<jupyter_start><jupyter_text>Load the default spacy NLP model<jupyter_code>nlp_model = spacy.load('en')<jupyter_output><empty_output><jupyter_text>Create a task object<jupyter_code>item1 = Task('buy dog food today')
item1<jupyter_output><empty_output><jupyter_text>Create a spacy doc object from the task text.<jupyter_code>item1_doc = nlp_model(item1.text)
item1_doc
[(token.lemma_, token.dep_) for token in item1_doc]<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.1091314031180401, 'fraction_numerical': 0.013363028953229399, 'mean_word_length': 10.538461538461538, 'pattern_counts': {'":': 0, '<': 13, '<?xml version=': 0, '>': 13, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '3', 'dir': 'jupyter-structured-clean-dedup', 'id': '290788', 'license': 'BSD-3-Clause', 'n_tokens_mistral': 175, 'n_tokens_neox': 173, 'n_words': 31, 'path': 'notebooks/task_practice.ipynb', 'repo_name': 'mnguyenngo/to-do-grid', 'size': '449'}