Import OpenData roadworks files into the database
Currently importing from: * Lille * Lyon * Montpellier * Nancy * Paris * Rennes * Seine-Saint-Denis * Sicoval (south of Toulouse) * Toulouse * Versailles Partially fixes #1.
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README.md
19
README.md
@ -126,6 +126,19 @@ You can use the `wsgi.py` script at the root of the git repository to serve
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the server side part. You can find some `uwsgi` and `nginx` base config files
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under the `support` folder.
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#### Importing OpenData
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A few OpenData files can be imported in Cycl'Assist, to import roadworks for
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instance. All the useful scripts to import OpenData are in the
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`scripts/opendata` folder. You can set up a daily cron task to automatically
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run the import of roadworks every day.
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#### Updating
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Database migrations are in the `scripts/migrations` folder, labelled by
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versions. You should run them in order from your current versions to the
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latest one when you upgrade.
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## Contributing
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@ -143,12 +156,6 @@ python -m server
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to spawn the server-side part, listening on `localhost:8081`.
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### Updating
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Database migrations are in the `scripts/migrations` folder, labelled by
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versions. You should run them in order from your current versions to the
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latest one when you upgrade.
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### Useful scripts for dev
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You can run `scripts/gps_to_gpx.py` on your GPX trace to create a
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364
scripts/opendata/works.py
Executable file
364
scripts/opendata/works.py
Executable file
@ -0,0 +1,364 @@
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#!/usr/bin/env python
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"""
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Import French opendata about works on roads.
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"""
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import logging
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import os
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import sys
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SCRIPT_DIRECTORY = os.path.dirname(os.path.realpath(__file__))
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sys.path.append(os.path.abspath(os.path.join(SCRIPT_DIRECTORY, '..', '..')))
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import arrow
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import pyproj
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import requests
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from functools import partial
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from shapely.geometry import Point, shape
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from shapely.ops import transform
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from server.models import db, Report
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level = logging.WARN
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if 'DEBUG' in os.environ:
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level = logging.info
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logging.basicConfig(level=level)
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def preprocess_lille(data):
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for item in data:
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try:
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fields = item['fields']
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# Homogeneize start date spelling
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fields['date_debut'] = fields['date_demarrage']
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# Homogeneize geo shape
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fields['geo_shape'] = fields['geometry']
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except KeyError as exc:
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logging.warning('Invalid item in Lille data: %s.', exc)
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continue
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return data
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def preprocess_lyon(data):
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out = []
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for item in data['features']:
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try:
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new_item = {
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'fields': item['properties'],
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'geometry': item['geometry'],
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'recordid': item['properties']['identifiant']
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}
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fields = new_item['fields']
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# Homogeneize start date and end date spelling
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fields['date_debut'] = fields['debutchantier']
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fields['date_fin'] = fields['finchantier']
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# Homogeneize geo shape
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fields['geo_shape'] = item['geometry']
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out.append(new_item)
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except KeyError as exc:
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logging.warning('Invalid item in Lyon data: %s.', exc)
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continue
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return out
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def preprocess_montpellier(data):
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out = []
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for item in data['features']:
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try:
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new_item = {
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'fields': item['properties'],
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'geometry': item['geometry'],
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'recordid': item['properties']['numero']
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}
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fields = new_item['fields']
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# Homogeneize start date and end date spelling
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fields['date_debut'] = fields['datedebut']
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fields['date_fin'] = fields['datefin']
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# Homogeneize geo shape
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fields['geo_shape'] = item['geometry']
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out.append(new_item)
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except KeyError as exc:
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logging.warning('Invalid item in Montpellier data: %s.', exc)
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continue
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return out
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def preprocess_nancy(data):
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out = []
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for item in data['features']:
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try:
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geometry = {
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'type': 'Point',
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'coordinates': [
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item['geometry']['x'],
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item['geometry']['y']
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]
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}
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new_item = {
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'fields': item['attributes'],
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'geometry': geometry,
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'recordid': item['attributes']['OBJECTID']
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}
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fields = new_item['fields']
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# Homogeneize start and end date spelling
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fields['date_debut'] = arrow.get(
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float(fields['DATE_DEBUT']) / 1000
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).isoformat()
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fields['date_fin'] = arrow.get(
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float(fields['DATE_FIN']) / 1000
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).isoformat()
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# Homogeneize geo shape
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fields['geo_shape'] = geometry
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out.append(new_item)
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except KeyError as exc:
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logging.warning('Invalid item in Nancy data: %s.', exc)
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continue
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return out
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def preprocess_rennes(data):
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out = []
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for item in data['features']:
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try:
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new_item = {
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'fields': item['properties'],
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'geometry': item['geometry'],
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'recordid': item['properties']['id']
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}
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fields = new_item['fields']
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# Homogeneize start date spelling
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fields['date_debut'] = fields['date_deb']
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# Homogeneize geo shape
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fields['geo_shape'] = item['geometry']
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out.append(new_item)
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except KeyError as exc:
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logging.warning('Invalid item in Rennes data: %s.', exc)
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continue
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return out
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def preprocess_seine_saint_denis(data):
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out = []
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for item in data['features']:
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try:
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new_item = {
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'fields': item['properties'],
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'geometry': item['geometry'],
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'recordid': item['properties']['id']
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}
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fields = new_item['fields']
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# Homogeneize geo shape
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fields['geo_shape'] = item['geometry']
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out.append(new_item)
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except KeyError as exc:
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logging.warning('Invalid item in Seine-Saint-Denis data: %s.', exc)
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continue
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return out
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def preprocess_sicoval(data):
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for item in data:
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fields = item['fields']
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try:
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# Homogeneize start date and end date spelling
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fields['date_debut'] = fields['startdate']
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fields['date_fin'] = fields['enddate']
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# Homogeneize geo shape
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fields['geo_shape'] = fields['geoshape2']
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except KeyError as exc:
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logging.warning('Invalid item in Sicoval data: %s.', exc)
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continue
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return data
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def preprocess_toulouse(data):
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for item in data:
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try:
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fields = item['fields']
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# Homogeneize start date and end date spelling
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fields['date_debut'] = fields['datedebut']
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fields['date_fin'] = fields['datefin']
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except KeyError as exc:
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logging.warning('Invalid item in Toulouse data: %s.', exc)
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continue
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return data
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def preprocess_versailles(data):
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out = []
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for item in data['features']:
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try:
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new_item = {
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'fields': item['properties'],
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'geometry': item['geometry'],
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'recordid': item['properties']['OBJECTID']
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}
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fields = new_item['fields']
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# Homogeneize start date and end date spelling
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fields['date_debut'] = fields['STARTDATE']
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fields['date_fin'] = fields['ENDDATE']
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# Homogeneize geo shape
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fields['geo_shape'] = item['geometry']
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out.append(new_item)
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except KeyError as exc:
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logging.warning('Invalid item in Versailles data: %s.', exc)
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continue
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return out
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MIN_DISTANCE_REPORT_DETAILS = 40 # Distance in meters, same as in constants.js
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OPENDATA_URLS = {
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# Work in Lille
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"lille": {
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"preprocess": preprocess_lille,
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"url": "https://opendata.lillemetropole.fr/explore/dataset/troncons-de-voirie-impactes-par-des-travaux-en-temps-reel/download/?format=json&timezone=Europe/Berlin"
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},
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# Work in Lyon
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"lyon": {
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"preprocess": preprocess_lyon,
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"url": "https://download.data.grandlyon.com/wfs/grandlyon?SERVICE=WFS&VERSION=2.0.0&outputformat=GEOJSON&maxfeatures=30&request=GetFeature&typename=pvo_patrimoine_voirie.pvochantierperturbant&SRSNAME=urn:ogc:def:crs:EPSG::4171",
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},
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# Work in Montpellier
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"montpellier": {
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"preprocess": preprocess_montpellier,
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"url": "http://data.montpellier3m.fr/sites/default/files/ressources/MMM_MMM_Chantiers.json"
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},
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# Work in Nancy
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"nancy": {
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"preprocess": preprocess_nancy,
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"url": "https://geoservices.grand-nancy.org/arcgis/rest/services/public/VOIRIE_Info_Travaux_Niveau/MapServer/0/query?where=1%3D1&text=&objectIds=&time=&geometry=&geometryType=esriGeometryEnvelope&inSR=&spatialRel=esriSpatialRelIntersects&relationParam=&outFields=*&returnGeometry=true&maxAllowableOffset=&geometryPrecision=&outSR=4326&returnIdsOnly=false&returnCountOnly=false&orderByFields=&groupByFieldsForStatistics=&outStatistics=&returnZ=false&returnM=false&gdbVersion=&returnDistinctValues=false&f=pjson"
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},
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# Work in Paris
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"paris": {
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"preprocess": None,
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"url": "https://opendata.paris.fr/explore/dataset/chantiers-perturbants/download/?format=json&timezone=Europe/Berlin",
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},
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# Work in Rennes
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"rennes": {
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"preprocess": preprocess_rennes,
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"url": "http://travaux.data.rennesmetropole.fr/api/roadworks?epsg=4326"
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},
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# Work in Seine-Saint-Denis
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"seine-saint-denis": {
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"preprocess": preprocess_seine_saint_denis,
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"url": "https://geo.data.gouv.fr/api/geogw/services/5779810963f06a3a8e81541b/feature-types/C1296/download?format=GeoJSON&projection=WGS84"
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},
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# Work in Sicoval (South of Toulouse)
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"sicoval": {
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"preprocess": preprocess_sicoval,
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"url": "https://data.opendatasoft.com/explore/dataset/travauxincidents@sicoval-haute-garonne/download/?format=json&timezone=Europe/Berlin"
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},
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# Work in Toulouse
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"toulouse": {
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"preprocess": preprocess_toulouse,
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"url": "https://data.toulouse-metropole.fr/explore/dataset/chantiers-en-cours/download/?format=json&timezone=Europe/Berlin",
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},
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# Work in Versailles
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"versailles": {
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"preprocess": preprocess_versailles,
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"url": "https://www.data.gouv.fr/en/datasets/r/16f90f14-7896-4463-bc35-9809b55c2c1b"
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},
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}
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REPORT_TYPE = 'interrupt'
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# Projection from WGS84 (GPS) to Lambert93 (for easy buffering of polygons)
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project = partial(
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pyproj.transform,
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pyproj.Proj(init='epsg:4326'), # source coordinates system
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pyproj.Proj(init='epsg:2154') # destination coordinates system
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)
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def process_opendata(name, data, report_type=REPORT_TYPE):
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# Coordinates of current reports in db, as shapely Points in Lambert93
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current_reports_points = []
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for report in Report.select().where(Report.type == REPORT_TYPE):
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current_reports_points.append(
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transform(project, Point(report.lng, report.lat))
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)
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for item in data:
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try:
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fields = item['fields']
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geometry = shape(item['geometry'])
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position = geometry.centroid # Report position
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# Check that the work is currently being done
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now = arrow.now('Europe/Paris')
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start_date = arrow.get(fields['date_debut'])
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end_date = arrow.get(fields['date_fin'])
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if not (start_date < now < end_date):
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logging.info(
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'Ignoring record %s, work not currently in progress.',
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item['recordid']
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)
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continue
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# Check if this precise position is already in the database
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if transform(project, position) in current_reports_points:
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logging.info(
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('Ignoring record %s, a similar report is already in '
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'the database.'),
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item['recordid']
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)
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continue
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# Check no similar reports is nearby
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if 'geo_shape' in fields:
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geo_shape = shape(fields['geo_shape'])
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else:
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geo_shape = geometry
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geo_shape = transform(project, geo_shape)
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overlap_area = geo_shape.buffer(MIN_DISTANCE_REPORT_DETAILS)
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is_already_inserted = False
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for report_point in current_reports_points:
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if report_point.within(geo_shape):
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# A similar report is already there
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is_already_inserted = True
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logging.info(
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('Ignoring record %s, a similar report is already in '
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'the database.'),
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item['recordid']
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)
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break
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if is_already_inserted:
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# Skip this report if a similar one is nearby
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continue
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# Get the position of the center of the item
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lng, lat = position.x, position.y
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# Compute expiration datetime
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expiration_datetime = end_date.replace(microsecond=0).naive
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# Add the report to the db
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logging.info('Adding record %s to the database.', item['recordid'])
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Report.create(
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type=report_type,
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expiration_datetime=expiration_datetime,
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lat=lat,
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lng=lng
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)
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except KeyError as exc:
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logging.warning(
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'Invalid record %s in %s, missing key: %s',
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item.get('recordid', '?'),
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name,
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exc
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)
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if __name__ == '__main__':
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db.connect()
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for name, item in OPENDATA_URLS.items():
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logging.info('Processing opendata from %s', name)
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try:
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r = requests.get(item['url'])
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data = r.json()
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except (requests.RequestException, ValueError) as exc:
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logging.warning('Error while fetching data for %s: %s.',
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name, exc)
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continue
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if item['preprocess']:
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data = item['preprocess'](data)
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process_opendata(name, data)
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Loading…
Reference in New Issue
Block a user