def _find(request):
MaxFeatures = 50
params = _get_find_params(request)
if params.searchText is None:
raise exc.HTTPBadRequest('Please provide a searchText')
models = queryable_models_from_bodid(params.layer, params.searchField)
features = []
if models is None:
raise exc.HTTPBadRequest(
'No Vector Table was found for %s for searchField %s' %
(params.layer, params.searchField))
for model in models:
searchColumn = model.get_column_by_property_name(params.searchField)
query = request.db.query(model)
if params.contains:
query = full_text_search(query, [searchColumn], params.searchText)
else:
if isinstance(searchColumn.type, Date):
query = query.filter(
cast(searchColumn, Date) == params.searchText)
else:
searchText = _format_search_text(searchColumn.type,
params.searchText)
query = query.filter(searchColumn == searchText)
query = query.limit(MaxFeatures)
for feature in query:
f = _process_feature(feature, params)
features.append(f)
return {'results': features}
def _find(request):
MaxFeatures = 50
params = _get_find_params(request)
if params.searchText is None:
raise exc.HTTPBadRequest('Please provide a searchText')
models = models_from_name(params.layer)
features = []
findColumn = lambda x: (x, x.get_column_by_name(params.searchField))
if models is None:
raise exc.HTTPBadRequest('No Vector Table was found for %s' %
params.layer)
for model in models:
vectorModel, searchColumn = findColumn(model)
if searchColumn is None:
raise exc.HTTPBadRequest('Please provide an existing searchField')
query = request.db.query(vectorModel)
if params.contains:
query = full_text_search(query, [searchColumn], params.searchText)
else:
if isinstance(searchColumn.type, Date):
query = query.filter(
cast(searchColumn, Date) == params.searchText)
else:
searchText = _format_search_text(searchColumn.type,
params.searchText)
query = query.filter(searchColumn == searchText)
query = query.limit(MaxFeatures)
for feature in query:
f = _process_feature(feature, params)
features.append(f)
return {'results': features}
def metadata(request):
params = LayersParams(request)
model = get_bod_model(params.lang)
query = params.request.db.query(model)
query = _filter_on_chargeable_attr(params, query, model)
if params.searchText is not None:
query = full_text_search(query, [model.fullTextSearch, model.layerBodId, model.idGeoCat], params.searchText)
results = computeHeader(params.mapName)
for layer in get_layers_metadata_for_params(params, query, model):
results["layers"].append(layer)
return results
def metadata(request):
params = BaseLayersValidation(request)
model = get_bod_model(params.lang)
query = params.request.db.query(model)
query = _filter_on_chargeable_attr(params, query, model)
if params.searchText is not None:
query = full_text_search(
query, [model.fullTextSearch, model.layerBodId, model.idGeoCat],
params.searchText)
results = computeHeader(params.mapName, params.srid)
for layer in get_layers_metadata_for_params(params, query, model):
results['layers'].append(layer)
return results
def _find(request):
MaxFeatures = MAX_FEATURES
params = FindServiceValidation(request)
if params.searchText is None:
raise exc.HTTPBadRequest('Please provide a searchText')
models = queryable_models_from_bodid(params.layer,
params.searchField,
srid=params.srid)
features = []
if models is None:
raise exc.HTTPBadRequest(
'No Vector Table was found for %s for searchField %s' %
(params.layer, params.searchField))
vectorLayers = []
for model in models:
where_txt = None
if params.where is not None:
where_txt = format_query(model, params.where, params.lang)
vectorLayers.append((model, where_txt))
# Attributes in the 'where' or 'layerDefs' should match attributes in
# at least one model related to a layer bodId
if params.where is not None and not any(list(zip(*vectorLayers)[1])):
raise exc.HTTPBadRequest(
'Filtering on a not existing field on layer {}'.format(
params.layer))
for model, where_text in vectorLayers:
searchColumn = model.get_column_by_property_name(params.searchField)
query = request.db.query(model)
if params.contains:
query = full_text_search(query, [searchColumn], params.searchText)
else:
if isinstance(searchColumn.type, Date):
query = query.filter(
cast(searchColumn, Date) == params.searchText)
else:
searchText = _format_search_text(searchColumn.type,
params.searchText)
query = query.filter(searchColumn == searchText)
if where_txt is not None:
query = query.filter(
text("({})".format(where_txt) # operator precedance
))
query = query.limit(MaxFeatures)
for feature in query:
f = _process_feature(feature, params)
features.append(f)
return {'results': features}
def _find(request):
MaxFeatures = 50
params = _get_find_params(request)
if params.searchText is None:
raise exc.HTTPBadRequest('Please provide a searchText')
models = models_from_name(params.layer)
features = []
findColumn = lambda x: (x, x.get_column_by_property_name(params.searchField))
if models is None:
raise exc.HTTPBadRequest('No Vector Table was found for %s' % params.layer)
for model in models:
vectorModel, searchColumn = findColumn(model)
if searchColumn is None:
raise exc.HTTPBadRequest('Please provide an existing searchField')
query = request.db.query(vectorModel)
if params.contains:
query = full_text_search(
query,
[searchColumn],
params.searchText
)
else:
if isinstance(searchColumn.type, Date):
query = query.filter(
cast(searchColumn, Date) == params.searchText
)
else:
searchText = _format_search_text(searchColumn.type, params.searchText)
query = query.filter(
searchColumn == searchText
)
query = query.limit(MaxFeatures)
for feature in query:
f = _process_feature(feature, params)
features.append(f)
return {'results': features}
def _find(request):
MaxFeatures = 50
params = FindServiceValidation(request)
if params.searchText is None:
raise exc.HTTPBadRequest('Please provide a searchText')
models = queryable_models_from_bodid(params.layer, params.searchField, srid=params.srid)
features = []
if models is None:
raise exc.HTTPBadRequest(
'No Vector Table was found for %s for searchField %s' % (params.layer, params.searchField))
for model in models:
searchColumn = model.get_column_by_property_name(params.searchField)
query = request.db.query(model)
if params.contains:
query = full_text_search(
query,
[searchColumn],
params.searchText
)
else:
if isinstance(searchColumn.type, Date):
query = query.filter(
cast(searchColumn, Date) == params.searchText
)
else:
searchText = _format_search_text(searchColumn.type, params.searchText)
query = query.filter(
searchColumn == searchText
)
query = query.limit(MaxFeatures)
for feature in query:
f = _process_feature(feature, params)
features.append(f)
return {'results': features}
