facebook/sapling
1
1
Fork 0
mirror of https://github.com/facebook/sapling.git synced 2024-10-10 00:45:18 +03:00
Code Issues Projects Releases Wiki Activity

revset: extract tree transformation from optimize()

Browse Source 
This patch separates the simple tree transformation from the optimization step,
which is called as _analyze() since I'll extend this function to infer ordering
flags. I want to avoid making _optimize() more complicated.

This will also allow us to evaluate unoptimized tree.
This commit is contained in:
Yuya Nishihara 2016-08-07 14:35:03 +09:00
parent 9acdc7a967
commit 48b8bb9c60
1 changed files with 63 additions and 23 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

86
mercurial/revset.py
View File

@ -2342,7 +2342,68 @@ def _fixops(x):
return (op,) + tuple(_fixops(y) for y in x[1:])
def _analyze(x):
"""Transform raw parsed tree to evaluatable tree which can be fed to
optimize() or getset()
All pseudo operations should be mapped to real operations or functions
defined in methods or symbols table respectively.
"""
if x is None:
return x
op = x[0]
if op == 'minus':
return _analyze(('and', x[1], ('not', x[2])))
elif op == 'only':
t = ('func', ('symbol', 'only'), ('list', x[1], x[2]))
return _analyze(t)
elif op == 'onlypost':
return _analyze(('func', ('symbol', 'only'), x[1]))
elif op == 'dagrangepre':
return _analyze(('func', ('symbol', 'ancestors'), x[1]))
elif op == 'dagrangepost':
return _analyze(('func', ('symbol', 'descendants'), x[1]))
elif op == 'rangeall':
return _analyze(('range', ('string', '0'), ('string', 'tip')))
elif op == 'rangepre':
return _analyze(('range', ('string', '0'), x[1]))
elif op == 'rangepost':
return _analyze(('range', x[1], ('string', 'tip')))
elif op == 'negate':
s = getstring(x[1], _("can't negate that"))
return _analyze(('string', '-' + s))
elif op in ('string', 'symbol'):
return x
elif op == 'and':
ta = _analyze(x[1])
tb = _analyze(x[2])
return (op, ta, tb)
elif op == 'or':
return (op,) + tuple(_analyze(y) for y in x[1:])
elif op == 'not':
return (op, _analyze(x[1]))
elif op == 'parentpost':
return (op, _analyze(x[1]))
elif op == 'group':
return _analyze(x[1])
elif op in ('dagrange', 'range', 'parent', 'ancestor'):
ta = _analyze(x[1])
tb = _analyze(x[2])
return (op, ta, tb)
elif op == 'list':
return (op,) + tuple(_analyze(y) for y in x[1:])
elif op == 'keyvalue':
return (op, x[1], _analyze(x[2]))
elif op == 'func':
return (op, x[1], _analyze(x[2]))
raise ValueError('invalid operator %r' % op)
def _optimize(x, small):
"""Optimize evaluatable tree
All pseudo operations should be transformed beforehand.
"""
if x is None:
return 0, x
@ -2351,27 +2412,7 @@ def _optimize(x, small):
smallbonus = .5
op = x[0]
if op == 'minus':
return _optimize(('and', x[1], ('not', x[2])), small)
elif op == 'only':
t = ('func', ('symbol', 'only'), ('list', x[1], x[2]))
return _optimize(t, small)
elif op == 'onlypost':
return _optimize(('func', ('symbol', 'only'), x[1]), small)
elif op == 'dagrangepre':
return _optimize(('func', ('symbol', 'ancestors'), x[1]), small)
elif op == 'dagrangepost':
return _optimize(('func', ('symbol', 'descendants'), x[1]), small)
elif op == 'rangeall':
return _optimize(('range', ('string', '0'), ('string', 'tip')), small)
elif op == 'rangepre':
return _optimize(('range', ('string', '0'), x[1]), small)
elif op == 'rangepost':
return _optimize(('range', x[1], ('string', 'tip')), small)
elif op == 'negate':
s = getstring(x[1], _("can't negate that"))
return _optimize(('string', '-' + s), small)
elif op in ('string', 'symbol'):
if op in ('string', 'symbol'):
return smallbonus, x # single revisions are small
elif op == 'and':
wa, ta = _optimize(x[1], True)
@ -2432,8 +2473,6 @@ def _optimize(x, small):
elif op == 'parentpost':
o = _optimize(x[1], small)
return o[0], (op, o[1])
elif op == 'group':
return _optimize(x[1], small)
elif op in ('dagrange', 'range', 'parent', 'ancestor'):
wa, ta = _optimize(x[1], small)
wb, tb = _optimize(x[2], small)
@ -2466,6 +2505,7 @@ def _optimize(x, small):
raise ValueError('invalid operator %r' % op)
def optimize(tree):
tree = _analyze(tree)
_weight, newtree = _optimize(tree, small=True)
return newtree