![]() ![]() Notice that we wrapped our SQL query in quotes – this is important. Now that we have a cursor object, we can use it to run SQL queries in the following style: cur.execute("YOUR-SQL-QUERY-HERE ") We’ll create a variable cur to hold our cursor object: cur = conn.cursor() Simply put, a cursor object allows us to execute SQL queries against a database. Now that we’ve created a database connection object, our next task is to create a cursor object. However, for the purposes of this tutorial, and for most use cases you’ll run into, you’ll use the method we described earlier. This is a great way to generate databases that can be used for testing purposes, as they exist only in RAM. In-Memory DatabasesĪnother way of generating databases using SQLite in Python is to create them in memory. The connect function creates a connection to the SQLite database and returns an object to represent it. You can learn more about raw strings by checking out this link. This lets Python know that we’re working with a raw string, meaning that the “/” won’t be used to escape characters. Note: Notice that we included the letter “r” before the string that contains this path. If the file already exists, the connect function will simply connect to that file. If you wanted to specify a specific directory, you could write: conn = nnect(r'PATH-TO-YOUR-DIRECTORY/orders.db') With this line of code, we’ve created a new connection object, as well as a new file called orders.db in the directory in which you’re working. We’ll represent the connection using a variable named conn. db file, as this is a very standard way of actually maintaining a SQLite database. ![]() This object is created using SQLite’s connect() function. In order to do this, we’ll create a Connection object that will represent the database. In this section of the Python SQLite tutorial, we’ll explore the different ways in which you can create a database in Python with SQLite. Let’s move into actually creating our database. We can do this by using the following command: import sqlite3 Let’s start off the tutorial by loading in the library. Unfortunately, when using SQLite, you’re restricted to these data types. – Includes a binary large object that is stored exactly as inputįrom this list, you may notice a number of missing data types such as dates. REAL – Includes a floating point (decimal) value.Let’s take a quick look at the data types that are available: However, as you’ll see, SQLite makes a lot of other things easier. SQLite for Python offers fewer data types than other SQL implementations. Data Types Available in SQLite for Python ![]()
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