removing some warnings

rowers/views/analysisviews.py

@@ -182,6 +182,16 @@ def analysis_new(request,userid=0,function='boxplot',teamid=0,id=''):
         enddate = startdate
         startdate = s
 
+    # make sure the dates are not naive
+    try:
+        startdate = pytz.utc.localize(startdate)
+    except (ValueError, AttributeError):
+        pass
+    try:
+        enddate = pytz.utc.localize(enddate)
+    except (ValueError, AttributeError):
+        pass
+
     negtypes = []
     for b in mytypes.boattypes:
         if b[0] not in waterboattype:
@@ -366,7 +376,7 @@ def trendflexdata(workouts, options,userid=0):
                              datadf[groupby].max()+binsize,
                              binsize)
             groups = datadf.groupby(pd.cut(datadf[groupby],bins,labels=False))
-        except ValueError:
+        except (ValueError, AttributeError):
             return ('','Error: not enough data')
     else:
         bins = np.arange(datadf['days ago'].min()-binsize,
@@ -426,7 +436,7 @@ def trendflexdata(workouts, options,userid=0):
             df['groupval'].loc[mask] = np.nan
 
             groupcols = df['groupval']
-        except ValueError:
+        except (ValueError, AttributeError):
             df['groupval'] =  groups.mean()[groupby].fillna(value=0)
             df['groupval'].loc[mask] = np.nan
             groupcols = df['groupval']
@@ -1917,6 +1927,8 @@ def rankings_view(request,userid=0,
     startdate = datetime.datetime.combine(startdate,datetime.time())
     enddate = datetime.datetime.combine(enddate,datetime.time(23,59,59))
     #enddate = enddate+datetime.timedelta(days=1)
+    startdate = arrow.get(startdate).datetime
+    enddate = arrow.get(enddate).datetime
 
     thedistances = []
     theworkouts = []
@@ -2324,7 +2336,8 @@ def rankings_view2(request,userid=0,
     startdate = datetime.datetime.combine(startdate,datetime.time())
     enddate = datetime.datetime.combine(enddate,datetime.time(23,59,59))
     #enddate = enddate+datetime.timedelta(days=1)
-
+    startdate = arrow.get(startdate).datetime
+    enddate = arrow.get(enddate).datetime
 
     thedistances = []
     theworkouts = []
@@ -2438,7 +2451,7 @@ def rankings_view2(request,userid=0,
         pwr = 2.8*(velo**3)
         try:
             pwr = int(pwr)
-        except ValueError:
+        except (ValueError, AttributeError):
             pwr = 0
 
         a = {'distance':rankingdistance,
@@ -2675,7 +2688,8 @@ def otwrankings_view(request,userid=0,
     enddate = datetime.datetime.combine(enddate,datetime.time(23,59,59))
     #enddate = enddate+datetime.timedelta(days=1)
 
-
+    startdate = arrow.get(startdate).datetime
+    enddate = arrow.get(enddate).datetime
 
     thedistances = []
     theworkouts = []
@@ -3087,7 +3101,8 @@ def oterankings_view(request,userid=0,
     startdate = datetime.datetime.combine(startdate,datetime.time())
     enddate = datetime.datetime.combine(enddate,datetime.time(23,59,59))
 
-
+    startdate = arrow.get(startdate).datetime
+    enddate = arrow.get(enddate).datetime
 
     thedistances = []
     theworkouts = []
@@ -3436,6 +3451,16 @@ def user_multiflex_select(request,
     else:
         rankingpiece = [True,False]
 
+    # make sure the dates are not naive
+    try:
+        startdate = pytz.utc.localize(startdate)
+    except (ValueError, AttributeError):
+        pass
+    try:
+        enddate = pytz.utc.localize(enddate)
+    except (ValueError, AttributeError):
+        pass
+
     workouts = Workout.objects.filter(
         user=r,
         startdatetime__gte=startdate,
@@ -3638,7 +3663,7 @@ def multiflex_data(request,userid=0,
                              datadf[groupby].max()+binsize,
                              binsize)
             groups = datadf.groupby(pd.cut(datadf[groupby],bins,labels=False))
-        except ValueError:
+        except (ValueError, AttributeError):
             messages.error(
                 request,
                 "Unable to compete. Probably not enough data selected"
@@ -3703,7 +3728,7 @@ def multiflex_data(request,userid=0,
             df['groupval'].loc[mask] = np.nan
 
             groupcols = df['groupval']
-        except ValueError:
+        except (ValueError, AttributeError):
             df['groupval'] =  groups.mean()[groupby].fillna(value=0)
             df['groupval'].loc[mask] = np.nan
             groupcols = df['groupval']
@@ -4079,6 +4104,15 @@ def user_boxplot_select(request,
         if b[0] not in waterboattype:
             negtypes.append(b[0])
 
+    # make sure the dates are not naive
+    try:
+        startdate = pytz.utc.localize(startdate)
+    except (ValueError, AttributeError):
+        pass
+    try:
+        enddate = pytz.utc.localize(enddate)
+    except (ValueError, AttributeError):
+        pass
 
     workouts = Workout.objects.filter(user=r,
                                        startdatetime__gte=startdate,
@@ -5338,7 +5372,7 @@ def history_view_data(request,userid=0):
         ddict['hrmean'] = int(wavg(ddf,'hr','deltat'))
         try:
             ddict['hrmax'] = ddf['hr'].max().astype(int)
-        except ValueError:
+        except (ValueError, AttributeError):
             ddict['hrmax'] = 0
 
         ddict['powermean'] = int(wavg(ddf,'power','deltat'))