/usr/lib/python2.7/dist-packages/imposm/reader.py is in python-imposm 2.6.0+ds-4.
This file is owned by root:root, with mode 0o644.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 | # Copyright 2011 Omniscale (http://omniscale.com)
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from functools import partial
from multiprocessing import Process, JoinableQueue
from imposm.parser import OSMParser
from imposm.util import setproctitle
class ImposmReader(object):
def __init__(self, mapping, cache, pool_size=2, merge=False, logger=None):
self.pool_size = pool_size
self.mapper = mapping
self.merge = merge
self.cache = cache
self.reader = None
self.logger = logger
self.estimated_coords = 0
def read(self, filename):
nodes_queue = JoinableQueue(128)
coords_queue = JoinableQueue(512)
ways_queue = JoinableQueue(128)
relations_queue = JoinableQueue(128)
log_proc = self.logger()
log_proc.start()
marshal = True
if self.merge:
# merging needs access to unmarshaled data
marshal = False
estimates = {
'coords': self.estimated_coords,
'nodes': self.estimated_coords//50,
'ways': self.estimated_coords//7,
'relations': self.estimated_coords//1000,
}
coords_writer = CacheWriterProcess(coords_queue, self.cache.coords_cache,
estimates['coords'], log=partial(log_proc.log, 'coords'),
marshaled_data=marshal)
coords_writer.start()
nodes_writer = CacheWriterProcess(nodes_queue, self.cache.nodes_cache,
estimates['nodes'], log=partial(log_proc.log, 'nodes'),
marshaled_data=marshal)
nodes_writer.start()
ways_writer = CacheWriterProcess(ways_queue, self.cache.ways_cache,
estimates['ways'], merge=self.merge, log=partial(log_proc.log, 'ways'),
marshaled_data=marshal)
ways_writer.start()
relations_writer = CacheWriterProcess(relations_queue, self.cache.relations_cache,
estimates['relations'], merge=self.merge, log=partial(log_proc.log, 'relations'),
marshaled_data=marshal)
relations_writer.start()
log_proc.message('coords: %dk nodes: %dk ways: %dk relations: %dk (estimated)' % (
estimates['coords']/1000, estimates['nodes']/1000, estimates['ways']/1000,
estimates['relations']/1000)
)
# keep one CPU free for writer proc on hosts with 4 or more CPUs
pool_size = self.pool_size if self.pool_size < 4 else self.pool_size - 1
parser = OSMParser(pool_size, nodes_callback=nodes_queue.put, coords_callback=coords_queue.put,
ways_callback=ways_queue.put, relations_callback=relations_queue.put, marshal_elem_data=marshal)
parser.nodes_tag_filter = self.mapper.tag_filter_for_nodes()
parser.ways_tag_filter = self.mapper.tag_filter_for_ways()
parser.relations_tag_filter = self.mapper.tag_filter_for_relations()
parser.parse(filename)
coords_queue.put(None)
nodes_queue.put(None)
ways_queue.put(None)
relations_queue.put(None)
coords_writer.join()
nodes_writer.join()
ways_writer.join()
relations_writer.join()
log_proc.stop()
log_proc.join()
class CacheWriterProcess(Process):
def __init__(self, queue, cache, estimated_records=None, merge=False, log=None,
marshaled_data=False):
Process.__init__(self)
self.daemon = True
setproctitle('imposm writer')
self.queue = queue
self.cache = cache
self.merge = merge
self.log = log
self.marshaled_data = marshaled_data
self.estimated_records = estimated_records
def run(self):
# print 'creating %s (%d)' % (self.filename, self.estimated_records or 0)
cache = self.cache(mode='w', estimated_records=self.estimated_records)
if self.marshaled_data:
cache_put = cache.put_marshaled
else:
cache_put = cache.put
while True:
data = self.queue.get()
if data is None:
self.queue.task_done()
break
if self.merge:
for d in data:
if d[0] in cache:
elem = cache.get(d[0])
elem.merge(*d[1:])
d = elem.to_tuple()
cache_put(*d)
else:
for d in data:
cache_put(*d)
if self.log:
self.log(len(data))
self.queue.task_done()
cache.close()
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