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You're reading from  The Data Wrangling Workshop - Second Edition

Product typeBook
Published inJul 2020
Reading LevelIntermediate
PublisherPackt
ISBN-139781839215001
Edition2nd Edition
Languages
Python
Tools
Jupyter
Concepts
Data Processing
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Authors (3):
Brian Lipp
Brian Lipp
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Brian Lipp

Brian Lipp is a Technology Polyglot, Engineer, and Solution Architect with a wide skillset in many technology domains. His programming background has ranged from R, Python, and Scala, to Go and Rust development. He has worked on Big Data systems, Data Lakes, data warehouses, and backend software engineering. Brian earned a Master of Science, CSIS from Pace University in 2009. He is currently a Sr. Data Engineer working with large Tech firms to build Data Ecosystems.
Read more about Brian Lipp

Shubhadeep Roychowdhury
Shubhadeep Roychowdhury
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Shubhadeep Roychowdhury

Shubhadeep Roychowdhury holds a master's degree in computer science from West Bengal University of Technology and certifications in machine learning from Stanford. He works as a senior software engineer at a Paris-based cybersecurity startup, where he is applying state-of-the-art computer vision and data engineering algorithms and tools to develop cutting-edge products. He often writes about algorithm implementation in Python and similar topics.
Read more about Shubhadeep Roychowdhury

Dr. Tirthajyoti Sarkar
Dr. Tirthajyoti Sarkar
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Dr. Tirthajyoti Sarkar

Dr. Tirthajyoti Sarkar works as a senior principal engineer in the semiconductor technology domain, where he applies cutting-edge data science/machine learning techniques for design automation and predictive analytics. He writes regularly about Python programming and data science topics. He holds a Ph.D. from the University of Illinois and certifications in artificial intelligence and machine learning from Stanford and MIT.
Read more about Dr. Tirthajyoti Sarkar

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The Requests and BeautifulSoup Libraries

We will take advantage of two Python libraries in this chapter: requests and BeautifulSoup. To avoid dealing with HTTP methods at a lower level, we will use the requests library. It is an API built on top of pure Python web utility libraries, which makes placing HTTP requests easy and intuitive.

BeautifulSoup is one of the most popular HTML parser packages. It parses the HTML content you pass on and builds a detailed tree of all the tags and markup within the page for easy and intuitive traversal. This tree can be used by a programmer to look for certain markup elements (for example, a table, a hyperlink, or a blob of text within a particular div ID) to scrape useful data.

We are going to do a couple of exercises in order to demonstrate how to use the requests library and decode the contents of the response received when data is fetched from the server.

Exercise 7.01: Using the Requests Library to Get a Response from the Wikipedia Home...

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The Data Wrangling Workshop - Second Edition
Published in: Jul 2020Publisher: PacktISBN-13: 9781839215001
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Authors (3)

author image
Brian Lipp

Brian Lipp is a Technology Polyglot, Engineer, and Solution Architect with a wide skillset in many technology domains. His programming background has ranged from R, Python, and Scala, to Go and Rust development. He has worked on Big Data systems, Data Lakes, data warehouses, and backend software engineering. Brian earned a Master of Science, CSIS from Pace University in 2009. He is currently a Sr. Data Engineer working with large Tech firms to build Data Ecosystems.
Read more about Brian Lipp

author image
Shubhadeep Roychowdhury

Shubhadeep Roychowdhury holds a master's degree in computer science from West Bengal University of Technology and certifications in machine learning from Stanford. He works as a senior software engineer at a Paris-based cybersecurity startup, where he is applying state-of-the-art computer vision and data engineering algorithms and tools to develop cutting-edge products. He often writes about algorithm implementation in Python and similar topics.
Read more about Shubhadeep Roychowdhury

author image
Dr. Tirthajyoti Sarkar

Dr. Tirthajyoti Sarkar works as a senior principal engineer in the semiconductor technology domain, where he applies cutting-edge data science/machine learning techniques for design automation and predictive analytics. He writes regularly about Python programming and data science topics. He holds a Ph.D. from the University of Illinois and certifications in artificial intelligence and machine learning from Stanford and MIT.
Read more about Dr. Tirthajyoti Sarkar

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