Improve contributing.asciidoc for run_profile.py
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@ -183,17 +183,21 @@ tox -e py35-cov -- tests/unit/browser/test_webelem.py
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Profiling
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~~~~~~~~~
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In the _scripts/_ subfolder there's a `run_profile.py` which profiles the code
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and shows a graphical representation of what takes how much time.
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In the _scripts/dev/_ subfolder there's `run_profile.py` which profiles the
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code and shows a graphical representation of what takes how much time.
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It uses the built-in Python
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https://docs.python.org/3.6/library/profile.html[cProfile] module and can show
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the output in four different ways:
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https://docs.python.org/3/library/profile.html[cProfile] module. It launches a
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qutebrowser instance, waits for it to exit and then shows the graph.
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* Raw profile file (`--profile-tool=none`)
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Available methods for visualization are:
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* https://jiffyclub.github.io/snakeviz/[SnakeViz] (`--profile-tool=snakeviz`, the default)
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* https://pypi.python.org/pypi/pyprof2calltree/[pyprof2calltree] and http://kcachegrind.sourceforge.net/html/Home.html[KCacheGrind] (`--profile-tool=kcachegrind`)
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* https://jiffyclub.github.io/snakeviz/[SnakeViz] (`--profile-tool=snakeviz`)
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* https://github.com/jrfonseca/gprof2dot[gprof2dot] (needs `dot` from http://graphviz.org/[Graphviz] and http://feh.finalrewind.org/[feh])
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* https://github.com/jrfonseca/gprof2dot[gprof2dot] (`--profile-tool=gprof2dot`, needs `dot` from http://graphviz.org/[Graphviz] and http://feh.finalrewind.org/[feh])
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* https://github.com/nschloe/tuna[tuna] (`--profile-tool=tuna`)
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You can also save the binary profile data to a file (`--profile-tool=none`).
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Debugging
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~~~~~~~~~
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