5-minute interval for visits

app/db.py

@@ -23,7 +23,7 @@
 
 class VisitStats(SQLModel, table=True):
     """
-    Table to record per-minute visit summaries.
+    Table to record per-interval visit summaries.
 
     All keys describing the platform are primary, so we have separate a usage record 
     coming from each source.
@@ -73,7 +73,7 @@ def get_visit_stats(
     end: datetime.datetime | None = None,
     limit: int | None = None,
 ) -> Sequence[VisitStats]:
-    """Return list of per-minute visit summary from the DB."""
+    """Return list of per-interval visit summary from the DB."""
     with Session(engine) as session:
         statement = select(VisitStats)
         if start:
@@ -105,9 +105,9 @@ def get_download_stats(
         return session.exec(statement).all()
 
 
-def insert_usage_stats(minute_summary: pd.DataFrame):
+def insert_usage_stats(visit_stats: pd.DataFrame):
     with Session(engine) as session:
-        for index, row in minute_summary.iterrows():
+        for index, row in visit_stats.iterrows():
             existing_entry = session.exec(
                 select(VisitStats).where(
                     VisitStats.start == row["start"]

app/main.py

@@ -165,7 +165,7 @@ async def persist_visits():
     return _persist_visits()
 
 
-def _summarize_visits() -> Response:
+def _summarize_visits(interval="5min") -> Response:
     """
     Summarize visits from the CSV file and write to the database
     """
@@ -179,30 +179,30 @@ def _summarize_visits() -> Response:
             na_filter=False,  # prevent empty strings from converting to nan or <NA>
         )
         df["start"] = pd.to_datetime(df["timestamp"])
-        df["end"] = df["start"] + pd.to_timedelta("1min")
+        df["end"] = df["start"] + pd.to_timedelta(interval)
         df["start"] = df["start"].dt.strftime("%Y-%m-%d %H:%M")
         df["end"] = df["end"].dt.strftime("%Y-%m-%d %H:%M")
         df["ci_environment"] = df["ci_environment"].apply(lambda val: strtobool(val) if val else False)
         df = df.drop(columns=["timestamp"])
 
-        # Summarize visits per user per minute
-        minute_summary = df.groupby(["start", "end"] + visit_fieldnames).size().reset_index(name="count")
-        if len(minute_summary) == 0:
+        # Summarize visits per user per time interval
+        interval_summary = df.groupby(["start", "end"] + visit_fieldnames).size().reset_index(name="count")
+        if len(interval_summary) == 0:
             return PlainTextResponse(content="No new visits to summarize")
 
-        logger.info(f"Summarizing {len(df)} visits in {CSV_FILE_PATH} and writing {len(minute_summary)} rows to the DB")
+        logger.info(f"Summarizing {len(df)} visits in {CSV_FILE_PATH} and writing {len(interval_summary)} rows to the DB")
         try:
-            db.insert_usage_stats(minute_summary)
+            db.insert_usage_stats(interval_summary)
         except Exception as e:
             return PlainTextResponse(
                 status_code=http.HTTPStatus.INTERNAL_SERVER_ERROR, 
                 content=f"Failed to write to the database: {e}",
             )
         else:
-            logger.info(f"Successfully wrote {len(minute_summary)} rows to the DB")
+            logger.info(f"Successfully wrote {len(interval_summary)} rows to the DB")
             open(CSV_FILE_PATH, "w").close()  # Clear the CSV file on successful write
             return PlainTextResponse(
-                content=f"Successfully summarized {len(df)} visits to {len(minute_summary)} per-minute entries",
+                content=f"Successfully summarized {len(df)} visits to {len(interval_summary)} per-interval entries",
             )