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Boris Feld authored
Instead of implementing our own algorithm, we reuse a more generic one. This
previous algorithm did not leave much room for laziness so we do not really
regress in that regards. A small impact is visible for first/last value in
some of the simpler cases. The time needed to compute all values improves
overall. Small optimization in the dagop.headrevs function will help to buy
this back in the next changesets.

There is room to introduce actual laziness in this algorithm, but this is out
of scope for this series.

This has no visible effect on expensive cases:

revset: heads(matching(tip, "author"))
   plain         min           max           first         last          reverse       rev..rst      rev..ast      sort          sor..rst      sor..ast
0) 7.574666      7.545950      7.570743      7.578697      7.525725      7.509929      7.443854      7.488442      7.452880      7.445411      7.689107
1) 7.549390      7.389162      7.529790      7.536297      7.450467      7.555347      7.404586      7.514948      7.542794      7.524787      7.536918

revset: heads(matching(tip, "author")) and -10000:-1
   plain         min           max           first         last          reverse       rev..rst      rev..ast      sort          sor..rst      sor..ast
0) 7.512533      7.605877      7.382894      7.462109      7.420086      7.575034      7.448452      7.549374      7.457880      7.450308      7.515019
1) 7.548677      7.551832      7.629598      7.494857      7.550554      7.521838      7.451794      error         7.321781      7.546885      7.557523

revset: (-10000:-1) and heads(matching(tip, "author"))
   plain         min           max           first         last          reverse       rev..rst      rev..ast      sort          sor..rst      sor..ast
0) 7.465419      7.570089      7.439594      7.521221      7.498716      7.492922      7.479108      7.552397      7.407888      error         7.468264
1) 7.539866      7.548045      7.491761      7.517170      7.469824      7.501990      7.579102      7.502568      7.578102      7.555754      7.567622

In simpler cases, we see a 10-15% impact when retrieving a single value, the
full computation time is equivalent or improved:

revset: (-5000:-1000) and heads(-10000:-1)
   plain         min           max           first         last          reverse       rev..rst      rev..ast      sort          sor..rst      sor..ast
0) 0.004244      0.003368      0.003313      0.003367      0.003327      0.004325      0.003401      0.003379      0.004310      0.003359      0.003396
1) 0.003969  93% 0.003862 114% 0.003834 115% 0.003810 113% 0.003822 114% 0.003940  91% 0.003908 114% 0.003814 112% 0.003986  92% 0.003954 117% 0.003816 112%

revset: heads(all())
   plain         min           max           first         last          reverse       rev..rst      rev..ast      sort          sor..rst      sor..ast
0) 0.036503      0.032564      0.030024      0.032378      0.030887      0.036367      0.031713      0.032205      0.036467      0.032286      0.030300
1) 0.036668      0.035347 108% 0.035611 118% 0.035358 109% 0.035726 115% 0.036411      0.035261 111% 0.036096 112% 0.036052      0.035095 108% 0.035792 118%

revset: heads(-10000:-1)
   plain         min           max           first         last          reverse       rev..rst      rev..ast      sort          sor..rst      sor..ast
0) 0.003936      0.003218      0.003227      0.003302      0.003328      0.003848      0.003305      0.003252      0.003839      0.003306      0.003279
1) 0.003870      0.003785 117% 0.003821 118% 0.003780 114% 0.003769 113% 0.003776      0.003792 114% 0.003805 117% 0.003810      0.003798 114% 0.003840 117%
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setup.py

Mercurial
=========

Mercurial is a fast, easy to use, distributed revision control tool
for software developers.

Basic install::

$ make # see install targets
$ make install # do a system-wide install
$ hg debuginstall # sanity-check setup
$ hg # see help

Running without installing::

$ make local # build for inplace usage
$ ./hg --version # should show the latest version

See https://mercurial-scm.org/ for detailed installation
instructions, platform-specific notes, and Mercurial user information.