DEVELOPMENT AND TESTING OF AUTOMATION TOOLS USING PYTHON

Abstract

In this paper, algorithms are developed and tested to automate tasks like web scraping, extraction of stock price data and its analysis and Bulk Email generation. Web scraping is a special method used for the extraction of data from the World Wide Web (WWW) and saving it to a file system or database for various types of data analysis. It is sometimes referred to as web extraction or web harvesting. The Hypertext Transfer Protocol (HTTP) is frequently used to scrape web data. Web scraping is widely recognized as an effective and powerful technique for gathering significant volumes of data due to the massive amount of heterogeneous data continuously generated on the WWW. In this paper algorithms are designed for storing and searching details of a product in the Flipkart website, predicting stock market prices, and sending automated mails to a number of recipients. Algorithms are coded in Python using libraries like Tkinter for GUI purpose, beautifulSoup for extracting data from HTML and XML format, urlLib for URL handling and TimeSeries for  timestamps and tracing open, high, low, close, volume of the equity for stock market pricing and analysis.