Skip to main content
100%

find all the words that can be built using the letters in a list, as in Scrabble™.

✓ Published0🌍 Public
Aamundo
Last edited Feb 10, 2010
Created on Feb 10, 2010

This example finds all valid words that can be formed from a given set of letters, as in Scrabble™. It reads a system dictionary file (`/usr/share/dict/words`) and iterates through each word, checking whether every letter in the candidate word appears in the tile string and that no letter is used more times than it appears in the tiles. The core logic uses Python’s `set.issubset` for letter containment and `str.count` to verify letter frequencies. The user supplies the tile letters as a command-line argument, and matching words are printed to standard output.

AI-generated description

Similar vizzes

Loading thumbnail…

A simple tool for finding the highest scoring words with a scrabble rack

This tool finds and displays the highest-scoring words playable from a given Scrabble rack. It reads a system dictionary file, filters words to those that can be spelled with the rack’s letters, and ranks them by their Scrabble letter values. The output is a plain-text list of scores and matching words, sorted ascending. The code uses Python’s built-in file iteration, string methods, and list comprehensions, with no external visualization libraries. It demonstrates a simple algorithmic approach to word scoring and rack-based filtering.

Aamundo
65% match
Loading thumbnail…

Gist 0d3ef677475862ba439fd5dacfd4a60d

The visualization maps the scoring patterns of five-letter words, showing how letter positions and letter values contribute to total word scores. It displays a grid or distribution of words, likely sorted or clustered by score, with each word’s score calculated from per-letter point values and a bonus for non-repeated letters. The implementation uses Python’s pandas to load and transform the word list, adding columns for each letter’s position and score, while the letter-to-value mapping follows standard Scrabble tile distributions. The final score sums individual letter scores and adds a two-point bonus when all letters are unique, as seen in the `duplicates` logic. The rendering itself is not shown in the code, but the data processing relies on pandas dataframes and string operations to derive the visualization’s underlying dataset.

CConorAspell
59% match
Loading thumbnail…

Gist 901f4da6657c981e68620127130e3f23

This example presents a heuristic strategy for a word-guessing game, prioritizing candidate words based on letter values and positional constraints. The visualization shows a sorted list of possible words, with scores derived from Scrabble-like letter values, adjusted by a penalty for duplicate letters and a bonus for letters already eliminated from the vocabulary. The code uses pandas to map scores across columns (first through fifth) and applies custom logic via `special_heuristic` to filter vacant positions and remaining letters. The approach relies on DataFrame operations for sorting and filtering, with no external visualization library, as the output is a single recommended word.

CConorAspell
58% match
Loading thumbnail…

Obligatory wordle coding

This example shows a command-line Wordle solver that filters the remaining possible five-letter words based on prior guesses and their result patterns. It uses the `click` library to parse comma-separated guesses and results, then computes letter constraints through Python list comprehensions and the `itertools.product` function to generate candidate words. The script prints all possibilities, or a message indicating too many when the combination count exceeds 10,000, leveraging the `math.prod` function for efficient count calculation.

Aandyreagan
58% match
Loading thumbnail…

Gist 2ddd23e185defb909f5b269d22e7849e

This example demonstrates a Wordle-solving filter tool that narrows down possible answer words based on player feedback. It shows how the filter function progressively eliminates candidates using three types of constraints: letters known to be absent, letters confirmed in specific positions, and letters that are present but misplaced. The code uses pandas DataFrame operations with string containment checks and column-based equality comparisons to refine the word list. While no visualization library is used, the logic relies on pandas’ vectorized string methods and boolean indexing to efficiently process the word list, making it a practical data-cleaning component for a word-guessing game interface.

CConorAspell
56% match
Loading thumbnail…

Finding reduplicated words in a wordlist

This example scans a wordlist for reduplicated words—words whose letter pairs repeat—by analyzing bigram frequency. It computes the median frequency of all bigrams in each word and prints the word if that median equals 2, indicating a likely reduplication. The Python script uses `collections.Counter` to tally bigrams, a custom `median()` function, and `fileinput` to read lines from standard input. The output is a filtered list of words, showing a simple text-based visualization of the detected pattern.

Aamundo
56% match
Loading thumbnail…

wordsearch fun

A word search puzzle presents a 15x15 grid of letters alongside a list of hidden words. Players click and drag across the grid to select letters, with valid horizontal, vertical, or diagonal selections highlighted as they are traced. The game uses vanilla JavaScript to generate the grid, placing words randomly and filling empty cells with random letters. Found words are marked in the grid and crossed off the list, with a "New Game" button resetting the puzzle for a fresh challenge.

KKareena
53% match
Loading thumbnail…

Make a Word

The visualization is a word-guessing game that displays seven letters and prompts the user to submit a valid word. The user can guess a word, shuffle the letters, or generate a new random set of letters. The game tracks the number of wins and losses, and shows a message indicating whether each guess is correct or wrong. The code uses plain JavaScript DOM methods like `querySelector`, `getElementById`, and `innerHTML` to manage the interface, with the letter set generated by combining random consonants and vowels.

FFrankieFabuloso
51% match