The complete code of this example app.py is the following. result_set = result_proxy.fetchall()Īnd now, print the result_set. To fetch the data from the object, use the fetchall() method. Now, we use the result_proxy object to retrieve the data. It returns the object that proxies cursor object from the Python Database API. To execute the query, use execute() function. So first, we need to save the select query into the query variable. We prepared a query, but this does not do anything. The SQLAlchemy Core query looks like this. In regular SQL, to select all the records, it is “SELECT * FROM shows”. With our table loaded, let’s prepare a query to select all the records from the shows table. shows = db.Table('Shows', metadata, autoload=True, autoload_with=engine) Step 6: Prepare the Query The Table() function takes Shows table, Metadata, autoload=True, and autoload_with=engine. To load the SQL table, use the db.Table() function. metadata = db.MetaData() Step 5: Load the shows table This metadata will hold all the information about our table. We can retrieve the metadata about our database with DB.metadata. connection = nnect() Step 4: Retrieve the Metadata The next step is to use the connect() function to connect with the database.
engine = db.create_engine('sqlite:///shows.db')Īs we have discussed earlier, our database name is shows.db.įrom the engine, we can create a connection and run the database queries. The engine allows us to create multiple database connections, and it manages those connections. To connect with the database, use the create_engine() function. We will fetch those records using SQLAlchemy. Now in that database, I have created a table called shows with some records. Now, I have already created a Database called shows.db in my project folder but if you don’t know how to create it, then check out how to create an SQLite database in Python. As you can see that we imported sqlalchemy as db.
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