This means that if pool_size=10 but our server never receives more than 5 concurrent requests, then the actual pool size will only grow to 5. The pool grows up to the minimum between the value of pool_size and the max number of concurrent requests. When web2py starts, the pool is always empty. If there are no available connections in the pool, a new connection is established. When the next http request arrives, web2py tries to recycle a connection from the pool and use that for the new transaction. Once a connection is established and the page has been served and the transaction completed, the connection is not closed but goes into a pool. This can be done withĪ common argument of the DAL constructor is the pool_size it defaults to zero.Īs it is rather slow to establish a new database connection for each request, web2py implements a mechanism for connection pooling. Some times you may need to generate SQL as if you had a connection but without actually connecting to the database. In this case DAL will not connect to any back-end database, but the API can still be accessed for testing. It is also possible to set the connection string to None. This is completely automatic and done at the datastore level, not at the web2py level. NDB uses a Memcache buffer to read data that is accessed often. In the Google/NoSQL case the +ndb option turns on NDB. In the MySQL connection string, the ?set_encoding=utf8mb4 at the end sets the encoding to UTF-8 and avoids an Invalid utf8 character string: error on Unicode characters that consist of four bytes, as by default, MySQL can only handle Unicode characters that consist of one to three bytes. Once the connection is established, web2py will create, alter, and drop tables appropriately. In the case of MySQL, PostgreSQL, MSSQL, FireBird, Oracle, DB2, Ingres and Informix the database "test" must be created outside web2py. This file is locked every time it is accessed. Here are examples of connection strings for specific types of supported back-end databases (in all cases, we assume the database is running from localhost on its default port and is named "test"): ndb that in SQLite the database consists of a single file. The connection string is the only web2py code that depends on a specific back-end database. The constructor of DAL requires a single argument, the connection string. You are free to give it a different name. To use any other database back-end, run from the source distribution and install the appropriate driver for the required back end.ĭb = DAL ( 'sqlite://storage.sqlite', pool_size = 0 )ĭb is not a keyword it is a local variable that stores the connection object DAL. The Mac binary distribution works out of the box with SQLite. The Windows binary distribution works out of the box with SQLite, MSSQL, PostgreSQL and MySQL. The Gotchas section at the end of this chapter has some more information about specific databases. Google NoSQL is treated as a particular case in Chapter 13. Please check on the web2py web site and mailing list for more recent adapters. A partial list of supported databases is show in the table below. The DAL dynamically generates the SQL in real time using the specified dialect for the database back end, so that you do not have to write SQL code or learn different SQL dialects (the term SQL is used generically), and the application will be portable among different types of databases. Web2py comes with a Database Abstraction Layer (DAL), an API that maps Python objects into database objects such as queries, tables, and records.
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