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Get rid of the various different launchers

Browse Source 
Now there is only one launcher. Which means it can be used to start
kitty with profiling and ASAN in the natural way. The recommended
way to run kitty from source is now:

./kitty/launcher/kitty

The launcher also automatically re-execs to resolve symlinks on macOS.
This commit is contained in:
Kovid Goyal
2019-06-24 17:00:34 +05:30
parent af3504e05c
commit 9135387cfa
10 changed files with 190 additions and 243 deletions
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13
docs/build.rst
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@@ -44,17 +44,10 @@ Now build the native code parts of |kitty| with the following command::
You can run |kitty|, as::
python3 .
./kitty/launcher/kitty
If that works, you can create a script to launch |kitty|:
.. code-block:: sh
#!/usr/bin/env python3
import runpy
runpy.run_path('/path/to/kitty/dir', run_name='__main__')
And place it in :file:`~/bin` or :file:`/usr/bin` so that you can run |kitty| using
If that works, you can create a symlink to the launcher in :file:`~/bin` or
some other directory on your PATH so that you can run |kitty| using
just ``kitty``.

12
docs/performance.rst
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@@ -14,12 +14,12 @@ render loop to reduce CPU usage. See :ref:`conf-kitty-performance` for details.
See also the :opt:`sync_to_monitor` option to further decrease latency at the cost
of some `tearing <https://en.wikipedia.org/wiki/Screen_tearing>`_ while scrolling.
You can generate detailed per-function performance data using
`gperftools <https://github.com/gperftools/gperftools>`_. Build |kitty| with
`make profile` which will create an executable called `kitty-profile`. Run
that and perform the task you want to analyse, for example, scrolling a large
file with `less`. After you quit, function call statistics will be printed to
`stdout` and you can use tools like *kcachegrind* for more detailed analysis.
You can generate detailed per-function performance data using `gperftools
<https://github.com/gperftools/gperftools>`_. Build |kitty| with `make
profile`. Run kitty and perform the task you want to analyse, for example,
scrolling a large file with `less`. After you quit, function call statistics
will be printed to `stdout` and you can use tools like *kcachegrind* for more
detailed analysis.
Here are some CPU usage numbers for the task of scrolling a file continuously
in less. The CPU usage is for the terminal process and X together and is