How does SQL integrate with Python?

2 Step 2: Create or connect to a database

The next step is to create or connect to a database using the sqlite3.connect() function. This function takes a database name as an argument and returns a connection object that represents the database. If the database does not exist, it will be created automatically. You can assign the connection object to a variable, such as conn, for later use. For example: conn = sqlite3.connect('example.db')

3 Step 3: Create a cursor object

A cursor object is an interface that allows you to execute SQL statements and fetch the results. You can create a cursor object from the connection object using the cursor() method. You can assign the cursor object to a variable, such as cur, for later use. For example: cur = conn.cursor()

4 Step 4: Execute SQL statements

You can execute SQL statements using the execute() method of the cursor object. This method takes a SQL query as an argument and executes it on the database. You can use any valid SQL syntax, such as CREATE TABLE, INSERT, SELECT, UPDATE, DELETE, etc. For example, to create a table called customers with four columns, you can use:

cur.execute('''
CREATE TABLE customers (
  id INTEGER PRIMARY KEY,
  name TEXT,
  email TEXT,
  phone TEXT
)
''')        

6 Step 6: Commit and close the connection

The last step is to commit and close the connection to the database. Committing the connection means saving the changes you made to the database, such as creating or modifying tables or data. You can commit the connection using the commit() method of the connection object. For example: conn.commit() Closing the connection means releasing the resources and ending the communication with the database. You can close the connection using the close() method of the connection object. For example: conn.close() By following these six steps, you can integrate SQL with Python and leverage the power of both languages for data management and analysis.