Editing Community Data Science Workshops (Spring 2014)/Saturday May 3rd lecture

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== Lecture Outline ==

# Introduction to APIs
#* definition of API: just an interface for programs
#* definition of web API
#** way to ask for data (almost always a URL)
#** way to get data back (almost always in a format called JSON)
#** every API is different, and documented
#* to use APIs to build a dataset we will need:
#** all our tools from last session: variables, etc
#** the ability to open urls on the web
#** the ability to create custom URLS
#** the ability to save to files 
#** the ability to understand (i.e., parse) JSON data that APIs usually give us
# Review material from last session
#* variables
#* lists
#* dictionaries
#* if statements
#* for loops
#* printing
#* modules
# New programming concepts:
#* urllib2 and urlopen
#* interpolate variables into a string using % and %()s
#* open files and write to them
# [http://placekitten.com/ placekitten.com]
#* API that takes specially crafted URLs and gives appropriately sized picture of kittens
#* example of placekitten in browser
#** visit the API documentation
#** kittens of different sizes
#** kittens in greyscale or color
#* show how to use place 
#* write a small program to grab arbitrary square from placekitten by asking for the size on standard in
# JSON file (JavaScript Object Notation)
#* what is json: useful for more structure data
#* import json; json.loads()
#* like Python (except no single quotes)
#* simple lists, dictionaries
#* can reflect more complicated data structures
#* Example file at http://mako.cc/cdsw.json
#* download it and parse it
# Other APIs
#* every API is different, so read the documentation!
#* for popular APIs, there are python modules that help you make requests and parse json!
#* rate limiting
#* authenticaiton
#* text encoding issues