Whitespacing and PEP8-ing.

imagekit/defaults.py

@@ -3,23 +3,28 @@
 from imagekit.specs import ImageSpec
 from imagekit import processors
 
+
 class ResizeThumbnail(processors.Resize):
     width = 100
     height = 50
     crop = True
 
+
 class EnhanceSmall(processors.Adjustment):
     contrast = 1.2
     sharpness = 1.1
 
+
 class SampleReflection(processors.Reflection):
     size = 0.5
     background_color = "#000000"
 
+
 class PNGFormat(processors.Format):
     format = 'PNG'
     extension = 'png'
 
+
 class DjangoAdminThumbnail(ImageSpec):
     access_as = 'admin_thumbnail'
     processors = [ResizeThumbnail, EnhanceSmall, SampleReflection, PNGFormat]

imagekit/management/commands/ikflush.py

@@ -14,6 +14,7 @@ class Command(BaseCommand):
     def handle(self, *args, **options):
         return flush_cache(args, options)
 
+
 def flush_cache(apps, options):
     """ Clears the image cache
 

imagekit/models.py

@@ -154,5 +154,3 @@ class ImageModel(models.Model):
 
 
 post_delete.connect(ImageModel.clear_cache, sender=ImageModel)
-
-

imagekit/processors.py

@@ -1,9 +1,9 @@
 """ Imagekit Image "ImageProcessors"
 
-A processor defines a set of class variables (optional) and a
-class method named "process" which processes the supplied image using
-the class properties as settings. The process method can be overridden as well allowing user to define their
-own effects/processes entirely.
+A processor defines a set of class variables (optional) and a class method
+named "process" which processes the supplied image using the class properties
+as settings. The process method can be overridden as well allowing user to
+define their own effects/processes entirely.
 
 """
 from imagekit.lib import Image, ImageEnhance, ImageColor
@@ -61,8 +61,8 @@ class Reflection(ImageProcessor):
         # create a new image filled with the bgcolor the same size
         background = Image.new("RGB", img.size, background_color)
         # calculate our alpha mask
-        start = int(255 - (255 * cls.opacity)) # The start of our gradient
-        steps = int(255 * cls.size) # the number of intermedite values
+        start = int(255 - (255 * cls.opacity))  # The start of our gradient
+        steps = int(255 * cls.size)  # The number of intermedite values
         increment = (255 - start) / float(steps)
         mask = Image.new('L', (1, 255))
         for y in range(255):
@@ -100,7 +100,7 @@ class Resize(ImageProcessor):
         if cls.crop:
             crop_horz = getattr(obj, obj._ik.crop_horz_field, 1)
             crop_vert = getattr(obj, obj._ik.crop_vert_field, 1)
-            ratio = max(float(cls.width)/cur_width, float(cls.height)/cur_height)
+            ratio = max(float(cls.width) / cur_width, float(cls.height) / cur_height)
             resize_x, resize_y = ((cur_width * ratio), (cur_height * ratio))
             crop_x, crop_y = (abs(cls.width - resize_x), abs(cls.height - resize_y))
             x_diff, y_diff = (int(crop_x / 2), int(crop_y / 2))
@@ -118,15 +118,15 @@ class Resize(ImageProcessor):
             img = img.resize((int(resize_x), int(resize_y)), Image.ANTIALIAS).crop(box)
         else:
             if not cls.width is None and not cls.height is None:
-                ratio = min(float(cls.width)/cur_width,
-                            float(cls.height)/cur_height)
+                ratio = min(float(cls.width) / cur_width,
+                            float(cls.height) / cur_height)
             else:
                 if cls.width is None:
-                    ratio = float(cls.height)/cur_height
+                    ratio = float(cls.height) / cur_height
                 else:
-                    ratio = float(cls.width)/cur_width
-            new_dimensions = (int(round(cur_width*ratio)),
-                              int(round(cur_height*ratio)))
+                    ratio = float(cls.width) / cur_width
+            new_dimensions = (int(round(cur_width * ratio)),
+                              int(round(cur_height * ratio)))
             if new_dimensions[0] > cur_width or \
                new_dimensions[1] > cur_height:
                 if not cls.upscale:

imagekit/utils.py

@@ -2,15 +2,16 @@
 
 import tempfile
 
+
 def img_to_fobj(img, format, **kwargs):
     tmp = tempfile.TemporaryFile()
-    
-    #preserve transparency if the image is in Pallette (P) mode
+
+    # Preserve transparency if the image is in Pallette (P) mode.
     if img.mode == 'P':
         kwargs['transparency'] = len(img.split()[-1].getcolors())
     else:
         img.convert('RGB')
-    
+
     img.save(tmp, format, **kwargs)
     tmp.seek(0)
     return tmp