import falcon import psycopg2.extras from falcon_swagger_ui import register_swaggerui_app from .database import DatabaseManager from .stats import get_downloads, get_views from .util import set_statistics_scope, validate_post_parameters class RootResource: def on_get(self, req, resp): resp.status = falcon.HTTP_200 resp.content_type = "text/html" with open("dspace_statistics_api/docs/index.html", "r") as f: resp.body = f.read() class OpenAPIJSONResource: def on_get(self, req, resp): resp.status = falcon.HTTP_200 resp.content_type = "text/html" with open("dspace_statistics_api/docs/openapi.json", "r") as f: resp.body = f.read() class AllStatisticsResource: @falcon.before(set_statistics_scope) def on_get(self, req, resp): """Handles GET requests""" # Return HTTPBadRequest if id parameter is not present and valid limit = req.get_param_as_int("limit", min_value=1, max_value=100) or 100 page = req.get_param_as_int("page", min_value=0) or 0 offset = limit * page with DatabaseManager() as db: db.set_session(readonly=True) with db.cursor() as cursor: # get total number of communities/collections/items so we can estimate the pages cursor.execute(f"SELECT COUNT(id) FROM {req.context.statistics_scope}") pages = round(cursor.fetchone()[0] / limit) # get statistics and use limit and offset to page through results cursor.execute( f"SELECT id, views, downloads FROM {req.context.statistics_scope} ORDER BY id LIMIT %s OFFSET %s", [limit, offset], ) # create a list to hold dicts of stats statistics = list() # iterate over results and build statistics object for result in cursor: statistics.append( { "id": str(result["id"]), "views": result["views"], "downloads": result["downloads"], } ) message = { "currentPage": page, "totalPages": pages, "limit": limit, "statistics": statistics, } resp.media = message @falcon.before(set_statistics_scope) @falcon.before(validate_post_parameters) def on_post(self, req, resp): """Handles POST requests. Uses two `before` hooks to set the statistics "scope" and validate the POST parameters. The "scope" is the type of statistics we want, which will be items, communities, or collections, depending on the request. """ # Build the Solr date string, ie: [* TO *] if req.context.dateFrom and req.context.dateTo: solr_date_string = f"[{req.context.dateFrom} TO {req.context.dateTo}]" elif not req.context.dateFrom and req.context.dateTo: solr_date_string = f"[* TO {req.context.dateTo}]" elif req.context.dateFrom and not req.context.dateTo: solr_date_string = f"[{req.context.dateFrom} TO *]" else: solr_date_string = "[* TO *]" # Helper variables to make working with pages/items/results easier and # to make the code easier to understand number_of_elements: int = len(req.context.elements) pages: int = int(number_of_elements / req.context.limit) first_element: int = req.context.page * req.context.limit last_element: int = first_element + req.context.limit # Get a subset of the POSTed items based on our limit. Note that Python # list slicing and indexing are both zero based, but the first and last # items in a slice can be confusing. See this ASCII diagram: # # +---+---+---+---+---+---+ # | P | y | t | h | o | n | # +---+---+---+---+---+---+ # Slice position: 0 1 2 3 4 5 6 # Index position: 0 1 2 3 4 5 # # So if we have a list of items with 240 items: # # 1st set: items[0:100] would give items at indexes 0 to 99 # 2nd set: items[100:200] would give items at indexes 100 to 199 # 3rd set: items[200:300] would give items at indexes 200 to 239 elements_subset: list = req.context.elements[first_element:last_element] views: dict = get_views( solr_date_string, elements_subset, req.context.views_facet_field ) downloads: dict = get_downloads( solr_date_string, elements_subset, req.context.downloads_facet_field ) # create a list to hold dicts of stats statistics = list() # iterate over views dict to extract views and use the element id as an # index to the downloads dict to extract downloads. for k, v in views.items(): statistics.append({"id": k, "views": v, "downloads": downloads[k]}) message = { "currentPage": req.context.page, "totalPages": pages, "limit": req.context.limit, "statistics": statistics, } resp.status = falcon.HTTP_200 resp.media = message class SingleStatisticsResource: @falcon.before(set_statistics_scope) def on_get(self, req, resp, id_): """Handles GET requests""" # Adapt Python’s uuid.UUID type to PostgreSQL’s uuid # See: https://www.psycopg.org/docs/extras.html psycopg2.extras.register_uuid() with DatabaseManager() as db: db.set_session(readonly=True) with db.cursor() as cursor: cursor = db.cursor() cursor.execute( f"SELECT views, downloads FROM {req.context.database} WHERE id=%s", [str(id_)], ) if cursor.rowcount == 0: raise falcon.HTTPNotFound( title=f"{req.context.statistics_scope} not found", description=f'The {req.context.statistics_scope} with id "{str(id_)}" was not found.', ) else: results = cursor.fetchone() statistics = { "id": str(id_), "views": results["views"], "downloads": results["downloads"], } resp.media = statistics api = application = falcon.API() api.add_route("/", RootResource()) # Item routes api.add_route("/items", AllStatisticsResource()) api.add_route("/item/{id_:uuid}", SingleStatisticsResource()) # Community routes api.add_route("/communities", AllStatisticsResource()) api.add_route("/community/{id_:uuid}", SingleStatisticsResource()) # Collection routes api.add_route("/collections", AllStatisticsResource()) api.add_route("/collection/{id_:uuid}", SingleStatisticsResource()) # Swagger configuration SWAGGERUI_URL = "/swagger" # without trailing slash SCHEMA_URL = "/docs/openapi.json" api.add_route("/docs/openapi.json", OpenAPIJSONResource()) register_swaggerui_app( api, SWAGGERUI_URL, SCHEMA_URL, config={ "supportedSubmitMethods": ["get", "post"], }, ) # vim: set sw=4 ts=4 expandtab: