In Python natural language processing, how do I store results in a database?

In Python natural language processing, storing results in a database can be accomplished using libraries such as SQLite, SQLAlchemy, or even directly using MySQL or PostgreSQL. You’ll want to first ensure your data is structured well and then insert that data into your preferred database. Below is a simple example using SQLite:

import sqlite3 # Connect to SQLite database (or create it if it doesn't exist) conn = sqlite3.connect('nlp_results.db') c = conn.cursor() # Create a table for storing NLP results c.execute(''' CREATE TABLE IF NOT EXISTS nlp_results ( id INTEGER PRIMARY KEY, input_text TEXT, processed_result TEXT ) ''') # Example NLP results input_text = "Natural language processing is fascinating." processed_result = "NLP successfully processed the text." # Insert results into the database c.execute(''' INSERT INTO nlp_results (input_text, processed_result) VALUES (?, ?) ''', (input_text, processed_result)) # Commit changes and close the connection conn.commit() conn.close() `, containing a description and a code block that demonstrates how to store NLP results in a SQLite database using Python. - The keywords and description are placed in their respective `