minimal refactoring and unique together constraint

rowers/models.py

@@ -3728,5 +3728,8 @@ class VideoAnalysis(models.Model):
     delay = models.IntegerField(default=0)
     workout = models.ForeignKey(Workout, on_delete=models.CASCADE)
 
+    class Meta:
+        unique_together = ('video_id','workout')
+
     def __str__(self):
         return self.name

rowers/views/workoutviews.py

@@ -46,6 +46,50 @@ def get_video_id(url):
     else:
         raise ValueError
 
+def get_video_data(w):
+    df = getsmallrowdata_db(['time','velo','spm'],ids=[w.id],
+    workstrokesonly=False,doclean=False,compute=False)
+    df['time'] = (df['time']-df['time'].min())/1000.
+    df.sort_values(by='time',inplace=True)
+
+
+    df.set_index(pd.to_timedelta(df['time'],unit='s'),inplace=True)
+    df2 = df.resample('1s').mean().interpolate()
+
+
+    #mask = df2['time'] < delay
+    #df2 = df2.mask(mask).dropna()
+    df2['time'] = (df2['time']-df2['time'].min())
+
+    boatspeed = (100*df2['velo']).astype(int)/100.
+    spm = (10*df2['spm']).astype(int)/10.
+
+    coordinates = dataprep.get_latlon_time(w.id)
+
+    coordinates.set_index(pd.to_timedelta(coordinates['time'],unit='s'),inplace=True)
+    coordinates = coordinates.resample('1s').mean().interpolate()
+    #mask = coordinates['time'] < delay
+    #coordinates = coordinates.mask(mask).dropna()
+    coordinates['time'] = coordinates['time']-coordinates['time'].min()
+    latitude = coordinates['latitude']
+    longitude = coordinates['longitude']
+
+    # create map
+    mapscript, mapdiv = leaflet_chart_video(latitude,longitude,
+                                            w.name)
+
+    # bundle data
+    data = {
+        'boatspeed':[ v for v in boatspeed.values],
+        'latitude':[ l for l in latitude.values],
+        'longitude':[ l for l in longitude.values],
+        'spm':[ s for s in spm.values ]
+        }
+
+    maxtime = coordinates['time'].max()
+
+    return data, mapscript, mapdiv, maxtime
+
 # Show a video compared with data
 def workout_video_view(request,id=''):
     try:
@@ -95,44 +139,7 @@ def workout_video_view(request,id=''):
         form = None
 
     # get data
-    df = getsmallrowdata_db(['time','velo','spm'],ids=[w.id],
-    workstrokesonly=False,doclean=False,compute=False)
-    df['time'] = (df['time']-df['time'].min())/1000.
-    df.sort_values(by='time',inplace=True)
-
-
-    df.set_index(pd.to_timedelta(df['time'],unit='s'),inplace=True)
-    df2 = df.resample('1s').mean().interpolate()
-
-
-    #mask = df2['time'] < delay
-    #df2 = df2.mask(mask).dropna()
-    df2['time'] = (df2['time']-df2['time'].min())
-
-    boatspeed = (100*df2['velo']).astype(int)/100.
-    spm = (10*df2['spm']).astype(int)/10.
-
-    coordinates = dataprep.get_latlon_time(w.id)
-
-    coordinates.set_index(pd.to_timedelta(coordinates['time'],unit='s'),inplace=True)
-    coordinates = coordinates.resample('1s').mean().interpolate()
-    #mask = coordinates['time'] < delay
-    #coordinates = coordinates.mask(mask).dropna()
-    coordinates['time'] = coordinates['time']-coordinates['time'].min()
-    latitude = coordinates['latitude']
-    longitude = coordinates['longitude']
-
-    # create map
-    mapscript, mapdiv = leaflet_chart_video(latitude,longitude,
-                                            w.name)
-
-    # bundle data
-    data = {
-        'boatspeed':[ v for v in boatspeed.values],
-        'latitude':[ l for l in latitude.values],
-        'longitude':[ l for l in longitude.values],
-        'spm':[ s for s in spm.values ]
-        }
+    data, mapscript, mapdiv, maxtime = get_video_data(w)
 
     breadcrumbs = [
             {
@@ -162,7 +169,7 @@ def workout_video_view(request,id=''):
                       'form':form,
                       'breadcrumbs':breadcrumbs,
                       'analysis':analysis,
-                      'maxtime':coordinates['time'].max(),
+                      'maxtime':maxtime,
                       })
 
 
@@ -201,44 +208,7 @@ def workout_video_create_view(request,id=0):
         delay = 0
 
     # get data
-    df = getsmallrowdata_db(['time','velo','spm'],ids=[w.id],
-                            workstrokesonly=False,doclean=False,compute=False)
-    df['time'] = (df['time']-df['time'].min())/1000.
-    df.sort_values(by='time',inplace=True)
-
-
-    df.set_index(pd.to_timedelta(df['time'],unit='s'),inplace=True)
-    df2 = df.resample('1s').mean().interpolate()
-
-
-    #mask = df2['time'] < delay
-    #df2 = df2.mask(mask).dropna()
-    df2['time'] = (df2['time']-df2['time'].min())
-
-    boatspeed = (100*df2['velo']).astype(int)/100.
-    spm = (10*df2['spm']).astype(int)/10.
-
-    coordinates = dataprep.get_latlon_time(w.id)
-
-    coordinates.set_index(pd.to_timedelta(coordinates['time'],unit='s'),inplace=True)
-    coordinates = coordinates.resample('1s').mean().interpolate()
-    #mask = coordinates['time'] < delay
-    #coordinates = coordinates.mask(mask).dropna()
-    coordinates['time'] = coordinates['time']-coordinates['time'].min()
-    latitude = coordinates['latitude']
-    longitude = coordinates['longitude']
-
-    # create map
-    mapscript, mapdiv = leaflet_chart_video(latitude,longitude,
-                                       w.name)
-
-    # bundle data
-    data = {
-        'boatspeed':[ v for v in boatspeed.values],
-        'latitude':[ l for l in latitude.values],
-        'longitude':[ l for l in longitude.values],
-        'spm':[ s for s in spm.values ]
-        }
+    data, mapscript, mapdiv, maxtime = get_video_data(w)
 
     breadcrumbs = [
             {