Given a list of very-substitutes, http://cse2050.drfitz.fit/data/very/very_words.txt, how do I write Python code that uses webscraping techniques to retrieve the data and then stores the data in a dictionary of the form {"bad": "Awful", "good": "Excellent", ... }. Then how do I prompt the user for a sentence and use your dictionary to help improve the user’s vocabulary? For example "Baby, this LED light makes the room very bright" may become "Baby, this LED light makes the room luminous.". How do I also ensure that my code is able to replace multiple very-phrases per sentence?
Given a list of very-substitutes, http://cse2050.drfitz.fit/data/very/very_words.txt, how do I write Python code that uses webscraping techniques to retrieve the data and then stores the data in a dictionary of the form {"bad": "Awful", "good": "Excellent", ... }. Then how do I prompt the user for a sentence and use your dictionary to help improve the user’s vocabulary? For example "Baby, this LED light makes the room very bright" may become "Baby, this LED light makes the room luminous.". How do I also ensure that my code is able to replace multiple very-phrases per sentence?
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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Given a list of very-substitutes, http://cse2050.drfitz.fit/data/very/very_words.txt,
how do I write Python code that uses webscraping techniques to retrieve the data and then stores the data in a
dictionary of the form {"bad": "Awful", "good": "Excellent", ... }. Then how do I prompt the user
for a sentence and use your dictionary to help improve the user’s vocabulary? For example "Baby,
this LED light makes the room very bright" may become "Baby, this LED light makes
the room luminous.". How do I also ensure that my code is able to replace multiple very-phrases per sentence?
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