Fix new date for google symptoms

google_symptoms/delphi_google_symptoms/date_utils.py

@@ -73,24 +73,29 @@ def generate_num_export_days(params: Dict, logger) -> [int]:
         "_".join([metric, smoother, "search"]) for metric, smoother in product(COMBINED_METRIC, SMOOTHERS)
     )
 
-    # Fetch metadata to check how recent each signal is
-    covidcast.use_api_key(params["indicator"]["api_credentials"])
-    metadata = covidcast.metadata()
-    # Filter to only those signals we currently want to produce for `google-symptoms`
-    gs_metadata = metadata[(metadata.data_source == "google-symptoms") & (metadata.signal.isin(sensor_names))]
-
     num_export_days = params["indicator"]["num_export_days"]
     custom_run = False if not params["common"].get("custom_run") else params["common"].get("custom_run", False)
 
     if num_export_days is None and not custom_run:
+        # Fetch metadata to check how recent each signal is
+        covidcast.use_api_key(params["indicator"]["api_credentials"])
+        metadata = covidcast.metadata()
+        # Filter to only those signals we currently want to produce for `google-symptoms`
+        gs_metadata = metadata[(metadata.data_source == "google-symptoms") & (metadata.signal.isin(sensor_names))]
+
         if sensor_names.difference(set(gs_metadata.signal)):
             # If any signal not in metadata yet, we need to backfill its full history.
             logger.warning("Signals missing in the epidata; backfilling full history")
             num_export_days = (export_end_date - FULL_BKFILL_START_DATE).days + 1
         else:
             latest_date_diff = (datetime.today() - to_datetime(min(gs_metadata.max_time))).days + 1
-            global_max_expected_lag = get_max_lag(params)
-            expected_date_diff = params["validation"]["common"].get("span_length", 14) + global_max_expected_lag
+
+            expected_date_diff = params["validation"]["common"].get("span_length", 14)
+
+            # there's an expected lag of 4 days behind if running from today
+            if export_end_date.date() == datetime.today().date():
+                global_max_expected_lag = get_max_lag(params)
+                expected_date_diff += global_max_expected_lag
 
             if latest_date_diff > expected_date_diff:
                 logger.info(f"Missing dates from: {to_datetime(min(gs_metadata.max_time)).date()}")

google_symptoms/delphi_google_symptoms/patch.py

@@ -71,7 +71,7 @@ def patch(params):
 
         # Output dir setup
         current_issue_yyyymmdd = issue_date.strftime("%Y%m%d")
-        current_issue_dir = f"""{params["patch"]["patch_dir"]}/issue_{current_issue_yyyymmdd}/google-symptom"""
+        current_issue_dir = f"""{params["patch"]["patch_dir"]}/issue_{current_issue_yyyymmdd}/google-symptoms"""
         makedirs(f"{current_issue_dir}", exist_ok=True)
 
         params["common"]["export_dir"] = f"""{current_issue_dir}"""

google_symptoms/delphi_google_symptoms/pull.py

@@ -248,10 +248,10 @@ def pull_gs_data(credentials, export_start_date, export_end_date, num_export_day
 
     # For state level data
     dfs["state"] = pull_gs_data_one_geolevel("state", retrieve_dates)
-
     # For county level data
     dfs["county"] = pull_gs_data_one_geolevel("county", retrieve_dates)
 
+
     # Add District of Columbia as county
     try:
         df_dc_county = dfs["state"][dfs["state"]["geo_id"] == "dc"].drop(
@@ -260,5 +260,4 @@ def pull_gs_data(credentials, export_start_date, export_end_date, num_export_day
         dfs["county"] = pd.concat([dfs["county"], df_dc_county])
     except KeyError:
         pass
-
     return dfs

google_symptoms/delphi_google_symptoms/run.py

@@ -5,13 +5,13 @@
 when the module is run with `python -m delphi_google_symptoms`.
 """
 import time
-from datetime import datetime, date
+from datetime import date, datetime
 from itertools import product
 
 import numpy as np
 from delphi_utils import create_export_csv, get_structured_logger
 
-from .constants import COMBINED_METRIC, GEO_RESOLUTIONS, SMOOTHERS, SMOOTHERS_MAP
+from .constants import COMBINED_METRIC, FULL_BKFILL_START_DATE, GEO_RESOLUTIONS, SMOOTHERS, SMOOTHERS_MAP
 from .date_utils import generate_num_export_days
 from .geo import geo_map
 from .pull import pull_gs_data
@@ -47,7 +47,9 @@ def run_module(params, logger=None):
             log_exceptions=params["common"].get("log_exceptions", True),
         )
 
-    export_start_date = datetime.strptime(params["indicator"]["export_start_date"], "%Y-%m-%d")
+    export_start_date = datetime.strptime(
+        params["indicator"].get("export_start_date", datetime.strftime(FULL_BKFILL_START_DATE, "%Y-%m-%d")), "%Y-%m-%d"
+    )
     # If end_date not specified, use current date.
     export_end_date = datetime.strptime(
         params["indicator"].get("export_end_date", datetime.strftime(date.today(), "%Y-%m-%d")), "%Y-%m-%d"

google_symptoms/setup.py

@@ -14,6 +14,7 @@
     "pylint==2.8.3",
     "pytest-cov",
     "pytest",
+    "pytest-freezegun~=0.4.2"
 ]
 
 setup(

google_symptoms/tests/conftest.py

@@ -1,11 +1,13 @@
 # -*- coding: utf-8 -*-
 import logging
 from pathlib import Path
+import re
 
 import copy
 import pytest
 import mock
 import pandas as pd
+from freezegun import freeze_time
 
 from os import listdir, remove, makedirs
 from os.path import join, exists
@@ -27,7 +29,7 @@
 #     end as open_covid_region_code,
 #     *
 # from `bigquery-public-data.covid19_symptom_search.states_daily_2020` # States by day
-# where timestamp(date) between timestamp("2020-07-26") and timestamp("2020-08-11")
+# where timestamp(date) between timestamp("2020-07-15") and timestamp("2020-08-22")
 
 # County data is created by running the following query in the BigQuery
 # browser console:
@@ -38,17 +40,21 @@
 #     end as open_covid_region_code,
 #     *
 # from `bigquery-public-data.covid19_symptom_search.counties_daily_2020` # Counties by day; includes state and county name, + FIPS code
-# where timestamp(date) between timestamp("2020-07-26") and timestamp("2020-08-11")
+# where timestamp(date) between timestamp("2020-07-15") and timestamp("2020-08-22")
+
+# good_input = {
+#     "state": f"{TEST_DIR}/test_data/small_states_daily.csv",
+#     "county": f"{TEST_DIR}/test_data/small_counties_daily.csv"
+# }
+
 
 good_input = {
-    "state": f"{TEST_DIR}/test_data/small_states_daily.csv",
-    "county": f"{TEST_DIR}/test_data/small_counties_daily.csv"
+    "state": f"{TEST_DIR}/test_data/small_states_2020_07_15_2020_08_22.csv",
+    "county": f"{TEST_DIR}/test_data/small_counties_2020_07_15_2020_08_22.csv"
 }
 
 patch_input = {
     "state": f"{TEST_DIR}/test_data/state_2024-05-16_2024-07-18.csv",
-    "county": f"{TEST_DIR}/test_data/county_2024-05-16_2024-07-18.csv"
-
 }
 
 symptom_names = ["symptom_" +
@@ -79,9 +85,9 @@ def params():
             "log_filename": f"{TEST_DIR}/test.log",
         },
         "indicator": {
-            "export_start_date": "2020-02-20",
             "bigquery_credentials": {},
             "num_export_days": 14,
+            "custom_run": False,
             "static_file_dir": "../static",
             "api_credentials": "fakesecret"
         },
@@ -124,7 +130,22 @@ def run_as_module(params):
 
     with mock.patch("delphi_google_symptoms.pull.initialize_credentials",
                     return_value=None), \
-         mock.patch("pandas_gbq.read_gbq", side_effect=[state_data, county_data]), \
+         mock.patch("pandas_gbq.read_gbq") as mock_read_gbq, \
          mock.patch("delphi_google_symptoms.pull.initialize_credentials", return_value=None), \
          mock.patch("delphi_google_symptoms.date_utils.covidcast.metadata", return_value=covidcast_metadata):
-            delphi_google_symptoms.run.run_module(params)
+        def side_effect(*args, **kwargs):
+            if "symptom_search_sub_region_1_daily" in args[0]:
+                df = state_data
+                pattern = re.compile(r'\d{4}-\d{2}-\d{2}')
+                start_date, end_date = re.findall(pattern, args[0])
+                return df[(df["date"] >= start_date) & (df["date"] <= end_date)]
+            elif "symptom_search_sub_region_2_daily" in args[0]:
+                df = county_data
+                pattern = re.compile(r'\d{4}-\d{2}-\d{2}')
+                start_date, end_date = re.findall(pattern, args[0])
+                return df[(df["date"] >= start_date) & (df["date"] <= end_date)]
+            else:
+                return pd.DataFrame()
+
+        mock_read_gbq.side_effect = side_effect
+        delphi_google_symptoms.run.run_module(params)