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94 lines
2.8 KiB
Python
94 lines
2.8 KiB
Python
import numpy as np
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import numpy.typing as npt
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from pathlib import Path
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_chars = ' abcdefghijklmnopqrstuvwxyz'
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_char_d = {c: i for i, c in enumerate(_chars)}
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def to_english(array: npt.NDArray[np.int64]) -> str:
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"""Converts a numpy integer array into a corresponding English string.
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Args:
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array: Word in array (int) form. It is assumed that each integer in the
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array is between 0,...,26 (inclusive).
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Returns:
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A (lowercase) string representation of the word.
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"""
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return ''.join(_chars[i] for i in array)
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def to_array(word: str) -> npt.NDArray[np.int64]:
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"""Converts a string of characters into a corresponding numpy array.
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Args:
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word: Word in string form. It is assumed that each character in the
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string is either an empty space ' ' or lowercase alphabetical
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character.
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Returns:
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An array representation of the word.
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"""
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return np.array([_char_d[c] for c in word])
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def get_words(category: str, build: bool = False) -> npt.NDArray[np.int64]:
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"""Loads a list of words in array form.
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If specified, this will recompute the list from the human-readable list of
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words, and save the results in array form.
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Args:
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category: Either 'guess' or 'solution', which corresponds to the list
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of acceptable guess words and the list of acceptable solution words.
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build: If True, recomputes and saves the array-version of the computed
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list for future access.
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Returns:
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An array representation of the list of words specified by the category.
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This array has two dimensions, and the number of columns is fixed at
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five.
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"""
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assert category in {'guess', 'solution'}
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arr_path = Path(__file__).parent / f'dictionary/{category}_list.npy'
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if build:
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list_path = Path(__file__).parent / f'dictionary/{category}_list.csv'
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with open(list_path, 'r') as f:
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words = np.array([to_array(line.strip()) for line in f])
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np.save(arr_path, words)
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return np.load(arr_path)
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def play():
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"""Play Wordle yourself!"""
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import gym
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import gym_wordle
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env = gym.make('Wordle-v0') # load the environment
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env.reset()
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solution = to_english(env.unwrapped.solution_space[env.solution]).upper() # no peeking!
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done = False
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while not done:
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action = -1
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# in general, the environment won't be forgiving if you input an
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# invalid word, but for this function I want to let you screw up user
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# input without consequence, so just loops until valid input is taken
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while not env.action_space.contains(action):
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guess = input('Guess: ')
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action = env.unwrapped.action_space.index_of(to_array(guess))
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state, reward, done, info = env.step(action)
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env.render()
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print(f"The word was {solution}")
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