class SearchArticle(SearchDocument):
class Meta(BaseMeta):
doc_type = ARTICLE_TYPE
activities = QEnumArray(
'act', model_field=Article.activities)
article_categories = QEnumArray(
'acat', model_field=Article.categories)
article_type = QEnum(
'atyp', model_field=Article.article_type)
FIELDS = ['activities', 'article_type']
@staticmethod
def to_search_document(document, index):
search_document = SearchDocument.to_search_document(document, index)
if document.redirects_to:
return search_document
search_document['article_categories'] = document.categories
SearchDocument.copy_fields(
search_document, document, SearchArticle.FIELDS)
return search_document
class SearchArea(SearchDocument):
class Meta(BaseMeta):
doc_type = AREA_TYPE
area_type = QEnum('atyp', model_field=Area.area_type)
FIELDS = ['area_type']
@staticmethod
def to_search_document(document, index):
search_document = SearchDocument.to_search_document(
document, index, include_areas=False)
if document.redirects_to:
return search_document
SearchDocument.copy_fields(search_document, document,
SearchArea.FIELDS)
return search_document
class SearchRoute(SearchDocument):
class Meta(BaseMeta):
doc_type = ROUTE_TYPE
# array of waypoint ids
waypoints = QLong('w', is_id=True)
# array of user ids
users = QLong('u', is_id=True)
activities = QEnumArray('act', model_field=Route.activities)
elevation_min = QInteger('rmina', range=True)
elevation_max = QInteger('rmaxa', range=True)
height_diff_up = QInteger('hdif', range=True)
height_diff_down = QInteger('ddif', range=True)
route_length = QInteger('rlen', range=True)
difficulties_height = QInteger('ralt', range=True)
height_diff_access = QInteger('rappr', range=True)
height_diff_difficulties = QInteger('dhei', range=True)
route_types = QEnumArray('rtyp', model_field=Route.route_types)
orientations = QEnumArray('fac', model_field=Route.orientations)
durations = QEnumRange('time',
model_field=Route.durations,
enum_mapper=sortable_route_duration_types)
glacier_gear = QEnum('glac', model_field=Route.glacier_gear)
configuration = QEnumArray('conf', model_field=Route.configuration)
ski_rating = QEnumRange('trat',
model_field=Route.ski_rating,
enum_mapper=sortable_ski_ratings)
ski_exposition = QEnumRange('sexpo',
model_field=Route.ski_exposition,
enum_mapper=sortable_exposition_ratings)
labande_ski_rating = QEnumRange('srat',
model_field=Route.labande_ski_rating,
enum_mapper=sortable_labande_ski_ratings)
labande_global_rating = QEnumRange('lrat',
model_field=Route.labande_global_rating,
enum_mapper=sortable_global_ratings)
global_rating = QEnumRange('grat',
model_field=Route.global_rating,
enum_mapper=sortable_global_ratings)
engagement_rating = QEnumRange('erat',
model_field=Route.engagement_rating,
enum_mapper=sortable_engagement_ratings)
risk_rating = QEnumRange('orrat',
model_field=Route.risk_rating,
enum_mapper=sortable_risk_ratings)
equipment_rating = QEnumRange('prat',
model_field=Route.equipment_rating,
enum_mapper=sortable_equipment_ratings)
ice_rating = QEnumRange('irat',
model_field=Route.ice_rating,
enum_mapper=sortable_ice_ratings)
mixed_rating = QEnumRange('mrat',
model_field=Route.mixed_rating,
enum_mapper=sortable_mixed_ratings)
exposition_rock_rating = QEnumRange(
'rexpo',
model_field=Route.exposition_rock_rating,
enum_mapper=sortable_exposition_rock_ratings)
rock_free_rating = QEnumRange('frat',
model_field=Route.rock_free_rating,
enum_mapper=sortable_climbing_ratings)
rock_required_rating = QEnumRange('rrat',
model_field=Route.rock_required_rating,
enum_mapper=sortable_climbing_ratings)
aid_rating = QEnumRange('arat',
model_field=Route.aid_rating,
enum_mapper=sortable_aid_ratings)
via_ferrata_rating = QEnumRange('krat',
model_field=Route.via_ferrata_rating,
enum_mapper=sortable_via_ferrata_ratings)
hiking_rating = QEnumRange('hrat',
model_field=Route.hiking_rating,
enum_mapper=sortable_hiking_ratings)
hiking_mtb_exposition = QEnumRange('hexpo',
model_field=Route.hiking_mtb_exposition,
enum_mapper=sortable_exposition_ratings)
snowshoe_rating = QEnumRange('wrat',
model_field=Route.snowshoe_rating,
enum_mapper=sortable_snowshoe_ratings)
mtb_up_rating = QEnumRange('mbur',
model_field=Route.mtb_up_rating,
enum_mapper=sortable_mtb_up_ratings)
mtb_down_rating = QEnumRange('mbdr',
model_field=Route.mtb_down_rating,
enum_mapper=sortable_mtb_down_ratings)
mtb_length_asphalt = QInteger('mbroad', range=True)
mtb_length_trail = QInteger('mbtrack', range=True)
mtb_height_diff_portages = QInteger('mbpush', range=True)
rock_types = QEnumArray('rock', model_field=Route.rock_types)
climbing_outdoor_type = QEnumArray('crtyp',
model_field=Route.climbing_outdoor_type)
slackline_type = QEnum('sltyp', model_field=Route.slackline_type)
FIELDS = [
'activities', 'elevation_min', 'elevation_max', 'height_diff_up',
'height_diff_down', 'route_length', 'difficulties_height',
'height_diff_access', 'height_diff_difficulties', 'route_types',
'orientations', 'glacier_gear', 'configuration', 'mtb_length_asphalt',
'mtb_length_trail', 'mtb_height_diff_portages', 'rock_types',
'climbing_outdoor_type', 'slackline_type'
]
ENUM_RANGE_FIELDS = [
'durations',
'ski_rating',
'ski_exposition',
'labande_ski_rating',
'labande_global_rating',
'global_rating',
'engagement_rating',
'risk_rating',
'equipment_rating',
'ice_rating',
'mixed_rating',
'exposition_rock_rating',
'rock_free_rating',
'rock_required_rating',
'aid_rating',
'via_ferrata_rating',
'hiking_rating',
'hiking_mtb_exposition',
'snowshoe_rating',
'mtb_up_rating',
'mtb_down_rating',
]
@staticmethod
def to_search_document(document, index):
search_document = SearchDocument.to_search_document(document, index)
if document.redirects_to:
return search_document
SearchDocument.copy_fields(search_document, document,
SearchRoute.FIELDS)
SearchDocument.copy_enum_range_fields(search_document, document,
SearchRoute.ENUM_RANGE_FIELDS,
SearchRoute)
for locale in document.locales:
search_document['title_' + locale.lang] = \
get_title(locale.title, locale.title_prefix)
if document.associated_waypoints_ids:
# add the document ids of associated waypoints and of the parent
# and grand-parents of these waypoints
search_document['waypoints'] = \
document.associated_waypoints_ids.waypoint_ids
if document.associated_users_ids:
# add the document ids of associated users
search_document['users'] = \
document.associated_users_ids.user_ids
return search_document
class SearchWaypoint(SearchDocument):
class Meta(BaseMeta):
doc_type = WAYPOINT_TYPE
elevation = QInteger('walt', range=True)
prominence = QInteger('prom', range=True)
waypoint_type = QEnum('wtyp', model_field=Waypoint.waypoint_type)
rock_types = QEnumArray('wrock', model_field=Waypoint.rock_types)
orientations = QEnumArray('wfac', model_field=Waypoint.orientations)
best_periods = QEnumArray('period', model_field=Waypoint.best_periods)
lift_access = QBoolean('plift', is_bool=True)
custodianship = QEnum('hsta', model_field=Waypoint.custodianship)
climbing_styles = QEnumArray('tcsty', model_field=Waypoint.climbing_styles)
access_time = QEnumRange('tappt',
model_field=Waypoint.access_time,
enum_mapper=sortable_access_times)
climbing_rating_max = QEnumRange('tmaxr',
model_field=Waypoint.climbing_rating_max,
enum_mapper=sortable_climbing_ratings)
climbing_rating_min = QEnumRange('tminr',
model_field=Waypoint.climbing_rating_min,
enum_mapper=sortable_climbing_ratings)
climbing_rating_median = QEnumRange(
'tmedr',
model_field=Waypoint.climbing_rating_median,
enum_mapper=sortable_climbing_ratings)
height_max = QInteger('tmaxh', range=True)
height_min = QInteger('tminh', range=True)
height_median = QInteger('tmedh', range=True)
routes_quantity = QInteger('rqua', range=True)
children_proof = QEnum('chil', model_field=Waypoint.children_proof)
rain_proof = QEnum('rain', model_field=Waypoint.rain_proof)
climbing_outdoor_types = QEnumArray(
'ctout', model_field=Waypoint.climbing_outdoor_types)
climbing_indoor_types = QEnumArray(
'ctin', model_field=Waypoint.climbing_indoor_types)
paragliding_rating = QEnumRange('pgrat',
model_field=Waypoint.paragliding_rating,
enum_mapper=sortable_paragliding_ratings)
exposition_rating = QEnumRange('pglexp',
model_field=Waypoint.exposition_rating,
enum_mapper=sortable_exposition_ratings)
length = QInteger('len', range=True)
weather_station_types = QEnumArray(
'whtyp', model_field=Waypoint.weather_station_types)
capacity = QInteger('hucap', range=True)
capacity_staffed = QInteger('hscap', range=True)
equipment_ratings = QEnumRange('anchq',
model_field=Waypoint.equipment_ratings,
enum_mapper=sortable_equipment_ratings)
public_transportation_types = QEnumArray(
'tpty', model_field=Waypoint.public_transportation_types)
public_transportation_rating = QEnum(
'tp', model_field=Waypoint.public_transportation_rating)
snow_clearance_rating = QEnum('psnow',
model_field=Waypoint.snow_clearance_rating)
product_types = QEnumArray('ftyp', model_field=Waypoint.product_types)
FIELDS = [
'elevation', 'prominence', 'waypoint_type', 'rock_types',
'orientations', 'climbing_outdoor_types', 'climbing_indoor_types',
'best_periods', 'lift_access', 'custodianship', 'climbing_styles',
'height_max', 'height_min', 'height_median', 'routes_quantity',
'children_proof', 'rain_proof', 'length', 'weather_station_types',
'capacity', 'capacity_staffed', 'public_transportation_types',
'public_transportation_rating', 'snow_clearance_rating',
'product_types'
]
ENUM_RANGE_FIELDS = [
'access_time', 'climbing_rating_max', 'climbing_rating_min',
'climbing_rating_median', 'paragliding_rating', 'exposition_rating',
'equipment_ratings'
]
@staticmethod
def to_search_document(document, index):
search_document = SearchDocument.to_search_document(document, index)
if document.redirects_to:
return search_document
SearchDocument.copy_fields(search_document, document,
SearchWaypoint.FIELDS)
SearchDocument.copy_enum_range_fields(search_document, document,
SearchWaypoint.ENUM_RANGE_FIELDS,
SearchWaypoint)
return search_document
class SearchDocument(DocType):
"""The base ElasticSearch mapping for documents. Each document type has
its own specific mapping.
We are using the "one language per field" strategy, for example for the
title field we have a field for each language: title_en, title_fr, ...
See also:
https://www.elastic.co/guide/en/elasticsearch/guide/current/one-lang-fields.html
For the search a different analyzer is used than for the indexing. This is
because the index analyzer uses n-grams, while the search words should
not be cut into n-gram tokens.
See also:
https://www.elastic.co/guide/en/elasticsearch/guide/current/_index_time_search_as_you_type.html
"""
class Meta(BaseMeta):
pass
id = Long()
doc_type = Enum()
quality = QEnum('qa', model_field=Document.quality)
available_locales = QEnumArray('l', enum=default_langs)
geom = GeoPoint()
# array of area ids
areas = QLong('a', is_id=True)
# fr
title_fr = String(analyzer='index_french', search_analyzer='search_french')
summary_fr = String(analyzer='index_french',
search_analyzer='search_french')
description_fr = String(analyzer='index_french',
search_analyzer='search_french')
# it
title_it = String(analyzer='index_italian',
search_analyzer='search_italian')
summary_it = String(analyzer='index_italian',
search_analyzer='search_italian')
description_it = String(analyzer='index_italian',
search_analyzer='search_italian')
# de
title_de = String(analyzer='index_german', search_analyzer='search_german')
summary_de = String(analyzer='index_german',
search_analyzer='search_german')
description_de = String(analyzer='index_german',
search_analyzer='search_german')
# en
title_en = String(analyzer='index_english',
search_analyzer='search_english')
summary_en = String(analyzer='index_english',
search_analyzer='search_english')
description_en = String(analyzer='index_english',
search_analyzer='search_english')
# es
title_es = String(analyzer='index_spanish',
search_analyzer='search_spanish')
summary_es = String(analyzer='index_spanish',
search_analyzer='search_spanish')
description_es = String(analyzer='index_spanish',
search_analyzer='search_spanish')
# ca
title_ca = String(analyzer='index_catalan',
search_analyzer='search_catalan')
summary_ca = String(analyzer='index_catalan',
search_analyzer='search_catalan')
description_ca = String(analyzer='index_catalan',
search_analyzer='search_catalan')
# eu
title_eu = String(analyzer='index_basque', search_analyzer='search_basque')
summary_eu = String(analyzer='index_basque',
search_analyzer='search_basque')
description_eu = String(analyzer='index_basque',
search_analyzer='search_basque')
@staticmethod
def to_search_document(document, index, include_areas=True):
search_document = {
'_index': index,
'_id': document.document_id,
'_type': document.type,
'id': document.document_id
}
if document.redirects_to:
# remove merged documents from the index
search_document['_op_type'] = 'delete'
else:
search_document['_op_type'] = 'index'
search_document['doc_type'] = document.type
available_locales = []
for locale in document.locales:
available_locales.append(locale.lang)
search_document['title_' + locale.lang] = locale.title
search_document['summary_' + locale.lang] = \
strip_bbcodes(locale.summary)
search_document['description_' + locale.lang] = \
strip_bbcodes(locale.description)
search_document['available_locales'] = available_locales
if document.geometry:
search_document['geom'] = SearchDocument.get_geometry(
document.geometry)
areas = []
if include_areas:
for area in document._areas:
areas.append(area.document_id)
search_document['areas'] = areas
return search_document
@staticmethod
def get_geometry(geometry):
if geometry.lon_lat:
geojson = json.loads(geometry.lon_lat)
return geojson['coordinates']
else:
return None
@staticmethod
def copy_fields(search_document, document, fields):
for field in fields:
search_document[field] = getattr(document, field)
class SearchRoute(SearchDocument):
class Meta(BaseMeta):
doc_type = ROUTE_TYPE
activities = QEnumArray('act', model_field=Route.activities)
elevation_min = QInteger('rmina', range=True)
elevation_max = QInteger('rmaxa', range=True)
height_diff_up = QInteger('hdif', range=True)
height_diff_down = QInteger('ddif', range=True)
route_length = QInteger('rlen', range=True)
difficulties_height = QInteger('ralt ', range=True)
height_diff_access = QInteger('rappr', range=True)
height_diff_difficulties = QInteger('dhei ', range=True)
route_types = QEnumArray('rtyp', model_field=Route.route_types)
orientations = QEnumArray('fac', model_field=Route.orientations)
durations = QEnumArray('time', model_field=Route.durations)
glacier_gear = QEnum('glac', model_field=Route.glacier_gear)
configuration = QEnumArray('conf', model_field=Route.configuration)
ski_rating = QEnum('trat', model_field=Route.ski_rating)
ski_exposition = QEnum('sexpo', model_field=Route.ski_exposition)
labande_ski_rating = QEnum('srat', model_field=Route.labande_ski_rating)
labande_global_rating = QEnum('lrat',
model_field=Route.labande_global_rating)
global_rating = QEnum('grat', model_field=Route.global_rating)
engagement_rating = QEnum('erat', model_field=Route.engagement_rating)
risk_rating = QEnum('orrat', model_field=Route.risk_rating)
equipment_rating = QEnum('prat', model_field=Route.equipment_rating)
ice_rating = QEnum('irat', model_field=Route.ice_rating)
mixed_rating = QEnum('mrat', model_field=Route.mixed_rating)
exposition_rock_rating = QEnum('rexpo',
model_field=Route.exposition_rock_rating)
rock_free_rating = QEnum('frat', model_field=Route.rock_free_rating)
rock_required_rating = QEnum('rrat',
model_field=Route.rock_required_rating)
aid_rating = QEnum('arat', model_field=Route.aid_rating)
via_ferrata_rating = QEnum('krat', model_field=Route.via_ferrata_rating)
hiking_rating = QEnum('hrat', model_field=Route.hiking_rating)
hiking_mtb_exposition = QEnum('hexpo',
model_field=Route.hiking_mtb_exposition)
snowshoe_rating = QEnum('wrat', model_field=Route.snowshoe_rating)
mtb_up_rating = QEnum('mbur', model_field=Route.mtb_up_rating)
mtb_down_rating = QEnum('mbdr', model_field=Route.mtb_down_rating)
mtb_length_asphalt = QInteger('mbroad', range=True)
mtb_length_trail = QInteger('mbtrack', range=True)
mtb_height_diff_portages = QInteger('mbpush', range=True)
rock_types = QEnumArray('rock', model_field=Route.rock_types)
climbing_outdoor_type = QEnumArray('crtyp',
model_field=Route.climbing_outdoor_type)
FIELDS = [
'activities', 'elevation_min', 'elevation_max', 'height_diff_up',
'height_diff_down', 'route_length', 'difficulties_height',
'height_diff_access', 'height_diff_difficulties', 'route_types',
'orientations', 'durations', 'glacier_gear', 'configuration',
'ski_rating', 'ski_exposition', 'labande_ski_rating',
'labande_global_rating', 'global_rating', 'engagement_rating',
'risk_rating', 'equipment_rating', 'ice_rating', 'mixed_rating',
'exposition_rock_rating', 'rock_free_rating', 'rock_required_rating',
'aid_rating', 'via_ferrata_rating', 'hiking_rating',
'hiking_mtb_exposition', 'snowshoe_rating', 'mtb_up_rating',
'mtb_down_rating', 'mtb_length_asphalt', 'mtb_length_trail',
'mtb_height_diff_portages', 'rock_types', 'climbing_outdoor_type'
]
@staticmethod
def to_search_document(document, index):
search_document = SearchDocument.to_search_document(document, index)
if document.redirects_to:
return search_document
SearchDocument.copy_fields(search_document, document,
SearchRoute.FIELDS)
for locale in document.locales:
search_document['title_' + locale.lang] = \
get_title(locale.title, locale.title_prefix)
return search_document