Add a real example

profiks-4.py

@@ -6,12 +6,12 @@
 A = TypeVar("A")
 B = TypeVar("B")
 
-def profile(f: Callable[A, B], args: A):
+def profile(f: Callable[A, B], *args: A):
     # a log of f's execution
     trajectory = []
 
     sys.settrace(makeTrace(trajectory))
-    result = f(args)
+    result = f(*args)
     sys.settrace(emptyTrace)
     return [result, trajectory]
 
@@ -52,13 +52,51 @@ def uploadSummary(summary):
     with requests.post("https://flamegraph.com", data=summary, headers=headers) as resp:
         return resp.text
 
+# functions to be profiled
+
 def fib(x: int) -> int:
     if x < 2:
         return 1
     return fib(x - 1) + fib(x - 2)
 
-if __name__ == "__main__":
-    f = lambda x: uploadSummary(summariseTrajectory(profile(fib, x)[1]))
+def wikiCommonWords():
+    import json
+    from urllib.request import urlopen
+
+    import collections
+    import operator
+    import sys
+
+    WIKIPEDIA_ARTICLE_API_URL = "https://en.wikipedia.org/w/api.php?action=query&titles=Spoon&prop=revisions&rvprop=content&format=json"
+
+    def download():
+        return urlopen(WIKIPEDIA_ARTICLE_API_URL).read()
+
+    def parse(json_data):
+        return json.loads(json_data)
+
+    def most_common_words(page):
+        word_occurences = collections.defaultdict(int)
+
+        for revision in page["revisions"]:
+            article = revision["*"]
 
-    for i in range(0, 7):
-        print(f(i))
+            for word in article.split():
+                if len(word) < 2:
+                    continue
+                word_occurences[word] += 1
+
+        word_list = sorted(word_occurences.items(), key=operator.itemgetter(1), reverse=True)
+
+        return word_list[0:5]
+
+    data = parse(download())
+    page = list(data["query"]["pages"].values())[0]
+
+    sys.stderr.write("The most common words were %s\n" % most_common_words(page))
+
+
+
+if __name__ == "__main__":
+    result = profile(lambda _: fib(7), None)
+    print(uploadSummary(summariseTrajectory(result[1])))