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APIs are all around us on the web. Sometimes we can use scraping techniques to interact with them in a meaningful way.
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Back in the good old days of the Internet,
if we wanted data,
0:00
we had to view it on Web pages.
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Now, however, many sites provide
a Web API that shares their data.
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Sometimes, we can use these APIs
to directly access information,
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without having to scrape the data.
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I'd recommend looking to see if
the site you are wanting to scrape
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offers an API for
the information you need.
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It can be a big time saver.
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Let's take a look at how we can get data
from the World Bank, using their API.
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There are many instances
when using an API is great.
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Sometimes, though, scraping results
from an API is useful as well,
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especially if the API
documentation isn't super helpful.
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Let's take a brief look at one
technique we can use to get and
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process data from an API.
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In this case,
we'll look at The World Bank API.
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It's actually very well documented, which
provides us with some extra knowledge
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as we go about trying to scrape things.
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If we look here, at
the Developer Information overview page,
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it provides information about how to
get started, and what the API provides.
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Let's look here,
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at the Country Queries section, to see
what information we might explore there.
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It looks like we could use this
information to get some generic
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information about
the countries of the world.
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For example, if we wanted to do some
high-level data exploration about
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income level in regions of the world,
let's use this request format here,
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look through some ISO codes, and get
some information that we could explore.
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We won't be doing any actual
exploration of data in this course, but
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check the teachers' notes for
more information.
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Let's take a look at the information we
get from a country with a lot of horses,
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like Ethiopia.
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I know their ISO code is ETH, so
let's put that into the request format.
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So we can copy this, Let's create
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a new tab, and we'll do ETH.
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It looks like we're getting back the same
information as the documentation stated,
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and its in XML format.
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That's great, we can handle that, we'll
use Beautiful Soup to parse this XML,
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and get the name, region,
and income level.
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This could be used, for
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example, to generate a histogram chart of
regions of the world and income levels.
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Lots of options for
data visualization, here.
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Let's go back to our code, and
create a new world_bank.py file.
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We don't need it inside the spider.
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World_bank.py, and
we'll start with our imports.
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So, from urlib.request import urlopen.
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We're going back to Beautiful Soup,
so bs4 import BeautifulSoup, and
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we'll be using a csv file of ISO codes,
so we 'll want to import csv as well.
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Let's define a function to get
the country information, get_country,
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and we'll pass in our country code, And
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just like we've done with Beautiful Soup
in the past, we define our HTML string.
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It's urlopen, And
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it's that request format string
that we saw just a moment ago,
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worldbank.org/v2/countries/, and
we'll use the string formatter,
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country_code, and
let's bring this down to a new line.
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Next, we define our soup object.
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So, we pass in our HTML,
and for our parser,
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since we're dealing with XML,
we can use an XML parser.
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Scraping XML is pretty
straightforward with Beautiful Soup.
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If we look at the results we got for
Ethiopia, we want to get three fields,
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wb:name, wb:region, and
the wb:incomeLevel.
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Let's go ahead and define those.
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Country_name is soup.find( 'wb:name' ),
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Region, ( 'wb:region' ),
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and income_level, soup.find(
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'wb:incomelevel' ), and
it was all lowercase.
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Now, let's print that information out.
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Here's a good example of a time when
we can use the get_text method.
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Get_text, and we'll print the region,
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get_text, And the income_level.
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Now, we can loop through the ISO codes,
and pass them to our get_country method.
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So, if __name__, == '__main__':,
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Let's bring that up on
the screen a little bit,
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I've included a file of ISO codes
that we can open up and read.
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So, file, country_code,
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oop, country_iso_codes.csv,
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want to read that.
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Now, iso_codes, then, will be our reader,
File, and our delimiter is ",".
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Now, we can loop through our file,
and get our information.
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for_code in iso_codes, and we want to
pass in our code into our get_country
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method, And
we want the first one from the list.
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Now, we can run world_bank.
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And it looks like I made
a mistake back up here,
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it wasn't all lowercase,
it's actually incomeLevel.
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Let's try it again, and
we get all of our expected data.
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Again, we could do something else here,
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like saving the information
to a csv file or database.
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Check the teachers' notes for
more resources on that.
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