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Natural Language Processing Fundamentals

You're reading from   Natural Language Processing Fundamentals Build intelligent applications that can interpret the human language to deliver impactful results

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Product type Paperback
Published in Mar 2019
Publisher
ISBN-13 9781789954043
Length 374 pages
Edition 1st Edition
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Authors (2):
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Dwight Gunning Dwight Gunning
Author Profile Icon Dwight Gunning
Dwight Gunning
Sohom Ghosh Sohom Ghosh
Author Profile Icon Sohom Ghosh
Sohom Ghosh
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Toc

Table of Contents (10) Chapters Close

Preface 1. Introduction to Natural Language Processing FREE CHAPTER 2. Basic Feature Extraction Methods 3. Developing a Text classifier 4. Collecting Text Data from the Web 5. Topic Modeling 6. Text Summarization and Text Generation 7. Vector Representation 8. Sentiment Analysis Appendix

Requesting Content from Web Pages

Whenever you visit a web page from your web browser, you actually send a request to fetch its content. This can be done using Python scripts. Packages such as urllib3 and requests are used to do so. Let's look at an exercise to get a better understanding of this concept.

Exercise 41: Collecting Online Text Data

In this exercise, we will collect online data, with the help of requests and urllib3. Follow these steps to implement this exercise:

  1. Use the requests library to request the content of a book available online with the following set of commands:
    import requests
    r = requests.post('https://www.gutenberg.org/files/766/766-0.txt')
    r.status_code

    The preceding code generates the following output:

    Figure 4.10: HTTP status code

    Note

    Here, 200 indicates that we received a proper response from the URL.

  2. To locate the text content of the fetched file, write the following code:
    r.text[:1000]

    The preceding code generates the following...

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