Add a gap detector to Sir Complainsalot

Detects gaps in reported data, e.g. if just one day is missing but more
recent days are available.

Author: capnrefsmmat

sir_complainsalot/delphi_sir_complainsalot/check_source.py

@@ -1,6 +1,8 @@
 from dataclasses import dataclass
 from typing import List
 
+import covidcast
+import numpy as np
 import pandas as pd
 
 @dataclass
@@ -27,33 +29,87 @@ def to_md(self):
             message=self.message, updated=self.last_updated.strftime("%Y-%m-%d"))
 
 def check_source(data_source, meta, params, grace):
-    """Iterate over all signals from a source and check if they exceed max age."""
+    """Iterate over all signals from a source and check for problems.
+
+    Possible problems:
+
+    - Newest available data exceeds max age.
+    - Gap between subsequent data points exceeds max gap.
+
+    For example, consider a source with a max age of 5 days and max gap of 1
+    day. If today is 2020-10-15, and the latest available data is from
+    2020-10-09, the max age is exceeded. If there is no data available on
+    2020-10-07, but there is on 2020-10-06 and 2020-10-08, there is a gap of 2
+    days and the max gap is exceeded.
+
+    The gap window controls how much data we check for gaps -- a gap window of
+    10 days means we check the most recent 10 days of data. Defaults to 7.
+
+    """
 
     source_config = params[data_source]
+    gap_window = pd.Timedelta(days=source_config.get("gap_window", 7))
+    max_allowed_gap = source_config.get("max_gap", 1)
 
     signals = meta[meta.data_source == data_source]
 
     now = pd.Timestamp.now()
 
-    complaints = {}
+    age_complaints = {}
+    gap_complaints = {}
 
     for _, row in signals.iterrows():
         if "retired-signals" in source_config and \
            row["signal"] in source_config["retired-signals"]:
             continue
 
+        # Check max age
         age = (now - row["max_time"]).days
 
         if age > source_config["max_age"] + grace:
-            if row["signal"] not in complaints:
-                complaints[row["signal"]] = Complaint(
+            if row["signal"] not in age_complaints:
+                age_complaints[row["signal"]] = Complaint(
                     "is more than {age} days old".format(age=age),
                     data_source,
                     row["signal"],
                     [row["geo_type"]],
                     row["max_time"],
                     source_config["maintainers"])
             else:
-                complaints[row["signal"]].geo_types.append(row["geo_type"])
+                age_complaints[row["signal"]].geo_types.append(row["geo_type"])
+
+        # Check max gap
+        if max_allowed_gap == -1:
+            # No gap detection for this source
+            continue
+
+        latest_data = covidcast.signal(
+            data_source, row["signal"],
+            start_day=row["max_time"] - gap_window,
+            end_day=row["max_time"],
+            geo_type=row["geo_type"]
+        )
+
+        # convert numpy datetime values to pandas datetimes and then to
+        # datetime.date, so we can work with timedeltas after
+        unique_dates = [pd.to_datetime(val).date()
+                        for val in latest_data["time_value"].unique()]
+
+        gap_days = [(day - prev_day).days
+                    for day, prev_day in zip(unique_dates[1:], unique_dates[:-1])]
+        gap = max(gap_days)
+
+        if gap > max_allowed_gap:
+            if row["signal"] not in gap_complaints:
+                gap_complaints[row["signal"]] = Complaint(
+                    "has a {gap}-day gap of missing data in its most recent "
+                    "{gap_window} days of data".format(gap=gap, gap_window=gap_window.days),
+                    data_source,
+                    row["signal"],
+                    [row["geo_type"]],
+                    row["max_time"],
+                    source_config["maintainers"])
+            else:
+                gap_complaints[row["signal"]].geo_types.append(row["geo_type"])
 
-    return list(complaints.values())
+    return list(age_complaints.values()) + list(gap_complaints.values())