On 5/8/2016 7:36 AM, Steven D'Aprano wrote:
On Sun, 8 May 2016 11:16 am, DFS wrote:
address data is scraped from a website:
names = tree.xpath()
addr = tree.xpath()
Why are you scraping the data twice?
Because it exists in 2 different sections of the document.
names = tree.xpath('//span[@class="header_text3"]/text()')
addresses = tree.xpath('//span[@class="text3"]/text()')
I thought you were a "master who knew her tools", and I was the
apprentice?
So why did "the master" think xpath() was magic?
names = addr = tree.xpath()
or if you prefer the old-fashioned:
names = tree.xpath()
addr = names
but that raises the question, how can you describe the same set of data as
both "names" and "addr[esses]" and have them both be accurate?
I want to store the data atomically,
I'm not really sure what you mean by "atomically" here. I know what *I* mean
by "atomically", which is to describe an operation which either succeeds
entirely or fails.
That's atomicity.
> But I don't know what you mean by it.
http://www.databasedesign-resource.com/atomic-database-values.html
so I parse street, city, state, and
zip into their own lists.
None of which is atomic.
All of which are atomic.
"1250 Peachtree Rd, Atlanta, GA 30303
street = [s.split(',')[0] for s in addr]
city = [c.split(',')[1].strip() for c in addr]
state = [s[-8:][:2] for s in addr]
zipcd = [z[-5:] for z in addr]
At this point, instead of iterating over the same list four times, doing the
same thing over and over again, you should do things the old-fashioned way:
streets, cities, states, zipcodes = [], [], [], []
for word in addr:
items = word.split(',')
streets.append(items[0])
cities.append(items[1].strip())
states.append(word[-8:-2])
zipcodes.append(word[-5:])
That's a good one.
Chris Angelico mentioned something like that, too, and I already put it
place.
Oh, and use better names. "street" is a single street, not a list of
streets, note plural.
I'll use whatever names I like.
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