Using Python to Access Web Data

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Using Python to Access Web Data

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Description

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  • Paid plan: Commit to earning a Certificate—it's a trusted, shareable way to showcase your new skills.

About this course: This course will show how one can treat the Internet as a source of data. We will scrape, parse, and read web data as well as access data using web APIs. We will work with HTML, XML, and JSON data formats in Python. This course will cover Chapters 11-13 of the textbook “Python for Everybody”. To succeed in this course, you should be familiar with the material covered in Chapters 1-10 of the textbook and the first two courses in this specialization. These topics include variables and expressions, conditional execution (loops, branching, and try/except), functions, Python data structures (strings, lists, dictionaries, and tuples), and manipulating files. This course cov…

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When you enroll for courses through Coursera you get to choose for a paid plan or for a free plan

  • Free plan: No certicification and/or audit only. You will have access to all course materials except graded items.
  • Paid plan: Commit to earning a Certificate—it's a trusted, shareable way to showcase your new skills.

About this course: This course will show how one can treat the Internet as a source of data. We will scrape, parse, and read web data as well as access data using web APIs. We will work with HTML, XML, and JSON data formats in Python. This course will cover Chapters 11-13 of the textbook “Python for Everybody”. To succeed in this course, you should be familiar with the material covered in Chapters 1-10 of the textbook and the first two courses in this specialization. These topics include variables and expressions, conditional execution (loops, branching, and try/except), functions, Python data structures (strings, lists, dictionaries, and tuples), and manipulating files. This course covers Python 3.

Created by:  University of Michigan
  • Taught by:  Charles Severance, Associate Professor

    School of Information
Basic Info Course 3 of 5 in the Python for Everybody Specialization Commitment 6 weeks of study, 2-4 hours/week Language English How To Pass Pass all graded assignments to complete the course. User Ratings 4.8 stars Average User Rating 4.8See what learners said Coursework

Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.

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Syllabus


WEEK 1


Getting Started



In this section you will install Python and a text editor. In previous classes in the specialization this was an optional assignment, but in this class it is the first requirement to get started. From this point forward we will stop using the browser-based Python grading environment because the browser-based Python environment (Skulpt) is not capable of running the more complex programs we will be developing in this class.


6 videos, 4 readings expand


  1. Video: Welcome to The Course
  2. Reading: Python Textbook
  3. Reading: Help us learn more about you!
  4. Video: Welcome to Python - Guido van Rossum
  5. Reading: Welcome to Python 3
  6. Reading: Notes on Choice of Text Editor
  7. Video: Windows 10: Installing Python and Writing A Program
  8. Video: Windows: Taking Screen Shots
  9. Video: Macintosh: Using Python and Writing A Program
  10. Video: Macintosh: Taking Screen Shots

Graded: Peer Review: Installing and Running Python Screen Shots

WEEK 2


Regular Expressions (Chapter 11)



Regular expressions are a very specialized language that allow us to succinctly search strings and extract data from strings. Regular expressions are a language unto themselves. It is not essential to know how to use regular expressions, but they can be quite useful and powerful.


4 videos, 1 reading expand


  1. Video: 11.1 - Regular Expressions
  2. Video: 11.2 - Extracting Data
  3. Reading: Python Regular Expression Quick Guide
  4. Video: Bonus: Office Hours - Den Haag
  5. Video: Bonus Interview: Bjarne Stroustrup - C++

Graded: Regular Expressions
Graded: Extracting Data With Regular Expressions

WEEK 3


Networks and Sockets (Chapter 12)
In this section we learn about the protocols that web browsers use to retrieve documents and web applications use to interact with Application Program Interfaces (APIs).


7 videos, 1 reading expand


  1. Video: 12.1 - Networked Technology
  2. Video: 12.2 - Hypertext Transfer Protocol (HTTP)
  3. Video: Worked Example: Sockets (Chapter 12)
  4. Reading: If You Want to Learn
  5. Video: Bonus: Leonard Kleinrock - The First Two Packets on the ARPANET
  6. Video: Bonus Video: Robert Cailliau - co-Inventor of the Web
  7. Video: Bonus: Office Hours - Atlanta GA (Buckhead)
  8. Video: Fun: Dr. Chuck @ CNN Reading the News

Graded: Networks and Sockets
Graded: Understanding the Request / Response Cycle

WEEK 4


Programs that Surf the Web (Chapter 12)
In this section we learn to use Python to retrieve data from web sites and APIs over the Internet.


8 videos, 1 reading expand


  1. Video: 12.3 - Unicode Characters and Strings
  2. Video: 12.4 - Retrieving Web Pages
  3. Video: Worked Example: Using Urllib (Chapter 12)
  4. Video: 12.5 - Parsing Web Pages
  5. Video: Worked Example: BeautifulSoup (Chapter 12)
  6. Reading: Notes Regarding the Use of BeautifulSoup
  7. Video: Bonus: Office Hours - Montreal
  8. Video: Bonus Interview: Tim Berners-Lee - Inventing the Web
  9. Video: Fun: I Got My Mojo Working - Geneva, Switzerland

Graded: Reading Web Data From Python
Graded: Scraping HTML Data with BeautifulSoup
Graded: Assignment: Following Links in HTML Using BeautifulSoup

WEEK 5


Web Services and XML (Chapter 13)
In this section, we learn how to retrieve and parse XML (eXtensible Markup Language) data.


8 videos expand


  1. Video: 13.1 - Data on the Web
  2. Video: 13.2 eXtensible Markup Language (XML)
  3. Video: 13.3 - XML Schema
  4. Video: 13.4 - Parsing XML
  5. Video: Worked Example: XML (Chapter 13)
  6. Video: Interview: Roy Fielding - Understanding the REST Architecture
  7. Video: Bonus: Office Hours - Boston
  8. Video: Bonus Video: Ian Horrocks / RDF / OWL (Advanced)

Graded: eXtensible Markup Language
Graded: Extracting Data from XML

WEEK 6


JSON and the REST Architecture (Chapter 13)
In this module, we work with Application Program Interfaces / Web Services using the JavaScript Object Notation (JSON) data format.


12 videos, 2 readings expand


  1. Video: 13.5 - JavaScript Object Notation (JSON)
  2. Video: Worked Example: JSON (Chapter 13)
  3. Video: Interview: Douglas Crockford - Discovering JSON
  4. Video: 13.6 - Service Oriented Approach
  5. Video: Video: Service Oriented Architectures
  6. Video: 13.7 - Using Application Programming Interfaces
  7. Video: Worked Example: GeoJSON API (Chapter 13)
  8. Video: 13.8 - Securing API Requests
  9. Video: Worked Example: Twitter API (Chapter 13)
  10. Video: Bonus: Office Hours - Melbourne, AU
  11. Video: Bonus: Office Hours - Santa Monica, CA
  12. Video: Bonus: Class Reunion at Bletchley Park
  13. Reading: Please Rate this Course on Class-Central
  14. Reading: Post-Course Survey

Graded: REST, JSON, and APIs
Graded: Extracting Data from JSON
Graded: Using the GeoJSON API
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