)	1,090,618	68.6%
10us - 100us	474,552	29.9%
100us - 1ms	20,373	1.3%
1ms - 10ms	3,799	0.2%
10ms - 100ms	76	0.0%
> 100ms	5	0.0%

---

Diagnostic Signal Summary

Signal	Status	Finding
Tracing Noise (P0)	⚠️ Significant	68.6% of spans < 10us
Thread Utilization (P0)	🆗 Average	63.1% utilization
Heavy Monoliths (P1)	✅ Minimal	5 tasks > 100ms
Asset Pipeline (P3)	Review	3,301.1 ms total
Bridge/Interop (P4)	Low	0.0 ms total

---

Action Items (P0-P4)

1. [P0] Profile lock contention to address 36% lost parallelism
2. [P1] Breakdown heavy monolith tasks (>100ms) to improve granularity
3. [P1] Review I/O patterns for potential batching opportunities
4. [P3] Optimize asset transformation pipeline hot-spots
5. [P4] Reduce "chatty" bridge operations if interop overhead is significant

---

Report generated by Utoopack Performance Analysis Agent on 2026-02-10
Following: Utoopack Performance Analysis Agent Protocol