Fix nowcast linting

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]
 

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)

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

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
 

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: