Add validation rules to PrevalenceAllLineagesByLocationHandler parame…

…ters

Add validation rules to PrevalenceByLocationAndTimeHandler

web/handlers/genomics/util.py

@@ -299,14 +299,6 @@ def get_total_hits(d): # To account for difference in ES versions 7.12.0 vs 6.8.
     return d["hits"]["total"]["value"] if isinstance(d["hits"]["total"], dict) else d["hits"]["total"]
 
 
-def validate_iso_date(date_str):
-    try:
-        dt.strptime(date_str, '%Y-%m-%d')
-        return True
-    except ValueError:
-        return False
-
-
 def create_date_range_filter(field_name, min_date=None, max_date=None):
     date_range_filter = {"range": {field_name: {}}}
     if not max_date and not min_date:

web/handlers/v2/genomics/prevalence_all_lineages_by_location.py

@@ -1,7 +1,6 @@
 from datetime import datetime as dt, timedelta
 
 import pandas as pd
-from tornado.web import HTTPError
 
 from web.handlers.genomics.base import BaseHandler
 from web.handlers.genomics.util import (
@@ -12,47 +11,35 @@
     get_major_lineage_prevalence,
     parse_location_id_to_query,
     parse_time_window_to_query,
-    validate_iso_date,
 )
 
 
 class PrevalenceAllLineagesByLocationHandler(BaseHandler):
     name = "prevalence-by-location-all-lineages"
     kwargs = dict(BaseHandler.kwargs)
     kwargs["GET"] = {
-        "location_id": {"type": str, "default": None},
-        "window": {"type": str, "default": None},
-        "other_threshold": {"type": float, "default": 0.05},
-        "nday_threshold": {"type": float, "default": 10},
-        "ndays": {"type": float, "default": 180},
+        "location_id": {"type": str, "required": True},
+        "window": {"type": int, "default": None, "min": 1},
+        "other_threshold": {"type": float, "default": 0.05, "min": 0, "max": 1},
+        "nday_threshold": {"type": int, "default": 10, "min": 1},
+        "ndays": {"type": int, "default": 180, "min": 1},
         "other_exclude": {"type": str, "default": None},
-        "cumulative": {"type": str, "default": None},
-        "min_date": {"type": str, "default": None},
-        "max_date": {"type": str, "default": None},
+        "cumulative": {"type": bool, "default": False},
+        "min_date": {"type": str, "default": None, "date_format": "%Y-%m-%d"},
+        "max_date": {"type": str, "default": None, "date_format": "%Y-%m-%d"},
     }
 
     async def _get(self):
         query_location = self.args.location_id
         query_window = self.args.window
-        query_window = int(query_window) if query_window is not None else None
         query_other_threshold = self.args.other_threshold
-        query_other_threshold = float(query_other_threshold)
         query_nday_threshold = self.args.nday_threshold
-        query_nday_threshold = float(query_nday_threshold)
         query_ndays = self.args.ndays
-        query_ndays = int(query_ndays)
         query_other_exclude = self.args.other_exclude
         query_other_exclude = (
             query_other_exclude.split(",") if query_other_exclude is not None else []
         )
         query_cumulative = self.args.cumulative
-        query_cumulative = True if query_cumulative == "true" else False
-        if self.args.max_date:
-            if not validate_iso_date(self.args.max_date):
-                raise HTTPError(400, reason="Invalid max_date format")
-        if self.args.min_date:
-            if not validate_iso_date(self.args.min_date):
-                raise HTTPError(400, reason="Invalid min_date format")
         query = {
             "size": 0,
             "query": {},

web/handlers/v2/genomics/prevalence_by_location_and_time.py

@@ -1,25 +1,22 @@
-from tornado.web import HTTPError
-
 from web.handlers.genomics.base import BaseHandler
 from web.handlers.genomics.util import (
     create_iterator,
     create_nested_mutation_query,
     parse_location_id_to_query,
     transform_prevalence,
-    validate_iso_date,
 )
 
 
 class PrevalenceByLocationAndTimeHandler(BaseHandler):
     name = "prevalence-by-location"
     kwargs = dict(BaseHandler.kwargs)
     kwargs["GET"] = {
-        "pangolin_lineage": {"type": str, "default": None},
+        "pangolin_lineage": {"type": str, "required": True},
         "mutations": {"type": str, "default": None},
         "location_id": {"type": str, "default": None},
-        "cumulative": {"type": str, "default": None},
-        "min_date": {"type": str, "default": None},
-        "max_date": {"type": str, "default": None},
+        "cumulative": {"type": bool, "default": False},
+        "min_date": {"type": str, "default": None, "date_format": "%Y-%m-%d"},
+        "max_date": {"type": str, "default": None, "date_format": "%Y-%m-%d"},
     }
 
     async def _get(self):
@@ -31,15 +28,10 @@ async def _get(self):
         query_mutations = self.args.mutations
         query_mutations = query_mutations.split(" AND ") if query_mutations is not None else []
         cumulative = self.args.cumulative
-        cumulative = True if cumulative == "true" else False
         date_range_filter = {"query": {"range": {"date_collected": {}}}}
         if self.args.max_date:
-            if not validate_iso_date(self.args.max_date):
-                raise HTTPError(400, reason="Invalid max_date format")
             date_range_filter["query"]["range"]["date_collected"]["lte"] = self.args.max_date
         if self.args.min_date:
-            if not validate_iso_date(self.args.min_date):
-                raise HTTPError(400, reason="Invalid min_date format")
             date_range_filter["query"]["range"]["date_collected"]["gte"] = self.args.min_date
 
         results = {}
@@ -65,7 +57,9 @@ async def _get(self):
             query_obj = create_nested_mutation_query(
                 lineages=lineages, mutations=j, location_id=query_location
             )
-            query["aggs"]["prevalence"]["aggs"]["count"]["aggs"]["lineage_count"]["filter"] = query_obj
+            query["aggs"]["prevalence"]["aggs"]["count"]["aggs"]["lineage_count"][
+                "filter"
+            ] = query_obj
             # import json
             # print(json.dumps(query))
             resp = await self.asynchronous_fetch(query)