Using Python 3 9 and BeautifulSoup to Web Scrape Market, Economic, Financial and Historical Compa...

Using Python 3 9 and BeautifulSoup to Web Scrape Market, Economic, Financial and Historical Company Earnings Data | 34.67 MB

Title: Using Python 3.9 and BeautifulSoup to Web Scrape Market, Economic, Financial and Historical Company Earnings Data
Author: Lee, John
Category: Nonfiction, Computers, Database Management, Data Processing, Programming, Programming Languages, Internet
Language: English | 159 Pages | ISBN: 9781786464293

Description:
Successfully scrape data from any website with the power of Python 3.x

About This Book

• A hands-on guide to web scraping using Python with solutions to real-world problems
  
• Create a number of different web scrapers in Python to extract information
  
• This book includes practical examples on using the popular and well-maintained libraries in Python for your web scraping needs
  

Who This Book Is For
This book is aimed at developers who want to use web scraping for legitimate purposes. Prior programming experience with Python would be useful but not essential. Anyone with general knowledge of programming languages should be able to pick up the book and understand the principals involved.

What You Will Learn

• Extract data from web pages with simple Python programming
  
• Build a concurrent crawler to process web pages in parallel
  
• Follow links to crawl a website
  
• Extract features from the HTML
  
• Cache downloaded HTML for reuse
  
• Compare concurrent models to determine the fastest crawler
  
• Find out how to parse jаvascript-dependent websites
  
• Interact with forms and sessions
  

In Detail
The Internet contains the most useful set of data ever assembled, most of which is publicly accessible for free. However, this data is not easily usable. It is embedded within the structure and style of websites and needs to be carefully extracted. Web scraping is becoming increasingly useful as a means to gather and make sense of the wealth of information available online.
This book is the ultimate guide to using the latest features of Python 3.x to scrape data from websites. In the early chapters, you'll see how to extract data from static web pages. You'll learn to use caching with databases and files to save time and manage the load on servers. After covering the basics, you'll get hands-on practice building a more sophisticated crawler using browsers, crawlers, and concurrent scrapers.
You'll determine when and how to scrape data from a jаvascript-dependent website using PyQt and Selenium. You'll get a better understanding of how to submit forms on complex websites protected by CAPTCHA. You'll find out how to automate these actions with Python packages such as mechanize. You'll also learn how to create class-based scrapers with Scrapy libraries and implement your learning on real websites.
By the end of the book, you will have explored testing websites with scrapers, remote scraping, best practices, working with images, and many other relevant topics.

Style and approach
This hands-on guide is full of real-life examples and solutions starting simple and then progressively becoming more complex. Each chapter in this book introduces a problem and then provides one or more possible solutions.

DOWNLOAD:


https://rapidgator.net/file/e69765c105bcae578ece1de1901775a9/Using_Python_3.9_and_BeautifulSoup_to_Web_Scrape_Market_Economic_Financial_and_Historical_Company_Earnings_Data.epub

https://nitroflare.com/view/0CC751EC1301E76/Using_Python_3.9_and_BeautifulSoup_to_Web_Scrape_Market_Economic_Financial_and_Historical_Company_Earnings_Data.epub

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