Community Data Science Workshops (Spring 2015)/Day 2 Lecture

In which you learn how to use Python and web APIs to meet the likes of these guys!

Lecture Outline

Introduction and context

• You can write some tools in Python now. Congratulations!
• Today we'll learn how to find/create data sets
• Next week we'll get into data science (asking and answering questions)

Outline

• What did we learn in Session 1?
• New data type: Tuple!
• What is an API?
• How do we use one to fetch interesting datasets?
• How do we write programs that use the internet?
• How can we use the placebear API to fetch bear pictures?
• Introduction to structured data (JSON)
• How do we use APIs in general?

What is a (web) API?

• API: a structured way for programs to talk to each other (aka an interface for programs)
• Web APIs: like a website your programs can visit (you:a website::your program:a web API)

How do we use an API to fetch datasets?

Basic idea: your program sends a request, the API sends data back

• Where do you direct your request? The site's API endpoint.
  • For example: Wikipedia's web API endpoint is http://en.wikipedia.org/w/api.php
• How do I write my request? Put together a URL; it will be different for different web APIs.
  • Check the documentation, look for code samples
• How do you send a request?
  • Python has modules you can use, like requests (they make HTTP requests)
• What do you get back?
  • Structured data (usually in the JSON format)
• How do you understand (i.e. parse) the data?
  • The requests module can do that using the .json() function!

How do we write Python programs that make web requests?

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

Session 1 review

• Navigating in the terminal and using it to run programs
• Writing Python:
  • using variables to manipulate data
  • types of data: strings, integers, lists, dictionaries
  • if statements
  • for loops
  • printing
  • importing modules, so you can use code other people have written for you!

New programming concepts

• interpolate variables into a string using % and %()s
• requests
• open files and write to them
• parsing a string (turning the string into a data structure we can manipulate)

How do we use an API to fetch pictures of bears?

placebear.com

• API that takes specially crafted URLs and gives appropriately sized picture of bears
• Exploring placebear in a browser:
  • visit the API documentation
  • bears of different sizes
  • bears in greyscale or color
• Now we write a small program to grab an arbitrary square from placebear by asking for the size on standard in (placebear_input.py)

Introduction to structured data (JSON, JavaScriptObjectNotation)

• what is json: useful for more structured 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 (e.g., with a program like parse_cdswjson.py)

Using other APIs

• every API is different, so read the documentation!
• If the documentation isn't helpful, search online
• for popular APIs, there are python modules that help you make requests and parse json

Possible issues:

• rate limiting
• authentication
• text encoding issues

Lecture Slides (From Fall 2014)

• Slides (PDF) — For viewing
• Slides (ODP Libreoffice Slides Format) — For editing and modification