ci: Redo format.sh --all script & backfill lint fixes (#9956)

doc/examples/newsreader/server.py

@@ -9,7 +9,6 @@ import ray
 
 @ray.remote
 class NewsServer(object):
-
     def __init__(self):
         self.conn = sqlite3.connect("newsreader.db")
         c = self.conn.cursor()
@@ -25,29 +24,36 @@ class NewsServer(object):
         items = []
         c = self.conn.cursor()
         for item in feed.items:
-            items.append({"title": item.title,
-                          "link": item.link,
-                          "description": item.description,
-                          "description_text": item.description,
-                          "pubDate": str(item.pub_date)})
-            c.execute("""INSERT INTO news (title, link, description,
+            items.append({
+                "title": item.title,
+                "link": item.link,
+                "description": item.description,
+                "description_text": item.description,
+                "pubDate": str(item.pub_date)
+            })
+            c.execute(
+                """INSERT INTO news (title, link, description,
                          published, feed, liked) values
-                         (?, ?, ?, ?, ?, ?)""", (
-                         item.title, item.link, item.description,
-                         item.pub_date, feed.link, False))
+                         (?, ?, ?, ?, ?, ?)""",
+                (item.title, item.link, item.description, item.pub_date,
+                 feed.link, False))
         self.conn.commit()
 
-        return {"channel": {"title": feed.title,
-                            "link": feed.link,
-                            "url": feed.link},
-                "items": items}
+        return {
+            "channel": {
+                "title": feed.title,
+                "link": feed.link,
+                "url": feed.link
+            },
+            "items": items
+        }
 
     def like_item(self, url, is_faved):
         c = self.conn.cursor()
         if is_faved:
-            c.execute("UPDATE news SET liked = 1 WHERE link = ?", (url,))
+            c.execute("UPDATE news SET liked = 1 WHERE link = ?", (url, ))
         else:
-            c.execute("UPDATE news SET liked = 0 WHERE link = ?", (url,))
+            c.execute("UPDATE news SET liked = 0 WHERE link = ?", (url, ))
         self.conn.commit()
 
 
@@ -71,8 +77,9 @@ def dispatcher():
         result = ray.get(method.remote(*method_args))
         return jsonify(result)
     else:
-        return jsonify(
-            {"error": "method_name '" + method_name + "' not found"})
+        return jsonify({
+            "error": "method_name '" + method_name + "' not found"
+        })
 
 
 if __name__ == "__main__":

doc/examples/streaming/streaming.py

@@ -7,10 +7,13 @@ import ray
 import wikipedia
 
 parser = argparse.ArgumentParser()
-parser.add_argument("--num-mappers",
-                    help="number of mapper actors used", default=3, type=int)
-parser.add_argument("--num-reducers",
-                    help="number of reducer actors used", default=4, type=int)
+parser.add_argument(
+    "--num-mappers", help="number of mapper actors used", default=3, type=int)
+parser.add_argument(
+    "--num-reducers",
+    help="number of reducer actors used",
+    default=4,
+    type=int)
 
 
 @ray.remote
@@ -47,8 +50,10 @@ class Reducer(object):
         word_count_sum = defaultdict(lambda: 0)
         # Get the word counts for this Reducer's keys from all of the Mappers
         # and aggregate the results.
-        count_ids = [mapper.get_range.remote(article_index, self.keys)
-                     for mapper in self.mappers]
+        count_ids = [
+            mapper.get_range.remote(article_index, self.keys)
+            for mapper in self.mappers
+        ]
         # TODO(rkn): We should process these out of order using ray.wait.
         for count_id in count_ids:
             for k, v in ray.get(count_id):
@@ -78,8 +83,9 @@ if __name__ == "__main__":
             streams.append(Stream([line.strip() for line in f.readlines()]))
 
     # Partition the keys among the reducers.
-    chunks = np.array_split([chr(i) for i in range(ord("a"), ord("z") + 1)],
-                            args.num_reducers)
+    chunks = np.array_split([chr(i)
+                             for i in range(ord("a"),
+                                            ord("z") + 1)], args.num_reducers)
     keys = [[chunk[0], chunk[-1]] for chunk in chunks]
 
     # Create a number of mappers.
@@ -93,12 +99,14 @@ if __name__ == "__main__":
     while True:
         print("article index = {}".format(article_index))
         wordcounts = {}
-        counts = ray.get([reducer.next_reduce_result.remote(article_index)
-                          for reducer in reducers])
+        counts = ray.get([
+            reducer.next_reduce_result.remote(article_index)
+            for reducer in reducers
+        ])
         for count in counts:
             wordcounts.update(count)
-        most_frequent_words = heapq.nlargest(10, wordcounts,
-                                             key=wordcounts.get)
+        most_frequent_words = heapq.nlargest(
+            10, wordcounts, key=wordcounts.get)
         for word in most_frequent_words:
             print("  ", word, wordcounts[word])
         article_index += 1