In this article, we are going to see how to execute SQLAlchemy core expression using Python.
Creating table for demonstration:
Import necessary functions from the SQLAlchemy package. Establish connection with the PostgreSQL database using create_engine() function as shown below, create a table called books with columns book_id and book_price. Insert record into the tables using insert() and values() function as shown.
Python3
# import necessary packages import sqlalchemy from sqlalchemy import create_engine, MetaData, Table, Column, Numeric,insert, Integer, VARCHAR, update, text, delete from sqlalchemy.engine import result # establish connections engine = create_engine( # initialize the Metadata Object meta = MetaData(bind=engine) MetaData.reflect(meta) # create a table schema books = Table( 'books', meta, Column('book_id', Integer, primary_key=True), Column('book_price', Numeric), Column('genre', VARCHAR), Column('book_name', VARCHAR) ) meta.create_all(engine) # insert records into the table statement1 = books.insert().values(book_id=1, book_price=12.2, genre='fiction', book_name='Old age') statement2 = books.insert().values(book_id=2, book_price=13.2, genre='non-fiction', book_name='Saturn rings') statement3 = books.insert().values(book_id=3, book_price=121.6, genre='fiction', book_name='Supernova') statement4 = books.insert().values(book_id=4, book_price=100, genre='non-fiction', book_name='History of the world') statement5 = books.insert().values(book_id=5, book_price=1112.2, genre='fiction', book_name='Sun city') # execute the insert records statement engine.execute(statement1) engine.execute(statement2) engine.execute(statement3) engine.execute(statement4) engine.execute(statement5) |
Output:
Sample table
Query to execute expressions in SQLAlchemy Core
In this article, we can discuss how to use execute function to executeSQLAlchemy core expressions and conventional SQL queries.
Example 1:
SQLAlchemy provides a function called text(). We can write any conventional SQL query inside the text function enclosed by “”. Now, passing this SQL query to execute function will convert this query to SQLAlchemy compatible format and returns the result.
from sqlalchemy import text
text("YOUR SQL QUERY")
Pass the SQL query to the execute() function and get all the results using fetchall() function. Use a for loop to iterate through the results. The SQLAlchemy query shown in the below code selects all rows where the book price is greater than Rs. 100.
Python3
# write the SQL query inside the text() block sql = text('SELECT * from BOOKS WHERE BOOKS.book_price > 100') results = engine.execute(sql) # Fetch all the records result = engine.execute(sql).fetchall() # View the records for record in result: print("\n", record) |
Output:
The output of books query
Example 2:
The below query returns the book_price which is exactly equal divisible by 10
Python3
# write the SQL query inside the text() block sql = text("SELECT * from BOOKS WHERE BOOKS.book_price/10 =10") # Fetch all the records result = engine.execute(sql).fetchall() # View the records for record in result: print("\n", record) |
Output:
The Output of book_price which is exactly equal divisible by 10
Example 3:
The below SQL expression will insert additional records in the created table using SQLAlchemy core.
from sqlalchemy import insert insert(table_name).values(column_name="value")
Get the books table from the Metadata object initialized while connecting to the database. Pass the insert query to the execute() function and get all the results using fetchall() function. Use a for loop to iterate through the results.
The SQLAlchemy query shown in the below code inserts additional records in the created table using SQLAlchemy core. Then, we can write a conventional SQL query and use fetchall() to print the results to check whether the table is updated properly.
Python3
# Get the `books` table from the Metadata object BOOKS = meta.tables['books'] from sqlalchemy import insert # write the insert statement stmt1 = insert(BOOKS).values(book_id=6, book_price=400, genre="fiction", book_name="yoga is science") stmt2 = insert(BOOKS).values(book_id=7, book_price=800, genre="non-fiction", book_name="alchemy tutorials") # execute engine.execute(stmt1) engine.execute(stmt2) # write the SQL query to check # whether the records are inserted sql = text("SELECT * FROM BOOKS ") results = engine.execute(sql) # View the records for record in results: print("\n", record) |
Output:
The output of inserting additional records
Example 4:
Let us see another example related to updating query.
Tablename.update().where(Tablename.c.column_name == ‘value’).values(column_name = ‘value’)
Get the books table from the Metadata object initialized while connecting to the database. Pass the delete query to the execute() function and get all the results using fetchall() function. Use a for loop to iterate through the results.
The SQLAlchemy query shown in the below code updates the genre “non-fiction” as “sci-fi” this will effectively update multiple rows at one go. Then, we can write a conventional SQL query and use fetchall() to print the results to check whether the table is updated properly.
Python3
# Get the `books` table from the Metadata object BOOKS = meta.tables['books'] # update stmt = BOOKS.update().where(BOOKS.c.genre == 'non-fiction' ).values(genre='sci-fi') engine.execute(stmt) # write the SQL query inside the # text() block to fetch all records sql = text("SELECT * from BOOKS") # Fetch all the records result = engine.execute(sql).fetchall() # View the records for record in result: print("\n", record) |
Output:
The output of the update query
