diff --git a/python/examples/py/FeatureCollection/count_features.py b/python/examples/py/FeatureCollection/count_features.py
index cd69d4a73..1b95f9641 100644
--- a/python/examples/py/FeatureCollection/count_features.py
+++ b/python/examples/py/FeatureCollection/count_features.py
@@ -10,8 +10,8 @@
 
 photos_near_sf = ee.FeatureCollection('GOOGLE/EE/DEMOS/sf-photo-locations')
 bridge_photos = photos_near_sf.filter(
-    ee.Filter().Or(ee.Filter.stringContains('title', 'Bridge'),
-                   ee.Filter.stringContains('title', 'bridge')))
+    ee.Filter.Or(ee.Filter.stringContains('title', 'Bridge'),
+                 ee.Filter.stringContains('title', 'bridge')))
 
 ee.mapclient.addToMap(photos_near_sf, {'color': '0040b0'})
 ee.mapclient.addToMap(bridge_photos, {'color': 'e02070'})
diff --git a/python/examples/py/FeatureCollection/reverse_mask.py b/python/examples/py/FeatureCollection/reverse_mask.py
index adf58c602..909e0214c 100644
--- a/python/examples/py/FeatureCollection/reverse_mask.py
+++ b/python/examples/py/FeatureCollection/reverse_mask.py
@@ -10,7 +10,7 @@
 ee.mapclient.centerMap(-115, 39, 5)
 
 fc = (ee.FeatureCollection('RESOLVE/ECOREGIONS/2017')
-      .filter(ee.Filter().eq('ECO_NAME', 'Great Basin shrub steppe')))
+      .filter(ee.Filter.eq('ECO_NAME', 'Great Basin shrub steppe')))
 
 # Start with a black image.
 empty = ee.Image(0).toByte()
diff --git a/python/examples/py/ImageCollection/clipped_composite.py b/python/examples/py/ImageCollection/clipped_composite.py
index 57f263396..c8f9254ab 100644
--- a/python/examples/py/ImageCollection/clipped_composite.py
+++ b/python/examples/py/ImageCollection/clipped_composite.py
@@ -19,7 +19,7 @@
 
 # Clip to the output image to the California state boundary.
 fc = (ee.FeatureCollection('TIGER/2018/States')
-      .filter(ee.Filter().eq('NAME', 'California')))
+      .filter(ee.Filter.eq('NAME', 'California')))
 image2 = image1.clipToCollection(fc)
 
 # Select the red, green and blue bands.