| import string | |
| import nltk | |
| nltk.download('punkt') | |
| from nltk.tokenize import word_tokenize | |
| def preprocess_text(texts): | |
| """ | |
| Preprocesses a list of texts by converting to lowercase, removing punctuation, and tokenizing. | |
| Args: | |
| texts (list): List of text strings to preprocess. | |
| Returns: | |
| list: List of preprocessed and tokenized texts. | |
| """ | |
| processed_texts = [] | |
| for text in texts: | |
| text = text.lower() | |
| text = text.translate(str.maketrans('', '', string.punctuation)) | |
| tokens = word_tokenize(text) | |
| processed_texts.append(tokens) | |
| return processed_texts | |