Python – Extracting URLs from Text Use regular expressions to extract URLs from a text file. The expression extracts text wherever it matches the pattern. Simply use the re module to accomplish this. Example We can use the following program…
Python – Reading a File Backwards When we normally read a file, the file contents are read line by line from the beginning. However, there are cases where we want to read the last line first. For example, if the…
Python – Text Wrapping Text wrapping is necessary when the text you scrape from a source isn’t formatted correctly to fit within the available screen width. This can be done using the following package, which can be installed in your…
Python – Capitalizing and Translating Strings Capitalizing characters is a common requirement in any text processing system. Python uses built-in functions from the standard library to accomplish this. In the following example, we use two string functions, capwords() and upper(),…
Python – Stemming Algorithms In natural language processing, we often encounter situations where two or more words share a common root. For example, the words “agree,” “agreeing,” and “agreeable” all share the same root, “agree.” Any search involving these words…
Python – Bigrams Some English words often appear together. For example, “Sky High,” “Do or Die,” “Best Performance,” “Heavy Rain,” and so on. Therefore, in text documents, we may need to identify such word pairs, which will aid in sentiment…
Python – A Text Processing Environment To successfully create and run the example code in this tutorial, we need to set up an environment that includes both general Python and specialized packages required for data science. We’ll first look at…
Python – Processing Word Documents To read Word documents, we use a module called “docx.” First, install “docx” as shown below, then write a program to use the different functions in the “docx” module to read the entire file paragraph…
Python – Text Summarization Text summarization is the process of generating a summary describing the context of a large amount of text. In the following example, we use the genism module and its summarize function to achieve this. To do…