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analyser_merge_public_equipment_FR_nantes_toilets.py
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#!/usr/bin/env python
#-*- coding: utf-8 -*-
###########################################################################
## ##
## Copyrights Adrien Pavie 2017 ##
## ##
## This program is free software: you can redistribute it and/or modify ##
## it under the terms of the GNU General Public License as published by ##
## the Free Software Foundation, either version 3 of the License, or ##
## (at your option) any later version. ##
## ##
## This program is distributed in the hope that it will be useful, ##
## but WITHOUT ANY WARRANTY; without even the implied warranty of ##
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the ##
## GNU General Public License for more details. ##
## ##
## You should have received a copy of the GNU General Public License ##
## along with this program. If not, see <http://www.gnu.org/licenses/>. ##
## ##
###########################################################################
from modules.OsmoseTranslation import T_
from .Analyser_Merge import Analyser_Merge_Point, SourceOpenDataSoft, JSON, Load_XY, Conflate, Select, Mapping
import json
class Analyser_Merge_Public_Equipment_FR_Nantes_Toilets(Analyser_Merge_Point):
def __init__(self, config, logger = None):
Analyser_Merge_Point.__init__(self, config, logger)
self.def_class_missing_official(item = 8180, id = 5, level = 3, tags = ['merge', 'public equipment', 'fix:survey', 'fix:picture'],
title = T_('{0} toilets not integrated', 'Nantes Métropole'))
self.init(
"https://data.nantesmetropole.fr/explore/dataset/244400404_toilettes-publiques-nantes-metropole",
"Toilettes publiques de Nantes Métropole",
JSON(
SourceOpenDataSoft(
attribution="Nantes Métropole",
url="https://data.nantesmetropole.fr/explore/dataset/244400404_toilettes-publiques-nantes-metropole",
format="json"),
extractor = lambda json: map(lambda j: j['fields'], json)),
Load_XY("geo_shape.coordinates", "geo_shape.coordinates",
xFunction = lambda c: c and json.loads(c)[0],
yFunction = lambda c: c and json.loads(c)[1]),
Conflate(
select = Select(
types = ["nodes", "ways"],
tags = {"amenity": "toilets"}),
conflationDistance = 100,
mapping = Mapping(
static1 = {
"amenity": "toilets",
"access": "yes"},
static2 = {"source": self.source},
mapping1 = {"name": 'nom'} )))