organicmaps/osm_conflate
13
Fork 0
Code Issues Pull requests Projects Releases Wiki Activity Actions

Initial commit

Browse source
This commit is contained in:
Ilya Zverev 2017-02-15 20:21:05 +03:00
commit af5f48fbf8
6 changed files with 754 additions and 0 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

3
.gitignore vendored Normal file
View file

@ -0,0 +1,3 @@
*.swp
*.osc
*.zip

175
LICENSE Normal file
View file

@ -0,0 +1,175 @@
Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
1. Definitions.
"License" shall mean the terms and conditions for use, reproduction,
and distribution as defined by Sections 1 through 9 of this document.
"Licensor" shall mean the copyright owner or entity authorized by
the copyright owner that is granting the License.
"Legal Entity" shall mean the union of the acting entity and all
other entities that control, are controlled by, or are under common
control with that entity. For the purposes of this definition,
"control" means (i) the power, direct or indirect, to cause the
direction or management of such entity, whether by contract or
otherwise, or (ii) ownership of fifty percent (50%) or more of the
outstanding shares, or (iii) beneficial ownership of such entity.
"You" (or "Your") shall mean an individual or Legal Entity
exercising permissions granted by this License.
"Source" form shall mean the preferred form for making modifications,
including but not limited to software source code, documentation
source, and configuration files.
"Object" form shall mean any form resulting from mechanical
transformation or translation of a Source form, including but
not limited to compiled object code, generated documentation,
and conversions to other media types.
"Work" shall mean the work of authorship, whether in Source or
Object form, made available under the License, as indicated by a
copyright notice that is included in or attached to the work
(an example is provided in the Appendix below).
"Derivative Works" shall mean any work, whether in Source or Object
form, that is based on (or derived from) the Work and for which the
editorial revisions, annotations, elaborations, or other modifications
represent, as a whole, an original work of authorship. For the purposes
of this License, Derivative Works shall not include works that remain
separable from, or merely link (or bind by name) to the interfaces of,
the Work and Derivative Works thereof.
"Contribution" shall mean any work of authorship, including
the original version of the Work and any modifications or additions
to that Work or Derivative Works thereof, that is intentionally
submitted to Licensor for inclusion in the Work by the copyright owner
or by an individual or Legal Entity authorized to submit on behalf of
the copyright owner. For the purposes of this definition, "submitted"
means any form of electronic, verbal, or written communication sent
to the Licensor or its representatives, including but not limited to
communication on electronic mailing lists, source code control systems,
and issue tracking systems that are managed by, or on behalf of, the
Licensor for the purpose of discussing and improving the Work, but
excluding communication that is conspicuously marked or otherwise
designated in writing by the copyright owner as "Not a Contribution."
"Contributor" shall mean Licensor and any individual or Legal Entity
on behalf of whom a Contribution has been received by Licensor and
subsequently incorporated within the Work.
2. Grant of Copyright License. Subject to the terms and conditions of
this License, each Contributor hereby grants to You a perpetual,
worldwide, non-exclusive, no-charge, royalty-free, irrevocable
copyright license to reproduce, prepare Derivative Works of,
publicly display, publicly perform, sublicense, and distribute the
Work and such Derivative Works in Source or Object form.
3. Grant of Patent License. Subject to the terms and conditions of
this License, each Contributor hereby grants to You a perpetual,
worldwide, non-exclusive, no-charge, royalty-free, irrevocable
(except as stated in this section) patent license to make, have made,
use, offer to sell, sell, import, and otherwise transfer the Work,
where such license applies only to those patent claims licensable
by such Contributor that are necessarily infringed by their
Contribution(s) alone or by combination of their Contribution(s)
with the Work to which such Contribution(s) was submitted. If You
institute patent litigation against any entity (including a
cross-claim or counterclaim in a lawsuit) alleging that the Work
or a Contribution incorporated within the Work constitutes direct
or contributory patent infringement, then any patent licenses
granted to You under this License for that Work shall terminate
as of the date such litigation is filed.
4. Redistribution. You may reproduce and distribute copies of the
Work or Derivative Works thereof in any medium, with or without
modifications, and in Source or Object form, provided that You
meet the following conditions:
(a) You must give any other recipients of the Work or
Derivative Works a copy of this License; and
(b) You must cause any modified files to carry prominent notices
stating that You changed the files; and
(c) You must retain, in the Source form of any Derivative Works
that You distribute, all copyright, patent, trademark, and
attribution notices from the Source form of the Work,
excluding those notices that do not pertain to any part of
the Derivative Works; and
(d) If the Work includes a "NOTICE" text file as part of its
distribution, then any Derivative Works that You distribute must
include a readable copy of the attribution notices contained
within such NOTICE file, excluding those notices that do not
pertain to any part of the Derivative Works, in at least one
of the following places: within a NOTICE text file distributed
as part of the Derivative Works; within the Source form or
documentation, if provided along with the Derivative Works; or,
within a display generated by the Derivative Works, if and
wherever such third-party notices normally appear. The contents
of the NOTICE file are for informational purposes only and
do not modify the License. You may add Your own attribution
notices within Derivative Works that You distribute, alongside
or as an addendum to the NOTICE text from the Work, provided
that such additional attribution notices cannot be construed
as modifying the License.
You may add Your own copyright statement to Your modifications and
may provide additional or different license terms and conditions
for use, reproduction, or distribution of Your modifications, or
for any such Derivative Works as a whole, provided Your use,
reproduction, and distribution of the Work otherwise complies with
the conditions stated in this License.
5. Submission of Contributions. Unless You explicitly state otherwise,
any Contribution intentionally submitted for inclusion in the Work
by You to the Licensor shall be under the terms and conditions of
this License, without any additional terms or conditions.
Notwithstanding the above, nothing herein shall supersede or modify
the terms of any separate license agreement you may have executed
with Licensor regarding such Contributions.
6. Trademarks. This License does not grant permission to use the trade
names, trademarks, service marks, or product names of the Licensor,
except as required for reasonable and customary use in describing the
origin of the Work and reproducing the content of the NOTICE file.
7. Disclaimer of Warranty. Unless required by applicable law or
agreed to in writing, Licensor provides the Work (and each
Contributor provides its Contributions) on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
implied, including, without limitation, any warranties or conditions
of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
PARTICULAR PURPOSE. You are solely responsible for determining the
appropriateness of using or redistributing the Work and assume any
risks associated with Your exercise of permissions under this License.
8. Limitation of Liability. In no event and under no legal theory,
whether in tort (including negligence), contract, or otherwise,
unless required by applicable law (such as deliberate and grossly
negligent acts) or agreed to in writing, shall any Contributor be
liable to You for damages, including any direct, indirect, special,
incidental, or consequential damages of any character arising as a
result of this License or out of the use or inability to use the
Work (including but not limited to damages for loss of goodwill,
work stoppage, computer failure or malfunction, or any and all
other commercial damages or losses), even if such Contributor
has been advised of the possibility of such damages.
9. Accepting Warranty or Additional Liability. While redistributing
the Work or Derivative Works thereof, You may choose to offer,
and charge a fee for, acceptance of support, warranty, indemnity,
or other liability obligations and/or rights consistent with this
License. However, in accepting such obligations, You may act only
on Your own behalf and on Your sole responsibility, not on behalf
of any other Contributor, and only if You agree to indemnify,
defend, and hold each Contributor harmless for any liability
incurred by, or claims asserted against, such Contributor by reason
of your accepting any such warranty or additional liability.

28
README.md Normal file
View file

@ -0,0 +1,28 @@
# OSM Conflator
This is a script for merging points from some third-party source with OpenStreetMap data.
Please make sure the license allows that. After merging and uploading, the data can be updated.
## Profiles
Each source should have a profile. It is a python script with variables configuring
names, tags and processing. See examples in the `profiles` directory.
## Usage
For a simplest case, run:
./conflate.py <profile.py>
You might want to add `-v` to get status messages, and other arguments to pass a dataset file
or write the resulting osmChange somewhere. Run `./conflate.py --help` to see a list of arguments.
## Uploading to OpenStreetMap
It is recommended to open the resulting file in the JOSM editor and manually check the changes.
Alternatively, you can use [bulk_upload.py](https://wiki.openstreetmap.org/wiki/Bulk_upload.py)
to upload a change file from the command line.
## License
Written by Ilya Zverev for MAPS.ME. Published under the Apache 2.0 license.

480
conflate.py Executable file
View file

@ -0,0 +1,480 @@
#!/usr/bin/env python3
import argparse
import logging
import requests
import sys
import kdtree
from io import BytesIO
import json # for profiles
import re # for profiles
try:
from lxml import etree
except ImportError:
import xml.etree.ElementTree as etree
OVERPASS_SERVER = 'http://overpass-api.de/api/'
BBOX_PADDING = 0.1 # in degrees
MAX_DISTANCE = 0.001 # how far can object be to be considered a match. 0.001 dg is ~110 m
class SourcePoint:
"""A common class for points. Has an id, latitude and longitude,
and a dict of tags."""
def __init__(self, pid, lat, lon, tags=None):
self.id = str(pid)
self.lat = lat
self.lon = lon
self.tags = {} if tags is None else tags
def __len__(self):
return 2
def __getitem__(self, i):
if i == 0:
return self.lat
elif i == 1:
return self.lon
else:
raise ValueError('A SourcePoint has only lat and lon in a list')
def __eq__(self, other):
return self.id == other.id
def __hash__(self):
return hash(self.id)
class OSMPoint(SourcePoint):
"""An OSM points is a SourcePoint with a few extra fields.
Namely, version, members (for ways and relations), and an action.
The id is compound and created from object type and object id."""
def __init__(self, ptype, pid, version, lat, lon, tags=None):
super().__init__('{}{}'.format(ptype[0], pid), lat, lon, tags)
self.osm_type = ptype
self.osm_id = pid
self.version = version
self.members = None
self.action = None
def to_xml(self):
"""Produces an XML out of the point data. Disregards the "action" field."""
el = etree.Element(self.osm_type, id=str(self.osm_id), version=str(self.version))
for tag, value in self.tags.items():
etree.SubElement(el, 'tag', k=tag, v=value)
if self.osm_type == 'node':
el.set('lat', str(self.lat))
el.set('lon', str(self.lon))
elif self.osm_type == 'way':
for node_id in self.members:
etree.SubElement(el, 'nd', ref=str(node_id))
elif self.osm_type == 'relation':
for member in self.members:
m = etree.SubElement(el, 'member')
for i, n in enumerate(('type', 'ref', 'role')):
m.set(n, str(member[i]))
return el
class ProfileException(Exception):
"""An exception class for the Profile instance."""
def __init__(self, attr, desc):
super().__init__('Field missing in profile: {} ({})'.format(attr, desc))
class Profile:
"""A wrapper for a profile.
A profile is a python script that sets a few local variables.
These variables become properties of the profile, accessible with
a "get" method. If something is a function, it will be called,
optional parameters might be passed to it.
You can compile a list of all supported variables by grepping through
this code, or by looking at a few example profiles. If something
is required, you will be notified of that.
"""
def __init__(self, fileobj):
s = fileobj.read().replace('\r', '')
self.profile = {}
exec(s, globals(), self.profile)
def has(self, attr):
return attr in self.profile
def get(self, attr, default=None, required=None, args=None):
if attr in self.profile:
value = self.profile[attr]
if callable(value):
if args is None:
return value()
else:
return value(*args)
else:
return value
if required is not None:
raise ProfileException(attr, required)
return default
class OsmConflator:
"""The main class for the conflator.
It receives a dataset, after which one must call either
"download_osm" or "parse_osm" methods. Then it is ready to match:
call the "match" method and get results with "to_osc".
"""
def __init__(self, profile, dataset):
self.dataset = {p.id: p for p in dataset}
self.osmdata = {}
self.matched = []
self.profile = profile
if self.profile.get('no_dataset_id', False):
self.ref = None
else:
self.ref = 'ref:' + self.profile.get('dataset_id', required='A fairly unique id of the dataset to query OSM')
def construct_overpass_query(self, bbox=None):
"""Constructs an Overpass API query from the "query" list in the profile.
(k, v) turns into [k=v], (k,) into [k], (k, None) into [!k], (k, "~v") into [k~v]."""
tags = self.profile.get('query', required="a list of tuples. E.g. [('amenity', 'cafe'), ('name', '~Mc.*lds')]")
tag_str = ''
for t in tags:
if len(t) == 1:
q = '"{}"'.format(t[0])
elif t[1] is None or len(t[1]) == 0:
q = '"!{}"'.format(t[0])
elif t[1][0] == '~':
q = '"{}"~"{}"'.format(t[0], t[1][1:])
else:
q = '"{}"="{}"'.format(t[0], t[1])
tag_str += '[' + q + ']'
query = '[out:json][timeout:300];('
bbox_str = '' if bbox is None else '(' + ','.join([str(x) for x in bbox]) + ')'
for t in ('node', 'way', 'relation'):
query += t + tag_str + bbox_str + ';'
if self.ref is not None:
query += t + '["' + self.ref + '"];'
query += '); out meta center;'
return query
def get_dataset_bbox(self):
"""Plain iterates over the dataset and returns the bounding box
that encloses it."""
bbox = [90.0, 180.0, -90.0, -180.0]
for p in self.dataset.values():
bbox[0] = min(bbox[0], p.lat - BBOX_PADDING)
bbox[1] = min(bbox[1], p.lon - BBOX_PADDING)
bbox[2] = max(bbox[2], p.lat + BBOX_PADDING)
bbox[3] = max(bbox[3], p.lon + BBOX_PADDING)
return bbox
def split_into_bboxes(self):
"""
Splits the dataset into multiple bboxes to lower load on the overpass api.
Returns a list of tuples (minlat, minlon, maxlat, maxlon).
Not implemented for now, returns the single big bbox. Not sure if needed.
"""
# TODO
return [self.get_dataset_bbox()]
def check_against_profile_tags(self, tags):
qualifies = self.profile.get('qualifies', args=tags)
if qualifies is not None:
return qualifies
query = self.profile.get('query', None)
if query is not None:
for tag in query:
if len(tag) >= 1:
if tag[0] not in tags:
return False
if len(tag) >= 2 and tag[1][0] != '~':
if tag[1] != tags[tag[0]]:
return False
return True
def download_osm(self):
"""Constructs an Overpass API query and requests objects
to match from a server."""
profile_bbox = self.profile.get('bbox', True)
if not profile_bbox:
bboxes = [None]
elif hasattr(profile_bbox, '__len__') and len(profile_bbox) == 4:
bboxes = [profile_bbox]
else:
bboxes = self.split_into_bboxes()
for b in bboxes:
query = self.construct_overpass_query(b)
logging.debug('Overpass query: %s', query)
r = requests.get(OVERPASS_SERVER + 'interpreter', {'data': query})
if r.status_code != 200:
raise IOError('Failed to download data from Overpass API: {} {}\nQuery: {}'.format(r.status_code, r.text, query))
for el in r.json()['elements']:
if 'tags' not in el:
continue
if 'center' in el:
for ll in ('lat', 'lon'):
el[ll] = el['center'][ll]
if self.check_against_profile_tags(el['tags']):
pt = OSMPoint(el['type'], el['id'], el['version'], el['lat'], el['lon'], el['tags'])
if 'nodes' in el:
pt.members = el['nodes']
elif 'members' in el:
pt.members = [(x['type'], x['ref'], x['role']) for x in el['members']]
self.osmdata[pt.id] = pt
def parse_osm(self, fileobj):
"""Parses an OSM XML file into the "osmdata" field. For ways and relations,
finds the center. Drops objects that do not match the overpass query tags
(see "check_against_profile_tags" method)."""
xml = etree.parse(fileobj).getroot()
nodes = {}
for nd in xml.findall('node'):
nodes[nd.get('id')] = (float(nd.get('lat')), float(nd.get('lon')))
ways = {}
for way in xml.findall('way'):
coord = [0, 0]
count = 0
for nd in way.findall('nd'):
if nd.get('id') in nodes:
count += 1
for i in range(len(coord)):
coord[i] += nodes[nd.get('ref')][i]
ways[way.get('id')] = [coord[0] / count, coord[1] / count]
for el in xml:
tags = {}
for tag in el.findall('tag'):
tags[tag.get('k')] = tag.get('v')
if not self.check_against_profile_tags(tags):
continue
if el.tag == 'node':
coord = nodes[el.get('id')]
members = None
elif el.tag == 'way':
coord = ways[el.get('id')]
members = [nd.get('ref') for nd in el.findall('nd')]
elif el.tag == 'relation':
coord = [0, 0]
count = 0
for m in el.findall('member'):
if m.get('type') == 'node' and m.get('ref') in nodes:
count += 1
for i in range(len(coord)):
coord[i] += nodes[m.get('ref')][i]
elif m.get('type') == 'way' and m.get('ref') in ways:
count += 1
for i in range(len(coord)):
coord[i] += ways[m.get('ref')][i]
coord = [coord[0] / count, coord[1] / count]
members = [(m.get('type'), m.get('ref'), m.get('role')) for m in el.findall('member')]
pt = OSMPoint(el.tag, el.get('id'), el.get('version'), coord[0], coord[1], tags)
pt.members = members
self.osmdata[pt.id] = pt
def register_match(self, dataset_key, osmdata_key, retag=None):
if osmdata_key is not None:
p = self.osmdata[osmdata_key]
del self.osmdata[osmdata_key]
else:
p = None
if dataset_key is not None:
sp = self.dataset[dataset_key]
del self.dataset[dataset_key]
if p is None:
p = OSMPoint('node', -1-len(self.matched), 1, sp.lat, sp.lon, sp.tags)
p.action = 'create'
else:
master_tags = self.profile.get('master_tags', required='a set of authoritative tags that replace OSM values')
changed = False
for k, v in sp.tags.items():
if k not in p.tags or (k in master_tags and p.tags[k] != v):
p.tags[k] = v
changed = True
if changed:
p.action = 'modify'
# If not, action is None and we're not including this object into the osmChange
source = self.profile.get('source', required='value of "source" tag for uploaded OSM objects')
p.tags['source'] = source
if self.ref is not None:
p.tags[self.ref] = sp.id
elif retag:
for k, v in retag.items():
if v is not None:
p.tags[k] = v
elif k in p.tags:
del p.tags[k]
p.action = 'modify'
else:
p.action = 'delete'
if p is not None and p.action is not None:
self.matched.append(p)
def match_dataset_points_smart(self):
"""Smart matching for dataset <-> OSM points.
We find a shortest link between a dataset and an OSM point.
Then we match these and remove both from dicts.
Then find another link and so on, until the length of a link
becomes larger than "max_distance".
Currently the worst case complexity is around O(n^2*log^2 n).
But given the small number of objects to match, and that
the average case complexity is ~O(n*log^2 n), this is fine.
"""
if not self.osmdata:
return
# KDTree distance is squared, so we square the max_distance
max_distance = pow(self.profile.get('max_distance', MAX_DISTANCE), 2)
osm_kd = kdtree.create(list(self.osmdata.values()))
count_matched = 0
dist = []
for sp, v in self.dataset.items():
osm_point, distance = osm_kd.search_nn(v)
if osm_point is not None and distance <= max_distance:
dist.append((distance, sp, osm_point.data))
needs_sorting = True
while dist:
if needs_sorting:
dist.sort(key=lambda x: x[0])
needs_sorting = False
count_matched += 1
osm_point = dist[0][2]
self.register_match(dist[0][1], osm_point.id)
osm_kd = osm_kd.remove(osm_point)
del dist[0]
for i in range(len(dist)-1, -1, -1):
if dist[i][2] == osm_point:
nearest = osm_kd.search_nn(self.dataset[dist[i][1]])
if nearest and nearest[1] <= max_distance:
new_point, distance = nearest
dist[i] = (distance, dist[i][1], new_point.data)
needs_sorting = i == 0 or distance < dist[0][0]
else:
del dist[i]
needs_sorting = i == 0
logging.info('Matched %s points', count_matched)
def match(self):
"""Matches each osm object with a SourcePoint, or marks it as obsolete.
The resulting list of OSM Points are written to the "matched" field."""
if self.ref is not None:
# First match all objects with ref:whatever tag set
count_ref = 0
for k, p in list(self.osmdata.items()):
if self.ref in p.tags:
if p.tags[self.ref] in self.dataset:
count_ref += 1
self.register_match(p.tags[self.ref], k)
logging.info('Updated %s OSM objects with %s tag', count_ref, self.ref)
# Then find matches for unmatched dataset points
self.match_dataset_points_smart()
# Add unmatched dataset points
logging.info('Adding %s unmatched dataset points', len(self.dataset))
for k in list(self.dataset.keys()):
self.register_match(k, None)
# And finally delete some or all of the remaining osm objects
if len(self.osmdata) > 0:
count_deleted = 0
count_retagged = 0
delete_unmatched = self.profile.get('delete_unmatched', False)
retag = self.profile.get('tag_unmatched')
for k, p in list(self.osmdata.items()):
if self.ref is not None and self.ref in p.tags:
# When ref:whatever is present, we can delete that object safely
count_deleted += 1
self.register_match(None, k)
elif delete_unmatched or retag:
if retag:
count_retagged += 1
else:
count_deleted += 1
self.register_match(None, k, retag=retag)
logging.info('Deleted %s and retagged %s unmatched objects from OSM', count_deleted, count_retagged)
def to_osc(self):
"""Returns a string with osmChange."""
osc = etree.Element('osmChange', version='0.6', generator='OSM Conflator')
for osmel in self.matched:
if osmel.action is not None:
el = osmel.to_xml()
etree.SubElement(osc, osmel.action).append(el)
return "<?xml version='1.0' encoding='utf-8'?>\n" + etree.tostring(osc, encoding='utf-8').decode('utf-8')
def read_dataset(profile, fileobj):
"""A helper function to call a "dataset" function in the profile.
If the fileobj is not specified, tries to download a dataset from
an URL specified in "download_url" profile variable."""
if not fileobj:
url = profile.get('download_url')
if url is None:
logging.error('No download_url specified in the profile, please provide a dataset file with --source')
return None
r = requests.get(url)
if r.status_code != 200:
logging.error('Could not download source data: %s %s', r.status_code, r.text)
return None
if len(r.content) == 0:
logging.error('Empty response from %s', url)
return None
fileobj = BytesIO(r.content)
if not profile.has('dataset'):
# The default option is to parse the source as a JSON
try:
data = []
for item in json.load(fileobj):
data.append(SourcePoint(item['id'], item['lat'], item['lon'], item['tags']))
return data
except Exception:
logging.error('Failed to parse the source as a JSON')
return profile.get('dataset', args=(fileobj,), required='returns a list of SourcePoints with the dataset')
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='''
OSM Conflator.
Reads a profile with source data and conflates it with OpenStreetMap data.
Produces an osmChange file ready to be uploaded.''')
parser.add_argument('profile', type=argparse.FileType('r'), help='Name of a profile to use')
parser.add_argument('-o', '--osc', type=argparse.FileType('w'), default=sys.stdout, help='Output osmChange file name')
parser.add_argument('-i', '--source', type=argparse.FileType('rb'), help='Source file to pass to the profile dataset() function')
parser.add_argument('--osm', type=argparse.FileType('r'), help='Instead of querying Overpass API, use this unpacked osm file')
parser.add_argument('--verbose', '-v', action='count', help='Display info messages, use -vv for debugging')
options = parser.parse_args()
if options.verbose == 2:
log_level = logging.DEBUG
elif options.verbose == 1:
log_level = logging.INFO
else:
log_level = logging.WARNING
logging.basicConfig(level=log_level, format='%(asctime)s %(message)s', datefmt='%H:%M:%S')
logging.getLogger("requests").setLevel(logging.WARNING)
logging.debug('Loading profile %s', options.profile)
profile = Profile(options.profile)
dataset = read_dataset(profile, options.source)
if not dataset:
logging.error('Empty source dataset')
sys.exit(2)
logging.info('Read %s items from the dataset', len(dataset))
conflator = OsmConflator(profile, dataset)
if options.osm:
conflator.parse_osm(options.osm)
else:
conflator.download_osm()
logging.info('Downloaded %s objects from OSM', len(conflator.osmdata))
conflator.match()
diff = conflator.to_osc()
options.osc.write(diff)

66
profiles/moscow_parkomats.py Normal file
View file

@ -0,0 +1,66 @@
# Available modules: logging, requests, json, re, etree. But importing these helps catch other errors
import json
import re
import logging
# Verify this at http://data.mos.ru/opendata/1421/passport ("Download .json")
# Disabled since the link returns a zip file and not a plain json
# download_url = 'http://op.mos.ru/EHDWSREST/catalog/export/get?id=89786'
# What will be put into "source" tags. Lower case please
source = 'dit.mos.ru'
# A fairly unique id of the dataset to query OSM, used for "ref:mos_parking" tags
# If you omit it, set explicitly "no_dataset_id = True"
dataset_id = 'mos_parking'
# Tags for querying with overpass api
query = [('amenity', 'vending_machine'), ('vending', 'parking_tickets')]
# Use bbox from dataset points (default). False = query whole world, [minlat, minlon, maxlat, maxlon] to override
bbox = True
# How close OSM point should be to register a match. Default is 0.001 (~110 m)
max_distance = 0.0003 # ~30 m
# Delete objects that match query tags but not dataset? False is the default
delete_unmatched = False
# If set, modify tags on unmatched objects instead
tag_unmatched = {
'fixme': 'Проверить на местности: в данных ДИТ отсутствует. Вероятно, демонтирован',
'amenity': None,
'was:amenity': 'vending_machine'
}
# A set of authoritative tags to replace on matched objects
master_tags = set(('zone:parking', 'ref', 'contact:phone', 'contact:website', 'operator'))
# A list of SourcePoint objects. Initialize with (id, lat, lon, {tags}).
def dataset(fileobj):
source = json.loads(fileobj.read().decode('cp1251'))
RE_NUM4 = re.compile(r'\d{4,6}')
data = []
for el in source:
try:
gid = el['global_id']
zone = el['ParkingZoneNumber']
lon = el['Longitude_WGS84']
lat = el['Latitude_WGS84']
pnum = el['NumberOfParkingMeter']
tags = {
'amenity': 'vending_machine',
'vending': 'parking_tickets',
'zone:parking': zone,
'contact:phone': '+7 495 539-54-54',
'contact:website': 'http://parking.mos.ru/',
'opening_hours': '24/7',
'operator': 'ГКУ «Администратор Московского парковочного пространства»',
'payment:cash': 'no',
'payment:credit_cards': 'yes',
'payment:debit_cards': 'yes'
}
try:
lat = float(lat)
lon = float(lon)
tags['ref'] = RE_NUM4.search(pnum).group(0)
data.append(SourcePoint(gid, lat, lon, tags))
except Exception as e:
logging.warning('PROFILE: Failed to parse lat/lon/ref for parking meter %s: %s', gid, str(e))
except Exception as e:
logging.warning('PROFILE: Failed to get attributes for parking meter: %s', str(e))
return data

2
requirements.txt Normal file
View file

@ -0,0 +1,2 @@
requests
kdtree