benchmarks: 1488e1f55f61 (original) (raw)

Mercurial > benchmarks

changeset 201:1488e1f55f61

Issue #17785: Use a faster URL shortener for perf.py

Alexandre Vassalotti alexandre@peadrop.com
date	Sat, 20 Apr 2013 12:59:46 -0700
parents	134941cc41c0
children	5d4ecadca0d5
files	perf.py
diffstat	1 files changed, 16 insertions(+), 12 deletions(-)[+] [-] perf.py 28

line wrap: on

line diff

--- a/perf.py +++ b/perf.py @@ -54,6 +54,7 @@ from future import division, with_st import csv import contextlib +import json import logging import math import optparse @@ -68,10 +69,9 @@ import tempfile import time import threading try:

from urllib.request import urlopen
from urllib.error import URLError

-except ImportError:

from urllib2 import urlopen, URLError

import http.client as httpclient

+except:

import httplib as httpclient

try: import multiprocessing except ImportError: @@ -784,21 +784,25 @@ def GetChart(base_data, changed_data, op def ShortenUrl(url):

"""Shorten a given URL using tinyurl.com.

"""Shorten a given URL using Google URL shortener.

Args: url: url to shorten. Returns:

   Shorter url. If tinyurl.com is not available, returns the original[](#l1.36)

```
   url unaltered.[](#l1.37)
```

   Shorter url. If the service is not available, returns None[](#l1.38)

"""

tinyurl_api = "http://tinyurl.com/api-create.php?url="[](#l1.40) try:

   url = urlopen(tinyurl_api + url).read()[](#l1.42)

except URLError:

   info("failed to call out to tinyurl.com")[](#l1.44)

return url

   conn = httpclient.HTTPSConnection("www.googleapis.com")[](#l1.46)

   body = json.dumps({"longUrl": url})[](#l1.47)

   headers = {"Content-Type": "application/json"}[](#l1.48)

   conn.request("POST", "/urlshortener/v1/url", body, headers)[](#l1.49)

   response = conn.getresponse()[](#l1.50)

   if response.status == httpclient.OK:[](#l1.51)

       return json.loads(response.read().decode("utf-8"))["id"][](#l1.52)

except IOError:

   info("failed to call out to URL shortening service")[](#l1.54)

return None

def SummarizeData(data, points=100, summary_func=max):