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a0bff20e31
* Add missing --open option * Update clinic-doctor.txt * Update clinic-flame.txt * Update clinic-bubbleprof.txt * Update clinic-flame.txt
50 lines
2.3 KiB
Plaintext
50 lines
2.3 KiB
Plaintext
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<title>Clinic.js Flame</title> - v{{version}}
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<code>clinic flame</code> helps you find synchronous bottlenecks
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by creating a flamegraph visualization that assists in identifying
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function calls that may be blocking the event loop.
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For more information see the 0x readme, https://github.com/davidmarkclements/0x
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To run <code>clinic flame</code>
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<code>clinic flame -- node server.js</code>
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Once you exit (Ctrl-C) the process, your report will open in a browser window. You can disable this behavior:
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<code>clinic flame --open=false -- node server.js</code>
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If profiling on a server, it can be useful to only do data collection:
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<code>clinic flame --collect-only -- node server.js</code>
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You can then transfer the data and visualize it locally:
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<code>clinic flame --visualize-only PID.clinic.flame</code>
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You can use the --autocannon flag to simulate load on your server.
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--autocannon accepts configuration for autocannon using "subarg" syntax:
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<code>clinic doctor --autocannon [ -m POST /api/example ] -- node server.js</code>
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When configuring --autocannon, the $PORT environment variable contains the
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port your server is listening on:
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<code>clinic doctor --autocannon [ -m POST 'http://localhost:$PORT/?\$page=1' ] -- node server.js</code>
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Note that dollar signs ($) appearing in the URL must be escaped, else they
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will be treated as environment variables as well.
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<h1>Flags</h1>
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-h | --help Display Help
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-v | --version Display Version
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--collect-only Do not process data on termination
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--visualize-only datapath Build or rebuild visualization from data
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--on-port Run a script when the server starts listening on a port.
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--autocannon Run the autocannon benchmarking tool when the server starts listening on a port.
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--open Boolean to enable or disable your report opening in your web browser.
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--dest Destination for the collected data (default <code>.clinic/</code>).
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--upload Upload the visualization using <code>clinic upload</code> instead of saving it locally.
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--server URL Use a different Clinic Upload server than the default (<link>https://upload.clinicjs.org/</link>).
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