def export_shape(dataset_name): """Route for /shapes/<shapeset>/ endpoint. Requires a dataset argument and can apply column specific filters to it. :param dataset_name: user provided name of target shapeset :returns: response object result of _export_shape """ # Find a way to work these into the validator, they shouldn't be out here. if dataset_name not in ShapeMetadata.tablenames(): return make_error(dataset_name + ' not found.', 404) try: ShapeMetadata.get_by_dataset_name(dataset_name).shape_table except NoSuchTableError: return make_error(dataset_name + ' has yet to be ingested.', 404) meta_params = ('shape', 'data_type', 'location_geom__within', 'job') request_args = request.args.to_dict() # Using the 'shape' key triggers the correct validator. request_args['shape'] = dataset_name validated_args = validate(ExportFormatsValidator(only=meta_params), request_args) if validated_args.errors: return bad_request(validated_args.errors) elif validated_args.data.get('job'): return make_job_response('export-shape', validated_args) else: query = _export_shape(validated_args) shapeset = validated_args.data.get('shapeset') data_type = validated_args.data.get('data_type') return export_dataset_to_response(shapeset, data_type, query)
def meta(): fields = ('obs_date__le', 'obs_date__ge', 'dataset_name', 'location_geom__within') validated_args = validate(NoDefaultDatesValidator(only=fields), request.args.to_dict()) if validated_args.errors: return bad_request(validated_args.errors) return _meta(validated_args)
def export_shape(dataset_name): """Route for /shapes/<shapeset>/ endpoint. Requires a dataset argument and can apply column specific filters to it. :param dataset_name: user provided name of target shapeset :returns: response object result of _export_shape """ # Find a way to work these into the validator, they shouldn't be out here. if dataset_name not in ShapeMetadata.tablenames(): return make_error(dataset_name + ' not found.', 404) try: ShapeMetadata.get_by_dataset_name(dataset_name).shape_table except NoSuchTableError: return make_error(dataset_name + ' has yet to be ingested.', 404) meta_params = ('shape', 'data_type', 'location_geom__within', 'job') request_args = request.args.to_dict() # Using the 'shape' key triggers the correct validator. request_args['shape'] = dataset_name validated_args = validate( ExportFormatsValidator(only=meta_params), request_args ) if validated_args.errors: return bad_request(validated_args.errors) elif validated_args.data.get('job'): return make_job_response('export-shape', validated_args) else: query = _export_shape(validated_args) shapeset = validated_args.data.get('shapeset') data_type = validated_args.data.get('data_type') return export_dataset_to_response(shapeset, data_type, query)
def detail_aggregate(): fields = ('location_geom__within', 'dataset_name', 'agg', 'obs_date__ge', 'obs_date__le', 'data_type') validator = NoGeoJSONDatasetRequiredValidator(only=fields) validated_args = validate(validator, request.args.to_dict()) if validated_args.errors: return bad_request(validated_args.errors) return _detail_aggregate(validated_args)
def grid(): fields = ('dataset_name', 'resolution', 'buffer', 'obs_date__le', 'obs_date__ge', 'location_geom__within') validated_args = validate(DatasetRequiredValidator(only=fields), request.args.to_dict()) if validated_args.errors: return bad_request(validated_args.errors) return _grid(validated_args)
def timeseries(): fields = ('location_geom__within', 'dataset_name', 'dataset_name__in', 'agg', 'obs_date__ge', 'obs_date__le', 'data_type') validator = NoGeoJSONValidator(only=fields) validated_args = validate(validator, request.args.to_dict()) if validated_args.errors: return bad_request(validated_args.errors) return _timeseries(validated_args)
def detail(): fields = ('location_geom__within', 'dataset_name', 'shape', 'obs_date__ge', 'obs_date__le', 'data_type', 'offset', 'date__time_of_day_ge', 'date__time_of_day_le', 'limit') validator = DatasetRequiredValidator(only=fields) validated_args = validate(validator, request.args.to_dict()) if validated_args.errors: return bad_request(validated_args.errors) return _detail(validated_args)
def meta(): fields = ('obs_date__le', 'obs_date__ge', 'dataset_name', 'location_geom__within', 'job') validator_result = validate(NoDefaultDatesValidator(only=fields), request.args.to_dict()) if validator_result.errors: return api_response.bad_request(validator_result.errors) if validator_result.data.get('job'): return make_job_response('meta', validator_result) else: result_data = _meta(validator_result) return api_response.meta_response(result_data, validator_result)
def aggregate_point_data(point_dataset_name, polygon_dataset_name): params = request.args.copy() # Doesn't this override the path-derived parameter with a query parameter? # Do we want that? if not params.get('shape'): # form_detail_query expects to get info about a shape dataset this way. params['shape'] = polygon_dataset_name params['dataset_name'] = point_dataset_name args = validate(DatasetRequiredValidator(), params) if args.errors: return bad_request(args.errors) # Apply standard filters to point dataset # And join each point to the containing shape q = form_detail_sql_query(args, True) q = q.add_columns(func.count(args.data['dataset'].c.hash)) # Apply a bounding box filter in case a geom was provided geom = args.data['geom'] dataset = args.data['dataset'] if geom: intersection = dataset.c.geom.ST_Within( func.ST_GeomFromGeoJSON(geom) ) q = q.filter(intersection) # Page in RESPONSE_LIMIT chunks # This seems contradictory. Don't we want one row per shape, no matter what? offset = args.data['offset'] q = q.limit(RESPONSE_LIMIT) if offset > 0: q = q.offset(offset) res_cols = [] columns = [str(col) for col in args.data['dataset'].columns] columns += [str(col) for col in args.data['shape'].columns] for col in columns: col = col.split('.') if col[0] == polygon_dataset_name: res_cols.append(col[1]) res_cols.append('count') rows = [OrderedDict(zip(res_cols, res)) for res in q.all()] if params.get('data_type') == 'csv': resp = form_csv_detail_response(['hash', 'ogc_fid'], rows) else: resp = form_geojson_detail_response(['hash', 'ogc_fid'], args, rows) return resp
def aggregate_point_data(point_dataset_name, polygon_dataset_name): consider = ('dataset_name', 'shape', 'obs_date__ge', 'obs_date__le', 'data_type', 'location_geom__within') request_args = request.args.to_dict() request_args['dataset_name'] = point_dataset_name request_args['shape'] = polygon_dataset_name validated_args = validate(Validator(only=consider), request_args) if validated_args.errors: return bad_request(validated_args.errors) return _aggregate_point_data(validated_args)
def detail_aggregate(): fields = ('location_geom__within', 'dataset_name', 'agg', 'obs_date__ge', 'obs_date__le', 'data_type', 'job') validator = NoGeoJSONDatasetRequiredValidator(only=fields) validator_result = validate(validator, request.args.to_dict()) if validator_result.errors: return api_response.bad_request(validator_result.errors) if validator_result.data.get('job'): return make_job_response('detail-aggregate', validator_result) else: time_counts = _detail_aggregate(validator_result) return api_response.detail_aggregate_response(time_counts, validator_result)
def meta(): fields = ('obs_date__le', 'obs_date__ge', 'dataset_name', 'location_geom__within', 'job') validator_result = validate(NoDefaultDatesValidator(only=fields), request.args.to_dict()) if validator_result.errors: return api_response.bad_request(validator_result.errors) if validator_result.data.get('job'): return make_job_response('meta', validator_result) else: result_data = _meta(validator_result) return api_response.meta_response(result_data, validator_result)
def dataset_fields(dataset_name): request_args = request.args.to_dict() request_args['dataset_name'] = dataset_name fields = ('obs_date__le', 'obs_date__ge', 'dataset_name', 'job') validator = DatasetRequiredValidator(only=fields) validator_result = validate(validator, request_args) if validator_result.errors: return api_response.bad_request(validator_result.errors) if validator_result.data.get('job'): return make_job_response('fields', validator_result) else: result_data = _meta(validator_result) return api_response.fields_response(result_data, validator_result)
def detail_aggregate(): fields = ('location_geom__within', 'dataset_name', 'agg', 'obs_date__ge', 'obs_date__le', 'data_type', 'job') validator = NoGeoJSONDatasetRequiredValidator(only=fields) validator_result = validate(validator, request.args.to_dict()) if validator_result.errors: return api_response.bad_request(validator_result.errors) if validator_result.data.get('job'): return make_job_response('detail-aggregate', validator_result) else: time_counts = _detail_aggregate(validator_result) return api_response.detail_aggregate_response(time_counts, validator_result)
def detail(): fields = ('location_geom__within', 'dataset_name', 'shape', 'obs_date__ge', 'obs_date__le', 'data_type', 'offset', 'date__time_of_day_ge', 'date__time_of_day_le', 'limit', 'job') validator = DatasetRequiredValidator(only=fields) validator_result = validate(validator, request.args.to_dict()) if validator_result.errors: return api_response.bad_request(validator_result.errors) if validator_result.data.get('job'): return make_job_response('detail', validator_result) else: result_rows = _detail(validator_result) return api_response.detail_response(result_rows, validator_result)
def detail(): fields = ('location_geom__within', 'dataset_name', 'shape', 'obs_date__ge', 'obs_date__le', 'data_type', 'offset', 'date__time_of_day_ge', 'date__time_of_day_le', 'limit', 'job') validator = DatasetRequiredValidator(only=fields) validator_result = validate(validator, request.args.to_dict()) if validator_result.errors: return api_response.bad_request(validator_result.errors) if validator_result.data.get('job'): return make_job_response('detail', validator_result) else: result_rows = _detail(validator_result) return api_response.detail_response(result_rows, validator_result)
def dataset_fields(dataset_name): request_args = request.args.to_dict() request_args['dataset_name'] = dataset_name fields = ('obs_date__le', 'obs_date__ge', 'dataset_name', 'job') validator = DatasetRequiredValidator(only=fields) validator_result = validate(validator, request_args) if validator_result.errors: return api_response.bad_request(validator_result.errors) if validator_result.data.get('job'): return make_job_response('fields', validator_result) else: result_data = _meta(validator_result) return api_response.fields_response(result_data, validator_result)
def dataset_fields(dataset_name): request_args = request.args.to_dict() request_args['dataset_name'] = dataset_name fields = ('obs_date__le', 'obs_date__ge', 'dataset_name') validator = DatasetRequiredValidator(only=fields) validated_args = validate(validator, request_args) if validated_args.errors: return bad_request(validated_args.errors) response = _meta(validated_args) # API defines column values to be in the 'objects' list. resp_dict = json.loads(response.data) resp_dict['objects'] = resp_dict['objects'][0]['columns'] response.data = json.dumps(resp_dict) return response
def aggregate_point_data(point_dataset_name, polygon_dataset_name): consider = ('dataset_name', 'shape', 'obs_date__ge', 'obs_date__le', 'data_type', 'location_geom__within', 'job') request_args = request.args.to_dict() request_args['dataset_name'] = point_dataset_name request_args['shape'] = polygon_dataset_name validated_args = validate(Validator(only=consider), request_args) if validated_args.errors: return bad_request(validated_args.errors) elif validated_args.data.get('job'): return make_job_response('aggregate-point-data', validated_args) else: result = _aggregate_point_data(validated_args) data_type = validated_args.data.get('data_type') return aggregate_point_data_response( data_type, result, [polygon_dataset_name, point_dataset_name])
def datadump_view(): fields = ('location_geom__within', 'dataset_name', 'shape', 'obs_date__ge', 'obs_date__le', 'offset', 'date__time_of_day_ge', 'date__time_of_day_le', 'limit', 'job', 'data_type') validator = DatasetRequiredValidator(only=fields) validator_result = validate(validator, request.args.to_dict()) if validator_result.errors: return api_response.error(validator_result.errors, 400) stream = datadump(**validator_result.data) dataset = validator_result.data['dataset'].name fmt = validator_result.data['data_type'] content_disposition = 'attachment; filename={}.{}'.format(dataset, fmt) attachment = Response(stream_with_context(stream), mimetype='text/%s' % fmt) attachment.headers['Content-Disposition'] = content_disposition return attachment
def datadump_view(): fields = ('location_geom__within', 'dataset_name', 'shape', 'obs_date__ge', 'obs_date__le', 'offset', 'date__time_of_day_ge', 'date__time_of_day_le', 'limit', 'job', 'data_type') validator = DatasetRequiredValidator(only=fields) validator_result = validate(validator, request.args.to_dict()) if validator_result.errors: return api_response.error(validator_result.errors, 400) stream = datadump(**validator_result.data) dataset = validator_result.data['dataset'].name fmt = validator_result.data['data_type'] content_disposition = 'attachment; filename={}.{}'.format(dataset, fmt) attachment = Response(stream_with_context(stream), mimetype='text/%s' % fmt) attachment.headers['Content-Disposition'] = content_disposition return attachment
def aggregate_point_data(point_dataset_name, polygon_dataset_name): consider = ('dataset_name', 'shape', 'obs_date__ge', 'obs_date__le', 'data_type', 'location_geom__within', 'job') request_args = request.args.to_dict() request_args['dataset_name'] = point_dataset_name request_args['shape'] = polygon_dataset_name validated_args = validate(Validator(only=consider), request_args) if validated_args.errors: return bad_request(validated_args.errors) elif validated_args.data.get('job'): return make_job_response('aggregate-point-data', validated_args) else: result = _aggregate_point_data(validated_args) data_type = validated_args.data.get('data_type') return aggregate_point_data_response( data_type, result, [polygon_dataset_name, point_dataset_name] )
def grid(): fields = ( 'dataset', 'dataset_name', 'resolution', 'buffer', 'obs_date__le', 'obs_date__ge', 'location_geom__within', ) validator = PointsetRequiredValidator(only=fields) validator_result = validate(validator, request.args) if validator_result.errors: return api_response.bad_request(validator_result.errors) results = _grid(validator_result) query = validator.dumps(validator_result.data) query = json.loads(query.data) results['properties'] = query return jsonify(results)
def grid(): fields = ( 'dataset', 'dataset_name', 'resolution', 'buffer', 'obs_date__le', 'obs_date__ge', 'location_geom__within', ) validator = PointsetRequiredValidator(only=fields) validator_result = validate(validator, request.args) if validator_result.errors: return api_response.bad_request(validator_result.errors) results = _grid(validator_result) query = validator.dumps(validator_result.data) query = json.loads(query.data) results['properties'] = query return jsonify(results)