Community Data Science Course (Spring 2015)/Day 4 Lecture: Difference between revisions
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[[File:Highfivekitten.jpeg|200px|thumb|In which you learn how to use Python and web APIs to meet the likes of her!]] | [[File:Highfivekitten.jpeg|200px|thumb|In which you learn how to use Python and web APIs to meet the likes of her!]] | ||
== Lecture Outline == | == Lecture Outline == | ||
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;Outline: | ;Outline: | ||
* What is an API? | * What is an API? | ||
* How do we use one to fetch interesting datasets? | * How do we use one to fetch interesting datasets? | ||
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* the ability to save to files | * the ability to save to files | ||
* the ability to understand (i.e., parse) JSON data that APIs usually give us | * the ability to understand (i.e., parse) JSON data that APIs usually give us | ||
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* requests | * requests | ||
* open files and write to them | * open files and write to them | ||
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* can reflect more complicated data structures | * can reflect more complicated data structures | ||
* Example file at http://mako.cc/cdsw.json | * Example file at http://mako.cc/cdsw.json | ||
* | * You can parse data directly with <code>.json()</code> on a <code>requests</code> call | ||
; Using other APIs | ; Using other APIs | ||
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* authentication | * authentication | ||
* text encoding issues | * text encoding issues | ||
== Other Potentially Resources == | |||
My friend Frances gave a version of this lecture last year and create slides. They are written for Python 2, so the code might not all work (remember, use <Code>print()</code> with parentheses) but the basic ideas might be helpful: | |||
* [http://mako.cc/teaching/2014/cdsw-autumn/lecture2-web_apis.pdf Slides (PDF)] — For viewing | |||
* [http://mako.cc/teaching/2014/cdsw-autumn/lecture2-web_apis.odp Slides (ODP Libreoffice Slides Format)] — For editing and modification |
Latest revision as of 00:18, 21 April 2015
Lecture Outline[edit]
- 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 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 placekitten API to fetch kitten 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)
- Python has modules you can use, like
- What do you get back?
- Structured data (usually in the JSON format)
- How do you understand (i.e. parse) the data?
- There's a module for that!
- 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
- New programming concepts
- interpolate variables into a string using % and %()s
- requests
- open files and write to them
- How do we use an API to fetch kitten pictures?
- API that takes specially crafted URLs and gives appropriately sized picture of kittens
- Exploring placekitten in a browser:
- visit the API documentation
- kittens of different sizes
- kittens in greyscale or color
- Now we write a small program to grab an arbitrary square from placekitten by asking for the size on standard in: placekitten_raw_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
- You can parse data directly with
.json()
on arequests
call
- 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
Other Potentially Resources[edit]
My friend Frances gave a version of this lecture last year and create slides. They are written for Python 2, so the code might not all work (remember, use print()
with parentheses) but the basic ideas might be helpful:
- Slides (PDF) — For viewing
- Slides (ODP Libreoffice Slides Format) — For editing and modification