onlyphantom / sqlalchemy-tutorial

Ground Up tutorial to SQLAlchemy

Ground Up tutorial to SQLAlchemy

Project Description

A ground-up introduction to SQLAlchemy, which will cover everything from Engine, to Pools and its ORM implementation through Session.

Update on an almost-daily basis since 12 May 2019.

Preview (Sample Chapter)

The Engine is the starting point for any SQLAlchemy application. The official documentation calls it the home base for the actual database and its DBAPI, and a Dialect which describes how to talk to a specific kind of database/DBAPI combination. The code below creates an engine, which rereferences a Dialect object tailored for SQLite and a Pool object which will establish a DBAPI connection when a connection request is first received.

from sqlalchemy import create_engine
engine = create_engine('sqlite:///:memory:', echo=True)
print(engine)

Engine(sqlite:///:memory:)

Notice that the Engine and its underlying Pool doesn't establish the first actual DBAPI until the Engine.connect() method is called, or until an operation dependent on this method (such as Engine.execute()) is invoked. In this way, Engine and Poolis said to have a lazy initialization behavior.

The typical usage of create_engine() is once per particular database URL, held globally for the lifetime of a single application process... it is most efficient when created just once at the module level of an application, not per-object or per-function call.

The Engine can be used in one of two ways:

• Interact with the db directly by through SQL commands
• Passed to a Session object to work with the ORM

Working with Engines directly

A common use-case is to procure a connection resource via the Engine.connect() method:

from sqlalchemy import create_engine
connection = create_engine('sqlite:///../data/rcsample.db').connect()
result = connection.execute("select * from response order by workshop_id desc limit 10")
print([row['comments'] for row in result])
print([col for col in result.keys()])

['', '', '', '', '', '', '', '', 'yang robustness kok belum ya bang', 'Thank you,  you can teach and explain all the statistics "things" very clearly and make it fun. ']
['id', 'workshop_id', 'difficulty', 'assistants_score', 'knowledge', 'objectives', 'timeliness', 'venue_score', 'satisfaction_score', 'comments']

The connection we created above is an instance of Connection, which is a proxy object for an actual DBAPI connection.

Queue Pool

Whenever the connect() or execute() methods are called, the Engine will ask the connection pool for a connection. The default connection pool, QueuePool will open connections to the database on an as-needed basis; As concurrent statements are executed, QueuePool will grow its pool of connections to a defaulot size of five, and allow a default "overflow" of ten.

Tip: QueuePool is not used by default for SQLite engines

We can overwrite the above using the Engine Creation API.

engine = create_engine(
    "mysql://scott:tiger@hostname/dbname",
    case_sensitive=True,
    encoding='latin1', 
    pool_size=5,
    max_overflow=10)

The several parameters in our engine creation call above:

• case_sensitive=True: if False, result columns names will match in a case-insensitive fashion
• encoding: defaults to utf-8; The string encoding used by SQLAlchemy for string encode/decode operations which occur within SQLAlchemy, outside of the DBAPI
• pool_size: number of connections to keep open. To disable pooling, set poolclass to NullPool, a pool_size setting of 0 indicates no limit
• max_overflow: number of connections to allow in connection pool "overflow", that is connections that can be opened above and beyond the pool_size setting

Using the Engine to execute our database commands:

from sqlalchemy import create_engine
engine = create_engine('sqlite:///:memory:')
engine.execute('CREATE TABLE "salesperson" ('
               'id INTEGER NOT NULL,'
               'name VARCHAR,'
               'PRIMARY KEY (id));')
# print list of tables name
print(engine.table_names())

['salesperson']