comparison mercurial/revsetlang.py @ 34044:b862e6fca7ac

revsetlang: build optimized tree by helper function

This should make optimize() more readable, but it doubles the parsing cost.

  (original)
  $ python -m timeit -n10000 -s 'from mercurial import revsetlang as L' \
  'L.optimize(L.analyze(L.parse("::tip")))'
  10000 loops, best of 3: 18.1 usec per loop

  (this patch)
  $ python -m timeit -n10000 -s 'from mercurial import revsetlang as L' \
  'L._treecache.clear(); L.optimize(L.analyze(L.parse("::tip")))'
  10000 loops, best of 3: 48.4 usec per loop

30usec isn't dominant compared to the revset evaluation, but that is a cost.
That's why a parsed tree is cached, which can benefit in hgweb or chg server.

34043:90896b61fe26

def getargsdict(x, funcname, keys):
    return parser.buildargsdict(getlist(x), funcname, parser.splitargspec(keys),
                                keyvaluenode='keyvalue', keynode='symbol')

def _isnamedfunc(x, funcname):
    """Check if given tree matches named function"""
    return x and x[0] == 'func' and getsymbol(x[1]) == funcname

def _isposargs(x, n):

    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 == 'negate':
        s = getstring(x[1], _("can't negate that"))
        return _analyze(('string', '-' + s))
    elif op in ('string', 'symbol'):
        return x

        wa, ta = _optimize(x[1], True)
        wb, tb = _optimize(x[2], True)
        w = min(wa, wb)

        # (::x and not ::y)/(not ::y and ::x) have a fast path
        tm = _matchonly(ta, tb) or _matchonly(tb, ta)
        if tm:
            return w, ('func', ('symbol', 'only'), tm)

        if tb is not None and tb[0] == 'not':
            return wa, ('difference', ta, tb[1])
        if wa > wb:
            op = 'andsmally'

                return
            if len(ss) == 1:
                w, t = ss[0]
            else:
                s = '\0'.join(t[1] for w, t in ss)
                y = ('func', ('symbol', '_list'), ('string', s))
                w, t = _optimize(y, False)
            ws.append(w)
            ts.append(t)
            del ss[:]
        for y in getlist(x[1]):

            return ws[0], ts[0] # 'or' operation is fully optimized out
        return max(ws), (op, ('list',) + tuple(ts))
    elif op == 'not':
        # Optimize not public() to _notpublic() because we have a fast version
        if x[1][:3] == ('func', ('symbol', 'public'), None):
            newsym = ('func', ('symbol', '_notpublic'), None)
            o = _optimize(newsym, not small)
            return o[0], o[1]
        else:
            o = _optimize(x[1], not small)
            return o[0], (op, o[1])
    elif op == 'rangeall':

34044:b862e6fca7ac

def getargsdict(x, funcname, keys):
    return parser.buildargsdict(getlist(x), funcname, parser.splitargspec(keys),
                                keyvaluenode='keyvalue', keynode='symbol')

# cache of {spec: raw parsed tree} built internally
_treecache = {}

def _cachedtree(spec):
    # thread safe because parse() is reentrant and dict.__setitem__() is atomic
    tree = _treecache.get(spec)
    if tree is None:
        _treecache[spec] = tree = parse(spec)
    return tree

def _build(tmplspec, *repls):
    """Create raw parsed tree from a template revset statement

    >>> _build('f(_) and _', ('string', '1'), ('symbol', '2'))
    ('and', ('func', ('symbol', 'f'), ('string', '1')), ('symbol', '2'))
    """
    template = _cachedtree(tmplspec)
    return parser.buildtree(template, ('symbol', '_'), *repls)

def _isnamedfunc(x, funcname):
    """Check if given tree matches named function"""
    return x and x[0] == 'func' and getsymbol(x[1]) == funcname

def _isposargs(x, n):

    if x is None:
        return x

    op = x[0]
    if op == 'minus':
        return _analyze(_build('_ and not _', *x[1:]))
    elif op == 'only':
        return _analyze(_build('only(_, _)', *x[1:]))
    elif op == 'onlypost':
        return _analyze(_build('only(_)', x[1]))
    elif op == 'dagrangepre':
        return _analyze(_build('ancestors(_)', x[1]))
    elif op == 'dagrangepost':
        return _analyze(_build('descendants(_)', x[1]))
    elif op == 'negate':
        s = getstring(x[1], _("can't negate that"))
        return _analyze(('string', '-' + s))
    elif op in ('string', 'symbol'):
        return x

        wa, ta = _optimize(x[1], True)
        wb, tb = _optimize(x[2], True)
        w = min(wa, wb)

        # (::x and not ::y)/(not ::y and ::x) have a fast path
        m = _matchonly(ta, tb) or _matchonly(tb, ta)
        if m:
            return w, _build('only(_, _)', *m[1:])

        if tb is not None and tb[0] == 'not':
            return wa, ('difference', ta, tb[1])
        if wa > wb:
            op = 'andsmally'

                return
            if len(ss) == 1:
                w, t = ss[0]
            else:
                s = '\0'.join(t[1] for w, t in ss)
                y = _build('_list(_)', ('string', s))
                w, t = _optimize(y, False)
            ws.append(w)
            ts.append(t)
            del ss[:]
        for y in getlist(x[1]):

            return ws[0], ts[0] # 'or' operation is fully optimized out
        return max(ws), (op, ('list',) + tuple(ts))
    elif op == 'not':
        # Optimize not public() to _notpublic() because we have a fast version
        if x[1][:3] == ('func', ('symbol', 'public'), None):
            o = _optimize(_build('_notpublic()'), not small)
            return o[0], o[1]
        else:
            o = _optimize(x[1], not small)
            return o[0], (op, o[1])
    elif op == 'rangeall':