chore(cache): increase cache duration for station data

setting the cache to 1 hour seems like a good balance between
performance and data freshness.

Author: lalver1

pems_data/src/pems_data/services/stations.py

@@ -80,7 +80,7 @@ def get_imputed_agg_5min(self, station_id: str) -> pd.DataFrame:
             value (pandas.DataFrame): The station's data as a DataFrame.
         """
 
-        cache_opts = {"key": self._build_cache_key("imputed", "agg", "5m", "station", station_id), "ttl": 300}  # 5 minutes
+        cache_opts = {"key": self._build_cache_key("imputed", "agg", "5m", "station", station_id), "ttl": 3600}  # 1 hour
         columns = [
             "STATION_ID",
             "LANE",

pems_streamlit/src/pems_streamlit/apps/districts/app_stations.py

@@ -34,7 +34,7 @@ def match(m: re.Match):
     return S3.get_prefixes(pattern, initial_prefix=STATIONS.imputation_detector_agg_5min, match_func=match)
 
 
-@st.cache_data(ttl=300)  # Cache for 5 minutes
+@st.cache_data(ttl=3600)  # Cache for 1 hour
 def load_station_data(station_id: str) -> pd.DataFrame:
     """
     Loads station data for a specific station.

tests/pytest/pems_data/services/test_stations.py

@@ -74,6 +74,6 @@ def test_get_imputed_agg_5min(self, service: StationsService, data_source: IData
 
         cache_opts = data_source.read.call_args.kwargs["cache_opts"]
         assert station_id in cache_opts["key"]
-        assert cache_opts["ttl"] == 300
+        assert cache_opts["ttl"] == 3600
 
         pd.testing.assert_frame_equal(result, df)