This course teaches you to fetch and process data from services on the Internet. It covers Python list comprehensions and provides opportunities to practice extracting from and processing deeply nested data. You'll also learn how to use the Python requests module to interact with REST APIs and what to look for in documentation of those APIs. For the final project, you will construct a “tag recommender” for the flickr photo sharing site.
The course is well-suited for you if you have already taken the "Python Basics" and "Python Functions, Files, and Dictionaries" courses (courses 1 and 2 of the Python 3 Programming Specialization). If you are already familiar with Python fundamentals but want practice at retrieving and processing complex nested data from Internet services, you can also benefit from this course without taking the previous two.
This is the third of five courses in the Python 3 Programming Specialization.
提供方
教学大纲 - 您将从这门课程中学到什么
周
1完成时间为 6 小时
Nested Data and Nested Iteration
In week one the video lectures and activities from the Runestone textbook will cover more complex data structures. By the end of this week, you will have learned how to process json formatted data, traverse nested data using nested iteration, and extract values from nested data.
15 个视频 （总计 127 分钟）, 9 个阅读材料, 3 个测验
15 个视频
How to Use the Interactive Textbook14分钟
Introduction - Nested Data1分钟
Nested Lists17分钟
Nested Dictionaries6分钟
JSON Format and the JSON Module7分钟
Conclusion - Nested Data1分钟
Introduction - Nested Iteration1分钟
Nested Iteration19分钟
Structuring Nested Data6分钟
Shallow Copies7分钟
Deep Copies10分钟
Extracting from Nested Data13分钟
A Worked Example of Nested Iteration6分钟
Conclusion - Nested Data1分钟
9 个阅读材料
Syllabus10分钟
Help Us Learn More About You!10分钟
Introduction: Nested Data and Nested Iteration10分钟
Nested Dictionaries10分钟
Processing JSON Results10分钟
Nested Iteration10分钟
Structuring Nested Data10分钟
Deep and Shallow Copies10分钟
Extracting from Nested Data10分钟
1 个练习
Optional - What Did You Use to Practice This Week?4分钟
周
2完成时间为 4 小时
Map, Filter, and List Comprehensions
In week two you will be learning more advanced forms of accumulation. By the end of the week, you will have learned how to use the map and filter functions in combination with functions to transform or filter out data and store the resulting data in a new object. You will have also learned how to accumulate data using a list comprehension.
13 个视频 （总计 75 分钟）, 5 个阅读材料, 3 个测验
13 个视频
Map11分钟
Filter8分钟
Conclusion - Map and Filter2分钟
Introduction - List Comprehensions1分钟
List Comprehensions9分钟
List Comprehensions Example 17分钟
List Comprehensions Example 29分钟
Conclusion - List Comprehensions1分钟
Introduction - Zip40
Zip7分钟
The Hangman Blanked Function13分钟
Conclusion - Zip1分钟
5 个阅读材料
Introduction: Map, Filter, and List Comprehensions10分钟
Map10分钟
Filter10分钟
List Comprehensions10分钟
Zip10分钟
1 个练习
Optional - What Did You Use to Practice This Week?4分钟
周
3完成时间为 6 小时
Internet APIs
In week three you will learn how to request data from the internet using Application Programming Interfaces (APIs). By the end of the week, you will have learned how to access data from a few APIs, cache data that you have requested, and also learned how to read and work with other APIs that were not touched on in the module.
21 个视频 （总计 118 分钟）, 13 个阅读材料, 2 个测验
21 个视频
URLs, Domain Names, and IP Addresses5分钟
Routing3分钟
HTTP: Behind the Scenes5分钟
URL Query Parameters3分钟
REST API URLs3分钟
The requests Module5分钟
Conclusion - REST APIs2分钟
Introduction - Using REST APIs1分钟
Generating URLs with requests.get5分钟
Reading API Documentation: Datamuse7分钟
Debugging Calls to requests.get5分钟
Caching Response Content8分钟
The requests_with_caching Module8分钟
Conclusion - Using REST APIs1分钟
Introduction - Practice with REST APIs49
iTunes API7分钟
flickr API15分钟
Conclusion - Practice with REST APIs1分钟
Fun with the Google Places API19分钟
Introduction - Final Course Project2分钟
13 个阅读材料
How the Internet Works10分钟
Anatomy of URLs10分钟
The HTTP Protocol10分钟
Using REST APIs10分钟
Fetching a Page with the requests Module10分钟
Generating URLs with requests.get10分钟
Reading API Documentation: Datamuse10分钟
Debugging Calls to requests.get10分钟
Caching Response Content10分钟
Searching for Media on iTunes10分钟
Searching for Tags on Flickr10分钟
Unicode for Non-English Characters10分钟
Course Feedback10分钟
4.7
30 个审阅热门审阅
Great course and instructors, ample time and resources to practice, the graded tests are challenging and require good understanding of the course material which I appreciate
Great course, with so many interactive exercises it really help to clear some confusion and make abstract concept easier to understand,
讲师
Paul Resnick
Michael D. Cohen Collegiate ProfessorSchool of Information
Jaclyn Cohen
LecturerSchool of Information
关于 密歇根大学
The mission of the University of Michigan is to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values, and in developing leaders and citizens who will challenge the present and enrich the future.
关于 Python 3 Programming 专项课程
This specialization teaches the fundamentals of programming in Python 3. We will begin at the beginning, with variables, conditionals, and loops, and get to some intermediate material like keyword parameters, list comprehensions, lambda expressions, and class inheritance.
You will have lots of opportunities to practice. You will also learn ways to reason about program execution, so that it is no longer mysterious and you are able to debug programs when they don’t work.
By the end of the specialization, you’ll be writing programs that query Internet APIs for data and extract useful information from them. And you’ll be able to learn to use new modules and APIs on your own by reading the documentation. That will give you a great launch toward being an independent Python programmer.
This specialization is a good next step for you if you have completed Python for Everybody but want a more in-depth treatment of Python fundamentals and more practice, so that you can proceed with confidence to specializations like Applied Data Science with Python.
But it is also appropriate as a first set of courses in Python if you are already familiar with some other programming language, or if you are up for the challenge of diving in head-first.
常见问题
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