diff --git a/nowcast/.pylintrc b/nowcast/.pylintrc
index 90d5d3f91..786c72eb8 100644
--- a/nowcast/.pylintrc
+++ b/nowcast/.pylintrc
@@ -16,9 +16,9 @@ disable=logging-format-interpolation,
 [BASIC]
 
 # Allow arbitrarily short-named variables.
-variable-rgx=[a-z_][a-z0-9_]*
-argument-rgx=[a-z_][a-z0-9_]*
-attr-rgx=[a-z_][a-z0-9_]*
+variable-rgx=[A-Za-z_][a-z0-9_]*
+argument-rgx=[A-Za-z_][a-z0-9_]*
+attr-rgx=[A-Za-z_][a-z0-9_]*
 
 [DESIGN]
 
diff --git a/nowcast/delphi_nowcast/deconvolution/deconvolution.py b/nowcast/delphi_nowcast/deconvolution/deconvolution.py
index dd6b00f61..03e4a9c08 100644
--- a/nowcast/delphi_nowcast/deconvolution/deconvolution.py
+++ b/nowcast/delphi_nowcast/deconvolution/deconvolution.py
@@ -74,7 +74,7 @@ def deconvolve_double_smooth_ntf(
     x_k = None
     alpha_0 = np.zeros(n - k - 1)
     u_0 = np.zeros(n - k - 1)
-    for t in range(n_iters):
+    for _ in range(n_iters):
         x_k = x_update_1 @ (Cty + rho * D.T @ (alpha_0 + u_0))
         Dx = D @ x_k
         alpha_k = _soft_thresh(Dx - u_0, lam / rho)
diff --git a/nowcast/delphi_nowcast/deconvolution/ground_truth.py b/nowcast/delphi_nowcast/deconvolution/ground_truth.py
deleted file mode 100644
index f251771f7..000000000
--- a/nowcast/delphi_nowcast/deconvolution/ground_truth.py
+++ /dev/null
@@ -1,47 +0,0 @@
-"""Functions to construct the ground truth for a given location."""
-from datetime import date
-from typing import List, Dict, Tuple
-
-import numpy as np
-
-from .deconvolution import deconvolve_double_smooth_tf_cv
-from ..constants import Default
-from ..data_containers import LocationSeries, SensorConfig
-from ..epidata import get_historical_sensor_data, get_indicator_data, export_to_csv
-
-
-def construct_truths(start_date: date,
-                     end_date: date,
-                     as_of: date,  # most likely today
-                     truth: SensorConfig,
-                     locations: List[LocationSeries],
-                     export_dir: str = "") -> Dict[Tuple, LocationSeries]:
-    raw_indicator = get_indicator_data([truth], locations, as_of)
-    output = {}
-    for location in locations:
-        indicator_key = (truth.source, truth.signal, location.geo_type, location.geo_value)
-        location, missing_dates = get_historical_sensor_data(truth, location, end_date, start_date)
-        location, export = fill_missing_days(location, raw_indicator[indicator_key], missing_dates)
-        output[indicator_key] = location
-        if export_dir and export.values:
-            export_to_csv(export,  truth, as_of, export_dir)
-        return output
-
-
-def fill_missing_days(stored_vals: LocationSeries,
-                      indicator_data: LocationSeries,
-                      missing_dates: List[date]):
-    export_data = LocationSeries(stored_vals.geo_value, stored_vals.geo_type)
-    for day in missing_dates:
-        try:
-            y = np.array(indicator_data.get_data_range(min(indicator_data.dates), day, "linear"))
-            x = np.arange(1, len(y) + 1)
-        except ValueError:
-            continue
-        deconv_vals = deconvolve_double_smooth_tf_cv(
-            y, x, Default.DELAY_DISTRIBUTION
-        )
-        missing_day_val = deconv_vals[-1]
-        stored_vals.add_data(day, missing_day_val)
-        export_data.add_data(day, missing_day_val)  # holds only data to get exported
-    return stored_vals, export_data
diff --git a/nowcast/delphi_nowcast/sensorization/ar_model.py b/nowcast/delphi_nowcast/sensorization/ar_model.py
index ca7bc68db..34feb9b74 100644
--- a/nowcast/delphi_nowcast/sensorization/ar_model.py
+++ b/nowcast/delphi_nowcast/sensorization/ar_model.py
@@ -1,4 +1,6 @@
-from datetime import datetime, timedelta, date
+"""Fit autoregression models."""
+
+from datetime import timedelta, date
 from typing import Tuple
 
 import numpy as np
diff --git a/nowcast/delphi_nowcast/sensorization/regression_model.py b/nowcast/delphi_nowcast/sensorization/regression_model.py
index dab70d0ba..a22cc01c3 100644
--- a/nowcast/delphi_nowcast/sensorization/regression_model.py
+++ b/nowcast/delphi_nowcast/sensorization/regression_model.py
@@ -1,4 +1,6 @@
-from datetime import datetime, timedelta, date
+"""Fit linear regression mdels."""
+
+from datetime import timedelta, date
 
 import numpy as np
 
diff --git a/nowcast/delphi_nowcast/sensorization/sensor.py b/nowcast/delphi_nowcast/sensorization/sensor.py
index 913e07fce..39fa07876 100644
--- a/nowcast/delphi_nowcast/sensorization/sensor.py
+++ b/nowcast/delphi_nowcast/sensorization/sensor.py
@@ -1,5 +1,4 @@
 """Functions to run sensorization."""
-import os
 from collections import defaultdict
 from typing import List, DefaultDict
 from datetime import timedelta, date
@@ -54,7 +53,7 @@ def compute_sensors(as_of_date: date,
                 (sensor.source, sensor.signal, loc.geo_type, loc.geo_value)
             )
             if not covariates:
-                # TODO convert to log statements #689
+                # TODO convert to log statements #689 # pylint: disable=fixme
                 print(f"No data: {(sensor.source, sensor.signal, loc.geo_type, loc.geo_value)}")
                 continue
             reg_sensor = compute_regression_sensor(sensor_pred_date, covariates, loc, REG_INTERCEPT)
@@ -95,7 +94,7 @@ def historical_sensors(start_date: date,
     output = defaultdict(list)
     for location in ground_truths:
         for sensor in sensors:
-            sensor_vals, missing_dates = get_historical_sensor_data(
+            sensor_vals, _ = get_historical_sensor_data(
                 sensor, location, start_date, end_date
             )
             if sensor_vals.data: