Peterbe.com

If you met someone from Nestle, Pfizer, Wal-Mart, ExxonMobil, Chevron, Dow Chemical or Monsanto in a suit and who is proud of her job, would you punch her in the face? No? But would you pretend that you don't know about the ways of her company?

Eco blogger Eco-Chick has written a great write-up on some of the worlds greediest and least irresponsible companies. A great read if you're one of the millions of people who understand that corporate ownership of the world is a bad thing but don't necessarily know any specific details or examples.

When you're desperate for money you can do crazy things like rob a bank or mug an innocent old lady. But decisions to mug an old lady is 100% yours whereas office workers for irresponsible corporations are usually just a cog in a wheel, and therefore they all blame their destructive practices aren't their own idea or initiative. That is was someone "in upper management who decided". Would you dare to confront those excuses at a dinner party if you met one?

Hard-to-explain-type-of-online-art

I have a query that looks like this (simplified for the sake of brevity):

SELECT
  gl.id,
  miles_between_lat_long(46.519582, 6.632121,
                         gl.latitude::numeric, gl.longitude::numeric
                        ) AS distance
FROM 
 kungfuperson gl
 miles_between_lat_long(46.519582, 6.632121,
                        gl.latitude::numeric, gl.longitude::numeric
                        ) < 5000

ORDER BY distance ASC;

It basically finds other entries in a table (which has columns for latitude and longitude) but only returns those that are within a certain distance (from a known latitude/longitude point). Running this query on my small table takes about 7 milliseconds. (I used EXPLAIN ANALYZE)

So I thought, how about if I wrap it in a sub-select so that the function miles_between_lat_long() is only used once per row. Surely that would make it a lot faster. I accept that it wouldn't be twice as fast because wrapping it in a sub-select would also add some extra computation. Here's the "improved" version:

SELECT * FROM (
SELECT
  gl.id,
  miles_between_lat_long(46.519582, 6.632121,
                         gl.latitude::numeric, gl.longitude::numeric
                        ) AS distance
FROM 
 kungfuperson gl
) AS ss
WHERE ss.distance < 5000
ORDER BY ss.distance ASC;

To test it I wrote a little script that randomly runs these two versions many many times (about 50 times) each and then compare the averages.

Here I'm going to explain a solution I had to make for a site I recently launched. Basically, I wanted to cache the whole page in memcache and set the appropriate Expires and Cache-Control headers so that my view was only rendered once an hour and parts of the page needs to be unique (i.e. "Hi, logged in as xxxx")

The advantages is great: The page loads fast, content is stored in memcache every hour, page still appears to be dynamic.

The disadvantages are not so great: the AJAX loads fast but causes a flicker

Basically, I wrote a custom decorator called custom_cache_page(<delay in seconds>) that works like the normal cache_page(<delay in seconds>) decorator available in stock Django. However, my decorator inserts a piece of HTML into the rendered HTML (before it's stored in memcache) that I later use to update certain elements of the page with AJAX instead of server side.

Really impressed by the menu/nav on this e-commerce site. Couldn't be any more obvious how to find the teas you're looking for.

"A table of countries lists every country and whether they drive on the left side of the road or the right side of the road."

"SEO is not about creating a website sausage overstuffed with key words and phrases. It’s all about creating relevant and compelling content that transforms you into a thought leader who can become a trusted provider That is ultimately how you convert visitors into buyers"

Tonight we're launching our new Kung Fu website: kungfupeople.com

My friend Chris and I have been busy building a website where people who do kung fu can put themselves on a map to say where they train kung fu, what style they do and what kung fu club they belong to. The site is very much centred on having a world map and each little pin on the map is one kung fu martial artist.

This site is build in Django and is based on work that was done to build Django People originally developed by Simon Willison. We took his original code and revamped it almost completely.

Our goal is to slowly build up a world map of people from all sorts of clubs and styles and hopefully one day become the best place on the Internet for understanding what clubs are available where and what styles different people do. The site has been in an "alpha testing" phase now for a couple of weeks and even though we still have lots of ideas and cool features to add we believe it's ready to go live.

So if you train kung fu or know someone who trains kung fu go to our website and add yourself to the map

I've been experimenting with the new Google Reverse Geocoding which allows you to get the location name and country and stuff from a latitude/longitude coordinate.

What I've been doing is comparing this with GeoNames. GeoNames is available from geopy in the reverse-geocode branch.

I wrote down a list of about 15 lat/long points and the result I expect from them (taken from an existing app I'm contemplating switching to Google Reverse Geocoding for) and ran a batch of timed tests on. These results might satisfy the impatient:

FAILURES:
geonames_json        0
google               0
geonames             12

TOTAL TIMES:
geonames_json        2.43582677841        0.143283928142 seconds/request
google               2.24999976158        0.132352927152 seconds/request
geonames             1.78063511848        0.104743242264 seconds/request

I've grown quite addicted to this and finding that it's saving me tonnes of milliseconds every day. First of all, I've made this little script and put it in my bin directory called '~/bin/gg':

#!/usr/bin/python
import sys, os
args = sys.argv[1:]
i = False
if '-i' in args:
    i = True
    args.remove('-i')
pattern = args[-1]
extra_args = ''
if len(args) > 1:
    extra_args = ' '.join(args[:-1])
if i:
    param = "-in"
else:
    param = "-n"
cmd = "git grep %s %s '%s'" % (param, extra_args, pattern)
os.system(cmd)

Basically, it's just a lazy short hand for git grep ("Look for specified patterns in the working tree files"). Now I can do this:

peterbe@trillian:~/MoneyVillage2 $ gg getDIYPackURL
Homesite.py:526:    def getDIYPackURL(self):
zpt/homepage/index_html.zpt:78:       tal:attributes="href here/getDIYPackURL">Get your free trial here</
zpt/moneyconcerns/index_html.zpt:36:       tal:attributes="href here/getDIYPackURL">Get your free trial h
zpt/moneyconcerns/index_html.zpt:50:          <p><a tal:attributes="href here/getDIYPackURL" class="makea
(END) 

It's not much faster than normal grep but it automatically filters out junk. Obviously doesn't help you when searching in files you haven't added yet.