Storm Manual
This is the detailed documentation for Storm. For a more hands-on approach, check out the [:Tutorial: Tutorial].
Databases
The create_database() function
The create_database() function has the following prototype:
database = create_database(uri)
The uri parameter may be either a URI string or a URI object. The following URIs are examples of acceptable syntax:
backend:database_name
backend://hostname/database_name
backend://hostname:port/database_name
backend://username:password@hostname/database_name
backend://hostname/database_name?option=value
backend://username@/database_name
MySQL
URIs
Dependencies
MySQL support depends on the [http://mysql-python.sf.net/ MySQLdb] module for Python.
PostgreSQL
URIs
Dependencies
PostgreSQL support depends on the [http://www.initd.org/tracker/psycopg/wiki/PsycopgTwo psycopg2] module for Python.
SQLite
Dependencies
SQLite support depends on the [http://www.initd.org/tracker/pysqlite/wiki/pysqlite pysqlite2] module for Python.
The Store interface
The ResultSet interface
Properties
What is a property in Storm
Common constructor parameters
Most properties accept the following properties. All of them are optional.
name: The column name in the database. Setting it allows the class attribute name and the column name in the database schema to differ. If unset, the name will be considered the same for the column and the class attribute.
primary: If true, this property is considered to map the primary key of the database table. Compound keys should be defined using the class-level __storm_primary__ attribute instead (see the section about compound keys for more information).
default: The default value for the property.
default_factory: A factory which returns default values for the property. This should be used when the default value is mutable.
Defining compound keys
To define a compound key in Storm, use the __storm_primary__ class-level attribute. It should be set to a tuple with the names of the properties composing the primary key. For example:
Table of properties vs. python vs. database types
Property |
Python |
PostgreSQL |
MySQL |
SQLite |
Bool |
bool |
BOOL |
TINYINT(1) |
anything(*) |
Int |
int, long |
SERIAL, BIGSERIAL, SMALLINT, INT, BIGINT |
TINYINT, SMALLINT, MEDIUMINT, INT, BIGINT |
anything(*) |
Float |
float |
FLOAT, REAL, DOUBLE PRECISION |
FLOAT, REAL, DOUBLE PRECISION |
anything(*) |
Decimal |
Decimal |
DECIMAL, NUMERIC, MONEY |
DECIMAL, NUMERIC |
anything(*) |
Unicode |
unicode |
TEXT, VARCHAR, CHAR |
TEXT, VARCHAR, CHAR |
anything(*) |
str |
BYTEA |
BLOB, BINARY, VARBINARY |
anything(*) |
|
Pickle |
any |
BYTEA |
BLOB, BINARY, VARBINARY |
anything(*) |
DateTime |
datetime |
TIMESTAMP |
DATETIME, TIMESTAMP |
anything(*) |
Date |
date |
DATE |
DATE |
anything(*) |
Time |
time |
TIME |
TIME |
anything(*) |
TimeDelta |
timedelta |
INTERVAL |
? |
anything(*) |
List |
list |
ARRAY[] |
? |
anything(*) |
(*) SQLite won't enforce data types, so they just must be formatted properly.
References
One-to-one
Many-to-one
Many-to-many
Using on_remote
The Reference interface
The ReferenceSet interface
Expressions
Managing stores
Working with multiple threads
Store objects are not threadsafe. This means that each Store must be accessed from only a single thread at a time. In fact, some databases (eg, SQLite) will require that the Store is only accessed by the thread in which it was created, which means that you can't keep a global pool of Stores and pass them to threads as needed, or simply implement a mutex around a single Store.
Therefore, the best policy is usually to create a Store object for each thread which needs one. One convenient way to manage this is to implement a "threadsafe" Store manager, which creates a Store for each thread when that thread first requests one, and then keeps the Store cached in a thread-local dictionary. This approach is taken by ZStorm to provide Store objects to each thread.
Note that Database objects are able to be shared between threads, and accessed concurrently, so you only need to create one of these for each underlying database.
SQLite and threads
Stores using SQLite, in particular, can be difficult to work with in a multi-threaded environment. This is because SQLite has very limited support for concurrent connections. In particular, any call which attempts to modify the database can only succeed if there are no other connections open on the database. Roughly, this translates into Storm as a requirement that no other Store objects exist for that database. If a call which attempts to modify the database is made while there are other connections open, the call check that there are no other connections, and if there are it will wait for a little while for those connections to go away (and new connections will be prevented from being opened while this wait is in progress). However, if the other connections don't go away within the timeout, the call will raise an OperationalError, with the message "database is locked".
By default, SQLite will wait for the other connections to go away for 5 seconds. However, this timeout can be changed by specifying a timeout option in the URI when opening the database. For example, the following command opens a database with a timeout of 0.3 seconds:
1 >>> database = create_database("sqlite:foo?timeout=0.3")
In most cases, if you get an exception from a call to the Store, you will need to call rollback() before continuing with use of the Store. However, in the specific case of a call which returns an OperationalError with the message "database is locked", the Store is left in a well defined state, such that you can simply retry the commit() call (possibly after taking some action to get rid of the other open connections to the database).
Warning: There is one exception to this: SQLite versions 3.3.0 to 3.3.17 inclusive have a bug which means that, if you get an OperationalError("database is locked") from any call other than commit(), further operations on the Store can lead to database corruption - unless you first call rollback(). More details of this bug are available at http://www.sqlite.org/cvstrac/wiki?p=CorruptionFollowingBusyError
It is not always possible to avoid getting "database is locked" exceptions; for example, the lock may be held by another process that you have little control over. However, it is often possible to structure your application to avoid concurrent connections blocking each other. One simple strategy is to perform all your access to SQLite from a single thread, using a single Store: this will mean that you won't get any concurrency, but won't have to wait for locks either. You could manage such a setup by having a threadsafe queue object, which any thread can put data to be written to the database on, or requests for data to be read from the database, and a single worker thread will then read items from the queue, perform the necessary actions on the Store, and put results back on a queue.
A slightly less restrictive setup is to restrict _write_ access to the Store to a single thread, but allow any thread to open a Store for read-only operations. As long as the read-only operations don't last long (specifically, they don't last longer than the timeout on the writer's Store), this will execute without error - however, read operations may have to wait for a commit to finish, which in turn may be waiting for other read operations to complete, so there could be noticeable delays in accessing information.
A different approach is to allow any thread to perform read or write access to the store, but to require that a mutex is obtained before a thread performs any write access to the database, and to require that write accesses are completed in a short time (such that readers don't timeout). The mutex is necessary to avoid a "deadlock" situation, where two writers begin a modification simultaneously, and thus cannot complete until the other goes away. Such deadlocks will be resolved, eventually, by a timeout, but no database access will be possible until the timeout finishes - better to use a mutex to prevent this situation occurring.
Whichever strategy you use (other than the single-worker-thread strategy), it is always possible that a call will take longer than you expect (perhaps due to an unusual spike in the server's load), resulting in other threads raising an OperationalError("database is locked") exception, so your code needs to anticipate this possibility, and handle it appropriately.
Finally, if you have a multi-threaded situation which requires greater concurrency, your best approach may well be to use a different database which is designed for this kind of situation.
Using a global function
Using a base class
Creating a backend
Testing
It's easy to test that Storm features are working with new backends. There are base test classes in tests/store/database.py and tests/store/base.py which may be inherited by database-specific test cases. Look at other backends to get a feeling of how it works.
If these tests pass with a new backend, you may be pretty sure that Storm is working fine with the created backend.