Exploring Anagrams in Python: A Step-by-Step Guide
n this blog post, we will embark on a journey through the world of anagrams using Python. We will follow along with the guidance provided by an instructor to load a dictionary of words, clean the data, and ultimately create anagrams. Let’s dive in!
Loading the Dictionary
To kick things off, we load a list of words from a file named “words.txt,” which contains the 1934 dictionary commonly found in UNIX systems. This dictionary serves as our foundation for exploring anagrams in Python.
# Load the dictionary file containing words
words_set = set()
with open('words.txt', 'r') as file:
for line in file:
word = line.strip().lower()
words_set.add(word)
Cleaning and Preparing the Data
Upon loading the dictionary, we encounter two issues: trailing newline characters and capitalized words. To address these, we utilize Python string methods to strip whitespace and convert all words to lowercase, ensuring uniformity in our data.
# Clean the data by stripping whitespace and converting to lowercase
cleaned_words = {word.strip().lower() for word in words_set}
Identifying Anagrams
With our cleaned dataset in hand, we move on to identifying anagrams by computing word signatures and grouping words with identical signatures together. This process enables us to efficiently find anagrams within the dictionary.
# Function to compute the signature of a word
def compute_signature(word):
return ''.join(sorted(word))
# Create a dictionary to store words grouped by their signatures
anagram_dict = {}
for word in cleaned_words:
signature = compute_signature(word)
anagram_dict.setdefault(signature, []).append(word)
# Function to find anagrams of a given word
def find_anagrams(input_word):
signature = compute_signature(input_word)
return anagram_dict.get(signature, [])
Conclusion
In this blog post, we have navigated through the process of loading a dictionary, cleaning the data, and uncovering anagrams using Python. By applying Python’s string manipulation capabilities and data structures, we have successfully embarked on an anagram exploration journey.
Feel free to expand upon this project, experiment with different languages, or challenge yourself with larger datasets to further enhance your understanding of anagrams and Python programming.