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Introduction
Web2py has a Database Abstraction Layer (DAL), an API that converts Python objects into database objects, including queries, tables, and records. The DAL dynamically creates the SQL in real-time using the given dialect for the database back end, eliminating the need for you to write SQL code or understand several SQL dialects and making the application portable across various databases.
This article goes one step further into the various concepts of DAL as it explains the DAL signature and connection in Web2py in complete detail. Let’s have a look!
DAL signature
In the DAL signature and connection in Web2py, the DAL support numerous connections to the same database, separate databases, and even databases of various types.
By making a DAL object instance, a connection with the database is established in the DAL signature and connection in Web2py :
DAL object:
db = DAL('sqlite://storage.sqlite', pool_size=0)
The connection object DAL is stored in the local variable db, which is not a keyword. You are free to call it anything else. The connection string is the only argument needed by the DAL constructor. The connection string is the only part of the web2py code dependent on a particular backend database. Here are some samples of connection strings for several supported back-end databases; in each case, we'll assume the database is called "test" and operates from localhost on its default port.
Remember that the database in SQLite is contained in a single file. It is generated if it doesn't already exist. Every time someone accesses this file, it is locked. The database "test" needs to be created outside web2py for MySQL, PostgreSQL, MSSQL, FireBird, Oracle, DB2, Ingres, and Informix. Web2py will construct, modify, and drop the necessary tables after making the connection.
The +ndb parameter in the Google/NoSQL scenario activates NDB. NDB reads frequently accessed data from a Memcache buffer. In contrast to web2py, this is carried out entirely automatically at the datastore level.
The connection string can alternatively be set to None. In this situation, DAL won't connect to any backend databases; however, the API can still be used for testing.
You might occasionally need to create SQL as though you were connected to the database but without really doing so. This is achievable using:
db = DAL('...', do_connect=False)
In this scenario, you can call _select, _insert, _update, and _delete to produce SQL but not select, insert, update, and delete. Most of the time, even without the necessary database drivers, you can use do_connect=False.
Take note that in DAL signature and connection in Web2py, the character encoding used for databases is utf8. You must modify it using the optional argument db_codec if you work with existing databases that behave differently.
db = DAL('...', db_codec='latin1')
You'll receive tickets for UnicodeDecodeError if you don't.
Connection Pooling
The pool_size, which has a default value of 0, is a frequent parameter of the DAL constructor in the DAL signature, and connection in Web2py.
Web2py includes a way for connection pooling because it takes a while to create a new database connection for each request. A connection is not terminated once it has been established, the page has been served, and the transaction has been finished; instead, it is added to a pool. Web2py tries to recycle a connection from the pool and use that for the new transaction when the subsequent http request comes in. A new connection is made if there are no open connections in the pool.
The pool is always empty when web2py starts. The pool expands until it reaches the least value between pool_size and the maximum number of simultaneous requests.
The real pool size will only increase to 5 if pool_size=10, yet our server never receives more than 5 concurrent requests. Connection pooling is not used if pool_size=0.
Connections in the pools are shared sequentially among threads, meaning that more than one thread may use them simultaneously but not simultaneously. Every process has its pool in the DAL signature and connection in Web2py.
Both SQLite and Google App Engine ignore the pool_size argument. SQLite does not use connection pooling since it would not be beneficial.
Connection Failures
DAL signature and connection in Web2py waits one second and, by default, tries up to five more times before failing to connect to the database. When using connection pooling, the database end can cancel a pooled connection that has been open but isn't being utilized for a while. Web2py tries to re-establish these dropped connections thanks to the retry feature. The attempts parameter controls how many attempts are made.
Frequently Asked Questions
Describe DAL Python.
Database Abstraction Layer (DAL), a feature of web2py, is an API that converts Python objects into database objects, including queries, tables, and records.
How do I implement web2py?
Run web2py.exe from your extracted files to launch your Web2py web server. It will then indicate you to create an administrative password so you may access your applications later on. Your web2py applications will launch in the browser when you select Start Server.
Explain pyDAL.
An entirely Python database abstraction layer is called pyDAL. The pyDAL module dynamically creates the SQL for the database back end in the chosen dialect.
Does web2py support Python 3?
Web2py functions on Python 2.7, and Python 3, with CPython (the C implementation) and PyPy (Python written in Python).
Should I study web2py?
Web2py is primarily used as a teaching tool rather than for web development. It makes it simple for the developer to learn server-side web development due to its graphical interface and integrated online IDE.
Conclusion
In this blog, we have extensively discussed the DAL signature and connection in Web2py, the uri parameter which establishes a connection with the database, and the connection pooling in the DAL constructor.
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