When we use css-sprites it's important to make browser cache them for longest period possible. On other hand, we need to refresh them when they are updated. This is especially visible when all icons are stored in single sprite. When it's outdated - entire site becomes ugly.
To solve this task I've implemented this small script that adds file's hash to url:
background-image: url(images/icons.png);
background-image: url(images/icons.png?a3844c660);#!/usr/bin/python
import os.path
import re
import hashlib
def file_hash(filename, block_size=2**20):
md5 = hashlib.md5()
with open(filename, 'rb') as f:
for data in iter(lambda: f.read(block_size), ''):
md5.update(data)
return md5.hexdigest()
def find_replace(match, basedir):
match = match.replace("'", '')
if '?' in match or '#' in match or match.startswith('http://'):
print 'skipping: ', match
return None
filename = os.path.join(basedir, match)
return '%s?%s' % (match, file_hash(filename)[:10])
def insert_hash(filename, debug=False):
basedir = os.path.dirname(filename)
css = open(filename).read()
matches = re.findall(r"url\((.*?)\)", css)
replacements = dict([
(match, find_replace(match, basedir))
for match in matches
])
if debug:
for key, value in replacements.iteritems():
print key, ' => ', value
else:
for match, repl in replacements.iteritems():
if repl:
css = css.replace(match, repl)
out = open(filename, 'w')
out.write(css)
out.close()
if __name__ == '__main__':
from optparse import OptionParser
usage = 'usage: %prog filename.css'
parser = OptionParser(usage=usage)
parser.add_option("", "--debug", action="store_true", dest="debug", default=False,
help="When set, just output list of substitutions.")
(options, args) = parser.parse_args()
if len(args) < 1:
print 'You must provide file name.'
insert_hash(os.path.realpath(args[0]), options.debug)Update
This is pretty old article. Now it's better to use something integrated to your build process - grunt, webassets, etc.
Subscribe for the news and updates
In one of our recent projects, we had an interesting case: the whole application was built around an interactive map for a fairly large shopping mall, and the main goal of the system was to plot the closest route to a user-selected destination.
Now it's time to get acquainted with Elasticsearch. This NoSQL database is used to store logs, analyze information and - most importantly - search.
When dealing with one of our projects (LookSMI media monitoring platform) we have to handle the huge volume of data – and its quantity is constantly growing. At the same time, we must run quick searches with smart rules. In this article I'll explain how we have achieved required performance.
It appears that not everyone knows that in python you can create classes dynamically without metaclasses. I'll show an example of how to do it.So we've learned how to use custom QuerySet to chain requests:Article.objects.old().public()Now we need to make it work for related objects:user.articles.old().public()This is done using use_for_related_fields, but it needs a little trick.
In my current project I had a task to use twitter API. Twitter uses OAuth for authentication, which is pretty dreary. To avoid fiddling with it all the time, I've moved authentication to decorator. If key is available - nothing happens, just view is launched as usual. It's convenient that there's no need for additional twitter settings in user profile. Code is in article.
In my recent project there was a lot of data business logic, so I had to organize this code somehow. In this article I'll describe a few hints on how to it.