Question

When you're working with text, regular expressions come in very handy. We'll apply them in a number of ways to our featured text sample. It's a poem titled "Ode on the Mammoth Cheese," written by James McIntyre in 1866 in homage to a seven-thousand-pound cheese that was crafted in Ontario and sent on an international tour. If you'd rather not type all of it, use your favorite search engine and cut and paste the words into your Python program, or just grab it from Project Gutenberg. Call the text string mammoth.

Short answer

Copy and paste the poem into a Python string variable named `mammoth`. Confirm it by printing the variable.

Step-by-step solution

Acquire the Text Source

Search for "Ode on the Mammoth Cheese" by James McIntyre using your preferred search engine or access it via Project Gutenberg. Copy the entire text.

Save the Text as a String

Paste the copied text into your Python program and assign it to a variable named `mammoth`. This variable now contains the entire poem as a string, which can be used for further processing.

Confirm Successful Assignment

To check if the text has been correctly stored, you can print the variable `mammoth` and visually inspect the output to ensure it matches the poem you copied.

Key concepts

Regular Expressions

Regular expressions, often abbreviated as regex, are powerful tools for managing and manipulating text. They help identify patterns within a text, which can be immensely useful in text processing tasks. For example, if you want to find all instances of the word 'cheese' in a text, regular expressions can do this easily.
Using regex may initially seem complex, but it becomes more intuitive over time. In Python, the `re` module provides support for regular expressions. To utilize it, you first need to import the module using `import re`.

• Pattern Matching: You can use functions like `re.search()` to check if a pattern exists in the text, or `re.findall()` to extract all occurrences of a pattern.
• Substitution: The `re.sub()` function lets you replace parts of a string that match a pattern with a different substring.
• Splitting: Use `re.split()` to split a string into a list using a regex pattern as the delimiter.

Remember, escaping special characters and correctly framing your regex patterns is critical to ensure accurate text processing. Practice makes perfect with regex!

Python Programming

Python programming is a highly versatile language, perfect for handling text processing with ease. One of the reasons behind Python's popularity is its powerful libraries that allow for efficient manipulation of text.
When working with text, the ability to store and manage large text bodies is crucial. Assigning a poem to a variable in Python is straightforward, as seen in the original exercise where the text was stored in the `mammoth` variable. This is how Python handles strings:

• Strings are sequences of characters enclosed in single or double quotes.
• You can concatenate strings using the `+` operator or format them using techniques like f-strings (e.g., `f"Hello, {name}")`.
• Python strings are immutable, meaning once they are created, they cannot be modified. Creating a new string is necessary for modifications.

Alongside regular expressions, Python's built-in string methods (such as `.lower()`, `.upper()`, and `.strip()`) provide additional ways to clean and manipulate text efficiently.

Text Sources

Text sources refer to the origin of the textual data you're working with. In the context of text processing and analysis, acquiring a reliable text source is fundamental. The original exercise suggests sourcing the poem "Ode on the Mammoth Cheese" from Project Gutenberg, a prominent source of free eBooks.
Determining your text source depends on your project needs. Here are a few considerations:

• **Accessibility:** Ensure that the text source can be accessed easily and complies with usage rights and copyright laws.
• **Format:** Text can come in a variety of formats such as plain text, HTML, PDF, or others. Knowing the format ahead of time helps in choosing the right processing tools.
• **Completeness:** Make sure the text is complete and unaltered if accuracy is necessary for the task at hand.

In Python programming, getting text from an online source can be done through libraries like `requests`, which allows you to fetch web pages directly into your Python program. With the text in hand, you can then move on to processing and analyzing it with confidence.