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keysym: use a perfect hash function for case sensitive xkb_keysym_from_name 

In 7d84809fdc I added a fast path for the
case-sensitive case, but it is still slowing down Compose parsing.

Instead of the binary search, use a perfect hash function, computed with
a simple python module I found (vendored).

It is faster -- perf diff is:

   Baseline  Delta Abs  Shared Object      Symbol
   ........  .........  .................  ...................................

     22.35%    -14.04%  libc-2.33.so       [.] __strcmp_avx2
     16.75%    +10.28%  bench-compose      [.] xkb_keysym_from_name
     20.72%     +2.40%  bench-compose      [.] parse.constprop.0
      2.29%     -1.97%  bench-compose      [.] strcmp@plt
      2.56%     +1.81%  bench-compose      [.] resolve_name
      2.37%     +0.92%  libc-2.33.so       [.] __GI_____strtoull_l_internal
     26.19%     -0.63%  bench-compose      [.] lex
      1.45%     +0.56%  libc-2.33.so       [.] __memchr_avx2
      1.13%     -0.31%  libc-2.33.so       [.] __strcpy_avx2

Also reduces the binary size:

Before:

      text    data     bss     dec     hex filename
    341111    5064       8  346183   54847 build/libxkbcommon.so.0.0.0

After:

      text    data     bss     dec     hex filename
    330215    5064       8  335287   51db7 build/libxkbcommon.so.0.0.0

Note however that it's still larger than before 7d84809fdccbb5898d08388:

      text    data     bss     dec     hex filename
    320617    5168       8  325793   4f8a1 build/libxkbcommon.so.0.0.0

Signed-off-by: Ran Benita <ran@unusedvar.com>
master
Ran Benita 2021-03-28 20:22:54 +03:00
parent 02b9cabf98
commit 68e69b7deb
4 changed files with 1036 additions and 2577 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

44
scripts/makekeys
View File

@ -2,10 +2,15 @@
import re, sys, itertools
import perfect_hash
pattern = re.compile(r'^#define\s+XKB_KEY_(?P<name>\w+)\s+(?P<value>0x[0-9a-fA-F]+)\s')
matches = [pattern.match(line) for line in open(sys.argv[1])]
entries = [(m.group("name"), int(m.group("value"), 16)) for m in matches if m]
entries_isorted = sorted(entries, key=lambda e: e[0].lower())
entries_kssorted = sorted(entries, key=lambda e: e[1])
print('''
/**
* This file comes from libxkbcommon and was generated by makekeys.py
@ -24,7 +29,7 @@ print('''
static const char *keysym_names =
'''.strip())
offs = 0
for (name, _) in sorted(entries, key=lambda e: e[0].lower()):
for (name, _) in entries_isorted:
entry_offsets[name] = offs
print(' "{name}\\0"'.format(name=name))
offs += len(name) + 1
@ -35,6 +40,35 @@ print('''
#endif
'''.strip())
template = r'''
static const uint16_t keysym_name_G[] = {
$G
};
static size_t
keysym_name_hash_f(const char *key, const char *T)
{
size_t sum = 0;
for (size_t i = 0; key[i] != '\0'; i++)
sum += T[i % $NS] * key[i];
return sum % $NG;
}
static size_t
keysym_name_perfect_hash(const char *key)
{
return (
keysym_name_G[keysym_name_hash_f(key, "$S1")] +
keysym_name_G[keysym_name_hash_f(key, "$S2")]
) % $NG;
}
'''
print(perfect_hash.generate_code(
keys=[name for name, value in entries_isorted],
template=template,
))
print('''
struct name_keysym {
xkb_keysym_t keysym;
@ -46,14 +80,10 @@ def print_entries(x):
print(' {{ 0x{value:08x}, {offs} }}, /* {name} */'.format(offs=entry_offsets[name], value=value, name=name))
print('static const struct name_keysym name_to_keysym[] = {')
print_entries(sorted(entries, key=lambda e: e[0]))
print('};\n')
print('static const struct name_keysym name_to_keysym_icase[] = {')
print_entries(sorted(entries, key=lambda e: e[0].lower()))
print_entries(entries_isorted)
print('};\n')
# *.sort() is stable so we always get the first keysym for duplicate
print('static const struct name_keysym keysym_to_name[] = {')
print_entries(next(g[1]) for g in itertools.groupby(sorted(entries, key=lambda e: e[1]), key=lambda e: e[1]))
print_entries(next(g[1]) for g in itertools.groupby(entries_kssorted, key=lambda e: e[1]))
print('};')

672
scripts/perfect_hash.py Normal file
View File

@ -0,0 +1,672 @@
# Derived from: https://github.com/ilanschnell/perfect-hash
# Commit: e376138af70db9f668de7e23cf84671872a676d8
# BSD 3-Clause License
#
# Copyright (c) 2019, Ilan Schnell
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
# * Neither the name of the <organization> nor the
# names of its contributors may be used to endorse or promote products
# derived from this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
# ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
# WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
# DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY
# DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
# (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
# LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
# ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
# SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
"""
Generate a minimal perfect hash function for the keys in a file,
desired hash values may be specified within this file as well.
A given code template is filled with parameters, such that the
output is code which implements the hash function.
Templates can easily be constructed for any programming language.
The code is based on an a program A.M. Kuchling wrote:
http://www.amk.ca/python/code/perfect-hash
The algorithm the program uses is described in the paper
'Optimal algorithms for minimal perfect hashing',
Z. J. Czech, G. Havas and B.S. Majewski.
http://citeseer.ist.psu.edu/122364.html
The algorithm works like this:
1. You have K keys, that you want to perfectly hash against some
desired hash values.
2. Choose a number N larger than K. This is the number of
vertices in a graph G, and also the size of the resulting table G.
3. Pick two random hash functions f1, f2, that return values from 0..N-1.
4. Now, for all keys, you draw an edge between vertices f1(key) and f2(key)
of the graph G, and associate the desired hash value with that edge.
5. If G is cyclic, go back to step 2.
6. Assign values to each vertex such that, for each edge, you can add
the values for the two vertices and get the desired (hash) value
for that edge. This task is easy, because the graph is acyclic.
This is done by picking a vertex, and assigning it a value of 0.
Then do a depth-first search, assigning values to new vertices so that
they sum up properly.
7. f1, f2, and vertex values of G now make up a perfect hash function.
For simplicity, the implementation of the algorithm combines steps 5 and 6.
That is, we check for loops in G and assign the vertex values in one procedure.
If this procedure succeeds, G is acyclic and the vertex values are assigned.
If the procedure fails, G is cyclic, and we go back to step 2, replacing G
with a new graph, and thereby discarding the vertex values from the failed
attempt.
"""
from __future__ import absolute_import, division, print_function
import sys
import random
import string
import subprocess
import shutil
import tempfile
from collections import defaultdict
from os.path import join
if sys.version_info[0] == 2:
from cStringIO import StringIO
else:
from io import StringIO
__version__ = '0.4.2'
verbose = False
trials = 150
class Graph(object):
"""
Implements a graph with 'N' vertices. First, you connect the graph with
edges, which have a desired value associated. Then the vertex values
are assigned, which will fail if the graph is cyclic. The vertex values
are assigned such that the two values corresponding to an edge add up to
the desired edge value (mod N).
"""
def __init__(self, N):
self.N = N # number of vertices
# maps a vertex number to the list of tuples (vertex, edge value)
# to which it is connected by edges.
self.adjacent = defaultdict(list)
def connect(self, vertex1, vertex2, edge_value):
"""
Connect 'vertex1' and 'vertex2' with an edge, with associated
value 'value'
"""
# Add vertices to each other's adjacent list
self.adjacent[vertex1].append((vertex2, edge_value))
self.adjacent[vertex2].append((vertex1, edge_value))
def assign_vertex_values(self):
"""
Try to assign the vertex values, such that, for each edge, you can
add the values for the two vertices involved and get the desired
value for that edge, i.e. the desired hash key.
This will fail when the graph is cyclic.
This is done by a Depth-First Search of the graph. If the search
finds a vertex that was visited before, there's a loop and False is
returned immediately, i.e. the assignment is terminated.
On success (when the graph is acyclic) True is returned.
"""
self.vertex_values = self.N * [-1] # -1 means unassigned
visited = self.N * [False]
# Loop over all vertices, taking unvisited ones as roots.
for root in range(self.N):
if visited[root]:
continue
# explore tree starting at 'root'
self.vertex_values[root] = 0 # set arbitrarily to zero
# Stack of vertices to visit, a list of tuples (parent, vertex)
tovisit = [(None, root)]
while tovisit:
parent, vertex = tovisit.pop()
visited[vertex] = True
# Loop over adjacent vertices, but skip the vertex we arrived
# here from the first time it is encountered.
skip = True
for neighbor, edge_value in self.adjacent[vertex]:
if skip and neighbor == parent:
skip = False
continue
if visited[neighbor]:
# We visited here before, so the graph is cyclic.
return False
tovisit.append((vertex, neighbor))
# Set new vertex's value to the desired edge value,
# minus the value of the vertex we came here from.
self.vertex_values[neighbor] = (
edge_value - self.vertex_values[vertex]) % self.N
# check if all vertices have a valid value
for vertex in range(self.N):
assert self.vertex_values[vertex] >= 0
# We got though, so the graph is acyclic,
# and all values are now assigned.
return True
class StrSaltHash(object):
"""
Random hash function generator.
Simple byte level hashing: each byte is multiplied to another byte from
a random string of characters, summed up, and finally modulo NG is
taken.
"""
chars = string.ascii_letters + string.digits
def __init__(self, N):
self.N = N
self.salt = ''
def __call__(self, key):
while len(self.salt) < len(key): # add more salt as necessary
self.salt += random.choice(self.chars)
return sum(ord(self.salt[i]) * ord(c)
for i, c in enumerate(key)) % self.N
template = """
def hash_f(key, T):
return sum(ord(T[i % $NS]) * ord(c) for i, c in enumerate(key)) % $NG
def perfect_hash(key):
return (G[hash_f(key, "$S1")] +
G[hash_f(key, "$S2")]) % $NG
"""
class IntSaltHash(object):
"""
Random hash function generator.
Simple byte level hashing, each byte is multiplied in sequence to a table
containing random numbers, summed tp, and finally modulo NG is taken.
"""
def __init__(self, N):
self.N = N
self.salt = []
def __call__(self, key):
while len(self.salt) < len(key): # add more salt as necessary
self.salt.append(random.randint(1, self.N - 1))
return sum(self.salt[i] * ord(c)
for i, c in enumerate(key)) % self.N
template = """
S1 = [$S1]
S2 = [$S2]
assert len(S1) == len(S2) == $NS
def hash_f(key, T):
return sum(T[i % $NS] * ord(c) for i, c in enumerate(key)) % $NG
def perfect_hash(key):
return (G[hash_f(key, S1)] + G[hash_f(key, S2)]) % $NG
"""
def builtin_template(Hash):
return """\
# =======================================================================
# ================= Python code for perfect hash function ===============
# =======================================================================
G = [$G]
""" + Hash.template + """
# ============================ Sanity check =============================
K = [$K]
assert len(K) == $NK
for h, k in enumerate(K):
assert perfect_hash(k) == h
"""
class TooManyInterationsError(Exception):
pass
def generate_hash(keys, Hash=StrSaltHash):
"""
Return hash functions f1 and f2, and G for a perfect minimal hash.
Input is an iterable of 'keys', whos indicies are the desired hash values.
'Hash' is a random hash function generator, that means Hash(N) returns a
returns a random hash function which returns hash values from 0..N-1.
"""
if not isinstance(keys, (list, tuple)):
raise TypeError("list or tuple expected")
NK = len(keys)
if NK != len(set(keys)):
raise ValueError("duplicate keys")
for key in keys:
if not isinstance(key, str):
raise TypeError("key a not string: %r" % key)
if NK > 10000 and Hash == StrSaltHash:
print("""\
WARNING: You have %d keys.
Using --hft=1 is likely to fail for so many keys.
Please use --hft=2 instead.
""" % NK)
# the number of vertices in the graph G
NG = NK + 1
if verbose:
print('NG = %d' % NG)
trial = 0 # Number of trial graphs so far
while True:
if (trial % trials) == 0: # trials failures, increase NG slightly
if trial > 0:
NG = max(NG + 1, int(1.05 * NG))
if verbose:
sys.stdout.write('\nGenerating graphs NG = %d ' % NG)
trial += 1
if NG > 100 * (NK + 1):
raise TooManyInterationsError("%d keys" % NK)
if verbose:
sys.stdout.write('.')
sys.stdout.flush()
G = Graph(NG) # Create graph with NG vertices
f1 = Hash(NG) # Create 2 random hash functions
f2 = Hash(NG)
# Connect vertices given by the values of the two hash functions
# for each key. Associate the desired hash value with each edge.
for hashval, key in enumerate(keys):
G.connect(f1(key), f2(key), hashval)
# Try to assign the vertex values. This will fail when the graph
# is cyclic. But when the graph is acyclic it will succeed and we
# break out, because we're done.
if G.assign_vertex_values():
break
if verbose:
print('\nAcyclic graph found after %d trials.' % trial)
print('NG = %d' % NG)
# Sanity check the result by actually verifying that all the keys
# hash to the right value.
for hashval, key in enumerate(keys):
assert hashval == (
G.vertex_values[f1(key)] + G.vertex_values[f2(key)]
) % NG
if verbose:
print('OK')
return f1, f2, G.vertex_values
class Format(object):
def __init__(self, width=76, indent=4, delimiter=', '):
self.width = width
self.indent = indent
self.delimiter = delimiter
def print_format(self):
print("Format options:")
for name in 'width', 'indent', 'delimiter':
print(' %s: %r' % (name, getattr(self, name)))
def __call__(self, data, quote=False):
if not isinstance(data, (list, tuple)):
return str(data)
lendel = len(self.delimiter)
aux = StringIO()
pos = 20
for i, elt in enumerate(data):
last = bool(i == len(data) - 1)
s = ('"%s"' if quote else '%s') % elt
if pos + len(s) + lendel > self.width:
aux.write('\n' + (self.indent * ' '))
pos = self.indent
aux.write(s)
pos += len(s)
if not last:
aux.write(self.delimiter)
pos += lendel
return '\n'.join(l.rstrip() for l in aux.getvalue().split('\n'))
def generate_code(keys, Hash=StrSaltHash, template=None, options=None):
"""
Takes a list of key value pairs and inserts the generated parameter
lists into the 'template' string. 'Hash' is the random hash function
generator, and the optional keywords are formating options.
The return value is the substituted code template.
"""
f1, f2, G = generate_hash(keys, Hash)
assert f1.N == f2.N == len(G)
try:
salt_len = len(f1.salt)
assert salt_len == len(f2.salt)
except TypeError:
salt_len = None
if template is None:
template = builtin_template(Hash)
if options is None:
fmt = Format()
else:
fmt = Format(width=options.width, indent=options.indent,
delimiter=options.delimiter)
if verbose:
fmt.print_format()
return string.Template(template).substitute(
NS = salt_len,
S1 = fmt(f1.salt),
S2 = fmt(f2.salt),
NG = len(G),
G = fmt(G),
NK = len(keys),
K = fmt(list(keys), quote=True))
def read_table(filename, options):
"""
Reads keys and desired hash value pairs from a file. If no column
for the hash value is specified, a sequence of hash values is generated,
from 0 to N-1, where N is the number of rows found in the file.
"""
if verbose:
print("Reading table from file `%s' to extract keys." % filename)
try:
fi = open(filename)
except IOError:
sys.exit("Error: Could not open `%s' for reading." % filename)
keys = []
if verbose:
print("Reader options:")
for name in 'comment', 'splitby', 'keycol':
print(' %s: %r' % (name, getattr(options, name)))
for n, line in enumerate(fi):
line = line.strip()
if not line or line.startswith(options.comment):
continue
if line.count(options.comment): # strip content after comment
line = line.split(options.comment)[0].strip()
row = [col.strip() for col in line.split(options.splitby)]
try:
key = row[options.keycol - 1]
except IndexError:
sys.exit("%s:%d: Error: Cannot read key, not enough columns." %
(filename, n + 1))
keys.append(key)
fi.close()
if not keys:
exit("Error: no keys found in file `%s'." % filename)
return keys
def read_template(filename):
if verbose:
print("Reading template from file `%s'" % filename)
try:
with open(filename, 'r') as fi:
return fi.read()
except IOError:
sys.exit("Error: Could not open `%s' for reading." % filename)
def run_code(code):
tmpdir = tempfile.mkdtemp()
path = join(tmpdir, 't.py')
with open(path, 'w') as fo:
fo.write(code)
try:
subprocess.check_call([sys.executable, path])
except subprocess.CalledProcessError as e:
raise AssertionError(e)
finally:
shutil.rmtree(tmpdir)
def main():
from optparse import OptionParser
usage = "usage: %prog [options] KEYS_FILE [TMPL_FILE]"
description = """\
Generates code for perfect hash functions from
a file with keywords and a code template.
If no template file is provided, a small built-in Python template
is processed and the output code is written to stdout.
"""
parser = OptionParser(usage = usage,
description = description,
prog = sys.argv[0],
version = "%prog: " + __version__)
parser.add_option("--delimiter",
action = "store",
default = ", ",
help = "Delimiter for list items used in output, "
"the default delimiter is '%default'",
metavar = "STR")
parser.add_option("--indent",
action = "store",
default = 4,
type = "int",
help = "Make INT spaces at the beginning of a "
"new line when generated list is wrapped. "
"Default is %default",
metavar = "INT")
parser.add_option("--width",
action = "store",
default = 76,
type = "int",
help = "Maximal width of generated list when "
"wrapped. Default width is %default",
metavar = "INT")
parser.add_option("--comment",
action = "store",
default = "#",
help = "STR is the character, or sequence of "
"characters, which marks the beginning "
"of a comment (which runs till "
"the end of the line), in the input "
"KEYS_FILE. "
"Default is '%default'",
metavar = "STR")
parser.add_option("--splitby",
action = "store",
default = ",",
help = "STR is the character by which the columns "
"in the input KEYS_FILE are split. "
"Default is '%default'",
metavar = "STR")
parser.add_option("--keycol",
action = "store",
default = 1,
type = "int",
help = "Specifies the column INT in the input "
"KEYS_FILE which contains the keys. "
"Default is %default, i.e. the first column.",
metavar = "INT")
parser.add_option("--trials",
action = "store",
default = 5,
type = "int",
help = "Specifies the number of trials before "
"NG is increased. A small INT will give "
"compute faster, but the array G will be "
"large. A large INT will take longer to "
"compute but G will be smaller. "
"Default is %default",
metavar = "INT")
parser.add_option("--hft",
action = "store",
default = 1,
type = "int",
help = "Hash function type INT. Possible values "
"are 1 (StrSaltHash) and 2 (IntSaltHash). "
"The default is %default",
metavar = "INT")
parser.add_option("-e", "--execute",
action = "store_true",
help = "Execute the generated code within "
"the Python interpreter.")
parser.add_option("-o", "--output",
action = "store",
help = "Specify output FILE explicitly. "
"`-o std' means standard output. "
"`-o no' means no output. "
"By default, the file name is obtained "
"from the name of the template file by "
"substituting `tmpl' to `code'.",
metavar = "FILE")
parser.add_option("-v", "--verbose",
action = "store_true",
help = "verbosity")
options, args = parser.parse_args()
if options.trials <= 0:
parser.error("trials before increasing N has to be larger than zero")
global trials
trials = options.trials
global verbose
verbose = options.verbose
if len(args) not in (1, 2):
parser.error("incorrect number of arguments")
if len(args) == 2 and not args[1].count('tmpl'):
parser.error("template filename does not contain 'tmpl'")
if options.hft == 1:
Hash = StrSaltHash
elif options.hft == 2:
Hash = IntSaltHash
else:
parser.error("Hash function %s not implemented." % options.hft)
# --------------------- end parsing and checking --------------
keys_file = args[0]
if verbose:
print("keys_file = %r" % keys_file)
keys = read_table(keys_file, options)
if verbose:
print("Number os keys: %d" % len(keys))
tmpl_file = args[1] if len(args) == 2 else None
if verbose:
print("tmpl_file = %r" % tmpl_file)
template = read_template(tmpl_file) if tmpl_file else None
if options.output:
outname = options.output
else:
if tmpl_file:
if 'tmpl' not in tmpl_file:
sys.exit("Hmm, template filename does not contain 'tmpl'")
outname = tmpl_file.replace('tmpl', 'code')
else:
outname = 'std'
if verbose:
print("outname = %r\n" % outname)
if outname == 'std':
outstream = sys.stdout
elif outname == 'no':
outstream = None
else:
try:
outstream = open(outname, 'w')
except IOError:
sys.exit("Error: Could not open `%s' for writing." % outname)
code = generate_code(keys, Hash, template, options)
if options.execute or template == builtin_template(Hash):
if verbose:
print('Executing code...\n')
run_code(code)
if outstream:
outstream.write(code)
if not outname == 'std':
outstream.close()
if __name__ == '__main__':
main()

27
src/keysym.c
View File

@ -107,22 +107,17 @@ xkb_keysym_from_name(const char *name, enum xkb_keysym_flags flags)
* So do it in a fast path.
*/
if (!icase) {
size_t lo = 0, hi = ARRAY_SIZE(name_to_keysym) - 1;
while (hi >= lo) {
size_t mid = (lo + hi) / 2;
int cmp = strcmp(name, get_name(&name_to_keysym[mid]));
if (cmp > 0)
lo = mid + 1;
else if (cmp < 0)
hi = mid - 1;
else
return name_to_keysym[mid].keysym;
size_t pos = keysym_name_perfect_hash(name);
if (pos < ARRAY_SIZE(name_to_keysym)) {
const char *s = get_name(&name_to_keysym[pos]);
if (strcmp(name, s) == 0)
return name_to_keysym[pos].keysym;
}
}
/*
* Find the correct keysym for case-insensitive match.
*
* The name_to_keysym_icase table is sorted by istrcmp(). So the binary
* The name_to_keysym table is sorted by istrcmp(). So the binary
* search may return _any_ of all possible case-insensitive duplicates. This
* code searches the entry, all previous and all next entries that match by
* case-insensitive comparison and returns the "best" case-insensitive
@ -135,16 +130,16 @@ xkb_keysym_from_name(const char *name, enum xkb_keysym_flags flags)
* lower-case match is enough in this case.
*/
else {
size_t lo = 0, hi = ARRAY_SIZE(name_to_keysym_icase) - 1;
size_t lo = 0, hi = ARRAY_SIZE(name_to_keysym) - 1;
while (hi >= lo) {
size_t mid = (lo + hi) / 2;
int cmp = istrcmp(name, get_name(&name_to_keysym_icase[mid]));
int cmp = istrcmp(name, get_name(&name_to_keysym[mid]));
if (cmp > 0) {
lo = mid + 1;
} else if (cmp < 0) {
hi = mid - 1;
} else {
entry = &name_to_keysym_icase[mid];
entry = &name_to_keysym[mid];
break;
}
}
@ -154,14 +149,14 @@ xkb_keysym_from_name(const char *name, enum xkb_keysym_flags flags)
if (icase && xkb_keysym_is_lower(entry->keysym))
return entry->keysym;
for (iter = entry - 1; iter >= name_to_keysym_icase; --iter) {
for (iter = entry - 1; iter >= name_to_keysym; --iter) {
if (istrcmp(get_name(iter), get_name(entry)) != 0)
break;
if (xkb_keysym_is_lower(iter->keysym))
return iter->keysym;
}
last = name_to_keysym_icase + ARRAY_SIZE(name_to_keysym_icase);
last = name_to_keysym + ARRAY_SIZE(name_to_keysym);
for (iter = entry + 1; iter < last; ++iter) {
if (istrcmp(get_name(iter), get_name(entry)) != 0)
break;

2870
src/ks_tables.h
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