doing time zones slightly better

rowers/dataprep.py

@@ -1727,60 +1727,53 @@ def save_workout_database(f2, r, dosmooth=True, workouttype='rower',
         workoutstartdatetime = row.rowdatetime
 
 
-    timezone_str = 'UTC'
-    try:
-        workoutstartdatetime = timezone.make_aware(workoutstartdatetime)
-    except ValueError:
-        pass
-
-
-    dologging('debuglog.log','Dataprep line 1737, Workout Startdatetime {workoutstartdatetime}'.format(
-        workoutstartdatetime=workoutstartdatetime,
-    ))
-
-
-
-
-
-    try:
-        latavg = row.df[' latitude'].mean()
-        lonavg = row.df[' longitude'].mean()
-
-        tf = TimezoneFinder()
+    if workoutstartdatetime.tzinfo is None:
+        timezone_str = 'UTC'
         try:
-            timezone_str = tf.timezone_at(lng=lonavg, lat=latavg)
-        except (ValueError,OverflowError): # pragma: no cover
-            timezone_str = 'UTC'
-        if timezone_str == None: # pragma: no cover
-            timezone_str = tf.closest_timezone_at(lng=lonavg,
-                                                  lat=latavg)
-            if timezone_str == None: # pragma: no cover
-                timezone_str = r.defaulttimezone
-        try:
-            workoutstartdatetime = pytz.timezone(timezone_str).localize(
-                row.rowdatetime
-            )
+            workoutstartdatetime = timezone.make_aware(workoutstartdatetime)
         except ValueError:
-            workoutstartdatetime = workoutstartdatetime.astimezone(
-                pytz.timezone(timezone_str)
-            )
-    except KeyError:
-        timezone_str = r.defaulttimezone
+            pass
 
 
+        try:
+            latavg = row.df[' latitude'].mean()
+            lonavg = row.df[' longitude'].mean()
+
+            tf = TimezoneFinder()
+            try:
+                timezone_str = tf.timezone_at(lng=lonavg, lat=latavg)
+            except (ValueError,OverflowError): # pragma: no cover
+                timezone_str = 'UTC'
+            if timezone_str is None: # pragma: no cover
+                timezone_str = tf.closest_timezone_at(lng=lonavg,
+                                                    lat=latavg)
+                if timezone_str is None: # pragma: no cover
+                    timezone_str = r.defaulttimezone
+            try:
+                workoutstartdatetime = pytz.timezone(timezone_str).localize(
+                    row.rowdatetime
+                    )
+            except ValueError:
+                workoutstartdatetime = workoutstartdatetime.astimezone(
+                    pytz.timezone(timezone_str)
+                    )
+        except KeyError:
+            timezone_str = r.defaulttimezone
+
+    dologging('debuglog.log','Dataprep line 1763, Workout Startdatetime {workoutstartdatetime}'.format(
+        workoutstartdatetime=workoutstartdatetime,
+        ))
+
     duration = totaltime_sec_to_string(totaltime)
 
-    workoutdate = workoutstartdatetime.astimezone(
-        pytz.timezone(timezone_str)
-    ).strftime('%Y-%m-%d')
-    workoutstarttime = workoutstartdatetime.astimezone(
-        pytz.timezone(timezone_str)
-    ).strftime('%H:%M:%S')
+    workoutdate = workoutstartdatetime.strftime('%Y-%m-%d')
+    workoutstarttime = workoutstartdatetime.strftime('%H:%M:%S')
 
-    s = 'Dataprep line 1780 workoutdate and time set to {workoutdate} and {workoutstarttime}'.format(
+    s = 'Dataprep line 1772 workoutdate and time set to {workoutdate} and {workoutstarttime}'.format(
         workoutdate=workoutdate,
         workoutstarttime=workoutstarttime,
     )
+    dologging('debuglog.log',s)
 
 
     if makeprivate: # pragma: no cover
@@ -1812,6 +1805,8 @@ def save_workout_database(f2, r, dosmooth=True, workouttype='rower',
     if title is not None and len(title)>140: # pragma: no cover
         title = title[0:140]
 
+    timezone_str = str(workoutstartdatetime.tzinfo)
+
     w = Workout(user=r, name=title, date=workoutdate,
                 workouttype=workouttype,
                 boattype=boattype,