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    <p>The first thing I would do when working with a big lump of json, is try to get it into a more readable format. <a href="http://jsonformatter.curiousconcept.com" rel="noreferrer">This online json formatting tool</a> should do the job.</p> <p>Here's some code that will get all the trend names:</p> <pre><code>import urllib2 import json url = 'http://api.twitter.com/1/trends/44418.json' # download the json string json_string = urllib2.urlopen(url).read() # de-serialize the string so that we can work with it the_data = json.loads(json_string) # get the list of trends trends = the_data[0]['trends'] # print the name of each trend for trend in trends: print trend['name'] </code></pre> <p>Or you can do it all in one line:</p> <pre><code>names = [trend['name'] for trend in the_data[0]['trends']] for name in names: print name </code></pre> <p>Both will result in:</p> <pre> #throwagrenade Rebecca Black Eric Abidal #questionsihate #juniordoctors Smiley Culture Lily Allen Wes Brown Pandev Ray Wilkins </pre> <p><strong>Relevant reading:</strong></p> <p><a href="http://docs.python.org/library/json.html" rel="noreferrer">Python docs on json</a> (although you should only really need <code>json.loads()</code>)</p> <p><a href="http://diveintopython.net/" rel="noreferrer"><em>Dive Into Python</em></a>'s sections on <a href="http://diveintopython.net/getting_to_know_python/lists.html" rel="noreferrer">lists</a> and <a href="http://diveintopython.net/getting_to_know_python/dictionaries.html" rel="noreferrer">dictionaries</a>.</p>
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    1. COthanks! great response, appreciate the extra reading material as well.
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      1. USAlex Karpowitsch
    2. COI'd also recommend the new [Dive Into Python 3](https://diveintopython3.ep.io/) - dictionaries and lists are mentioned in the section [Chapter 2. Native Datatypes](https://diveintopython3.ep.io/native-datatypes.html).
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