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Developer Guide

  • Integrate a new platform to OpenROAD Flow: Guide.
  • Adding a new design: Guide.
  • Continuous Integration: Guide.
  • How do I update the codebase? There are different ways to update your codebase depending on the method you installed it. We provide detailed instructions in this guide.
  • How do I contribute? Follow our Git Quickstart guide here.

Timing and Logging (run_command.py)

Every flow stage (synthesis, floorplan, CTS, routing, etc.) is wrapped by flow/scripts/run_command.py, which replaces the previous GNU time + tee shell pipeline with a pure-Python implementation.

What it does

run_command.py runs a command and:

  • Measures wall-clock time, CPU time (user + sys), and peak memory using Python's time.monotonic() and resource.getrusage().
  • Streams output line-by-line to both the console and a log file (replacing tee), flushing after every line for real-time tail -f observability.
  • Appends an Elapsed time: ... line in the format expected by genElapsedTime.py and genMetrics.py.

Usage

python3 flow/scripts/run_command.py [--log FILE] [--append] [--tee] -- command [args...]
Flag Effect
--log FILE Write command output + timing line to FILE
--append Append to log file instead of overwriting
--tee Also write output to stdout (like the tee command)

Monitoring long-running stages

When running under Bazel (bazelisk test ...) or other batch systems that hide console output, you can monitor progress by finding and tailing the log:

# Find the running stage's log file
ps -Af | grep run_command
# or
ps -Af | grep tmp.log

# Watch it in real time
tail -f /path/to/logs/4_cts.tmp.log

Output appears immediately in the log file (line-buffered with flush), so tail -f shows real-time progress.

Cross-platform support

Works on both Linux and macOS using only Python standard library modules. Peak memory is normalized automatically (ru_maxrss is KB on Linux, bytes on macOS).

Testing

python3 -m pytest flow/test/test_run_command.py -v