Tutorial to learn how to handle json in python

2.  Basic NetworkX
› Adding node(s), edges(s) to a graph
› Drawing graphs
› Networks characteristics
 Degree distribution
› Creating network of Twitter

3.  Dictionaries – compound data type
 Found in other languages as “map”,
“associative memories”, or “associative arrays”
 Lists vs Dictionaries
› You can use only integer number as index on lists
Like a[0], a[-1]
› You can use integer numbers and strings as key on
dictionaries(if its value exists)
Like d[0], d[‘foo’], d[‘bar’]

4.  Creating a dictionary
tel = {‘John’:0000, ‘Jane’:0001, ‘Joe’:0002}
 Adding key and value
tel[‘Joan’] = 0003
 Getting value from key
tel[‘Jane’]
 Setting value from key
tel[‘Joe’] = 0004
 Removing value from key
del tel[‘John’]
 Getting key list of a dictionary
tel.keys()

5.  you can nest dictionaries, like
data = {‘one’: {‘one’: 11, ‘two’: 12}, ‘two’: {‘one’: 21, ‘two’: 22}}
print data[‘one’][‘two’]
 Also, you can combine lists and dictionaries, like
data = {‘employees’:[
{‘firstName’: ‘John’, ‘lastName’: ‘Doe’},
{‘firstName’: ‘Anna’, ‘lastName’: ‘Smith’},
{‘firstName’: ‘Peter’, ‘lastName’: ‘Jones’}
]
print data[‘employees’][2][‘firstName’]

6.  JSON (JavaScript Object Notation) is a
lightweight data-interchange format.
 It is easy for humans to read and write.
 It is easy for machines to parse and
generate.
From http://json.org/

7.  A collection of name/value pairs. In various
languages, this is realized as an object,
record, struct, dictionary, hash table, keyed
list, or associative array.
 An ordered list of values. In most languages,
this is realized as an array, vector, list, or
sequence.
 From http://json.org/

8. {"employees":[
{"firstName":"John", "lastName":"Doe"},
{"firstName":"Anna", "lastName":"Smith"},
{"firstName":"Peter", "lastName":"Jones"}
]}
Example from
http://www.w3schools.com/json/

9. import json
 Load json from raw string
data = json.loads(‘{"employees":[
{"firstName":"John", "lastName":"Doe"},
{"firstName":"Anna", "lastName":"Smith"},
{"firstName":"Peter", "lastName":"Jones"}
]}’
print data[‘employees’][2][‘firstName’]
 From json file(save previous json as sample.json)
with open(‘sample.json’, ‘r’) as f:
data = json.load(f)
print data[‘employees’][2][‘firstName’]
 From url
Import urllib2
data = json.load(urllib2.urlopen(‘http://time.jsontest.com’))
print ‘Today is’, data[‘date’]

10.  http://www.ebay.com/
 An online auction and shopping site

11.  HTTP GET URL(search items that its keyword is “harry potter phoenix”
http://svcs.ebay.com/services/search/FindingService/v1?
OPERATION-NAME=findItemsByKeywords
&SERVICE-VERSION=1.0.0
&SECURITY-APPNAME=YourAppID
&RESPONSE-DATA-FORMAT=json
&REST-PAYLOAD
&keywords=harry%20potter%20phoenix
 YourAppID have to be replaced
 More Information:
› http://developer.ebay.com/Devzone/finding/Concepts/MakingACall.html
› http://developer.ebay.com/Devzone/finding/CallRef/index.html

12.  https://github.com/
 An online software development
environment

13.  HTTP GET URL(searches repositories(projects) that its keyword
is “tetris” and written in assembly language)
https://api.github.com/search/repositories?
q=tetris+language:assembly
&sort=stars
&order=desc
 More information:
› https://developer.github.com/v3/
› https://developer.github.com/v3/search/

14.  Saving
import networkx as nx
import pickle
G = Graph()
# some works here
pickle.dump(G, open(‘your_graph.txt’, ‘w’))
 Loading
G = pickle.load(open(‘your_graph.txt’, ‘r’))

15.  Dictionaries(Python data structure)
 Brief explanation of JSON
 Getting JSON Data
› From raw string
› From JSON file
› From URL
 Example: eBay and GitHub
 Saving/loading networks