复制下面这句话,粘贴给 Claude Code、Codex、Cursor 等 AI 编程工具,它会读取安装说明并在你确认后完成安装。
请阅读 https://ai.atlankj.com/install/asset/gh-native-app-performance-65fb0396f8e1 ,按照其中的说明把「native-app-performance」安装到你(当前 AI 工具)中。执行前先告诉我将运行的命令和写入的位置,等我确认。
查看 AI 将读取的安装说明正在读取 GitHub 原文…
内容来自 GitHub 原始文件,由原作者维护。在 GitHub 查看
Goal: record Time Profiler via xctrace, extract samples, symbolicate, and propose hotspots without opening Instruments.
# Start app yourself, then attach
xcrun xctrace record --template 'Time Profiler' --time-limit 90s --output /tmp/App.trace --attach <pid>
xcrun xctrace record --template 'Time Profiler' --time-limit 90s --output /tmp/App.trace --launch -- /path/App.app/Contents/MacOS/App
scripts/extract_time_samples.py --trace /tmp/App.trace --output /tmp/time-sample.xml
# While app is running
vmmap <pid> | rg -m1 "__TEXT" -n
scripts/top_hotspots.py --samples /tmp/time-sample.xml \
--binary /path/App.app/Contents/MacOS/App \
--load-address 0x100000000 --top 30
--launch.xcrun xctrace help record and xcrun xctrace help export show correct flags.scripts/record_time_profiler.sh: record via attach or launch.scripts/extract_time_samples.py: export time-sample XML from a trace.scripts/top_hotspots.py: symbolicate and rank top app frames.__TEXT load address from vmmap.--binary path; symbols must match the trace.atos.