Trac SQL Database API
You can find the specifics of the database API in the trac.db package. This package provides:
- Simple pooling of database connections
- Iterable cursors
- Selection of database modules based on connection URIs.
Accessing the Database
The Database API has evolved in the various versions of Trac, and its usage differs substantially across Trac 0.11, 0.12 and 1.x. The following subsections explain these differences chronologically.
API before Trac 0.12
This is how things used to be for Trac 0.5 - 0.11, and is still supported in Trac 0.12, but in new code this style should definitely not be used, as it introduces all the problems that the new styles are solving. See next sections for details.
Code accessing the database in Trac go through this layer simply by using the
get_db_cnx() to get a pooled database connection. A database cursor can be obtained from the pooled database connection, and the code uses the cursor in conjunction with SQL statements to implement the behavior:
from trac.env import Environment def myFunc(): env = Environment('/path/to/projenv') db = env.get_db_cnx() cursor = db.cursor() # Execute some SQL statements db.commit()
Note that you should always make sure that
db won't get garbage collected while
cursor is still used, as the collection will do a rollback and close the cursors.
Avoid in particular doing
cursor = env.get_db_cnx().cursor(), see r8878.
Trac 0.12 API
The 0.12 style can still be used in 1.0, but for new code we encourage you to focus on the Trac version 1.0 and to adopt the even simpler 1.0 style. See next sections for details.
As support for Python 2.3 has been dropped, we could make use of decorators to get rid of some of the boilerplate code:
from trac.env import Environment from trac.db import with_transaction def myFunc(): env = Environment('/path/to/projenv') @with_transaction(env) def do_something(db): cursor = db.cursor() # Execute some SQL statements
This is slightly simpler and more robust than the previous API, as not only the
commit() is performed in any successful case (i.e. the
Execute some SQL statements code can
return at any place), but a
rollback will be performed should an exception be triggered in that block.
See more details in the ApiChanges/0.12 paragraph.
The use of
env.get_db_cnx() is still possible, but deprecated.
env.get_read_db() method can be used to get a "read" only access to the database (for performing
With the API described above (since 0.12) it is possible to have nested transactions. A nested transaction is best explained by an example:
from trac.env import Environment from trac.db import with_transaction def myFunc1(): env = Environment('/path/to/projenv') @with_transaction(env) def do_outer_transaction(db): cursor = db.cursor() # Execute some SQL statements myFunc2(env) # do nested transaction # <=== commit or rollback def myFunc2(env): @with_transaction(env) def do_nested_transaction(db): cursor = db.cursor() # Execute some SQL statements
In this example, when
myFunc1() is called, it first executes the outer transaction (
do_outer_transaction()) and then executes a nested transaction (
myFunc2()) from within the outer transaction. The key observation is that nested transactions are atomic.
This means that either the whole (outer) transaction is either committed or aborted. So even if the nested transaction succeeded but the outer transaction fails (an exception is raised at the line with the "commit or rollback" comment), the whole transaction will be rolled back, ie including the changes made by the nested transaction.
- Do not call
commit()yourself in a transaction, even though this is still possible in the API for backward compatibility reasons. Not only is a commit performed automatically at the proper time (as explained above), but if you call it yourself, you risk to commit from within a nested transaction, possibly leading to an inconsistent state of the database.
env.get_read_db()within a transaction reuses the same connection as used for the connection. So uncommitted changes made by the transaction will already be visible to the caller of
get_read_db()(but not outside of the transaction - that is in another thread).
- Uncommited changes of a transaction are only visible to nested transactions in the same thread. Different threads use different database connections and therefore different transactions. To be more precise, the exact detail of what is visible to other threads is database specific and depends to the isolation level used.
Trac 1.0 API
This style is supported for version 1.0.x, 1.1.x and will be supported beyond as well.
As we dropped support for Python 2.4, we could simplify the code a bit more by using the
with keyword and context managers:
from trac.env import Environment def myFunc(): env = Environment('/path/to/projenv') with env.db_transaction as db: cursor = db.cursor() # Execute some SQL statements
It does essentially the same thing as the 0.12 version above in a terser way. Nested transactions work the way you would expect: only the outermost one will actually do the
commit(), upon normal exit. So, again, don't call
commit() by yourself.
The use of
env.get_db_cnx() is now deprecated.
Symmetrically, a second context manager is provided for performing read-only accesses:
from trac.env import Environment def myFunc(): env = Environment('/path/to/projenv') with env.db_query as db: cursor = db.cursor() cursor.execute(""" SELECT a, b, c FROM ... """, (param1, param2)) # Execute some SQL "SELECT" statements # (continue)
This one enforces the notion of read-access, because the
db connection bound to the context doesn't support the
rollback() methods. As there's no
commit() upon exit, one could question the usefulness of this syntactic construct. The main interest is in better locality of the connection: to improve concurrency, the lifetime of a connection wrapper has to be as short as possible (see #3446). Therefore, we close the connection on exit, making it available to other threads. So even if Python gives you access to the
db variable after the
with block (at the
# (continue) line in the above example), you should not (and can't) use it at that point.
Actually, if you don't need to do anything fancy with the cursor like calling
db.get_last_id(cursor, ...), then you can use a shorter form:
from trac.env import Environment def myFunc(): env = Environment('/path/to/projenv') with env.db_query as db: for a, b, c in db(""" SELECT a, b, c FROM ... """, (param1, param2)): # do something with a, b, c
All the results are returned at once in a list, by calling
fetchall() on the underlying cursor. This is fine most of the time, if you need to limit the number of returned results, you can still use "LIMIT" or "OFFSET" in the SQL query.
In the same spirit, if you don't even need to use
db itself for things like
db.like(), you can simply do:
from trac.env import Environment def myFunc(): env = Environment('/path/to/projenv') for a, b, c in env.db_query(""" SELECT a, b, c FROM ... """, (param1, param2)): # do something with a, b, c
These short forms also present an additional safety measure as they're only allowing a "SELECT" query to be executed by a read-only connection. Indeed, the same short forms are possible on both
To determine which database has to be used, Trac looks at the value of the
database configuration option in trac.ini, which should contain a database connection URI. The default value for this option tells Trac to use an SQLite database inside the environment directory:
[trac] database = sqlite:db/trac.db
The connection URI syntax has been designed to be compatible with that provided by SQLObject. See also the section on SQLObject connections. The only supported URI schemes at this point are
Prior to version 1.0, Trac used to operate the following way:
get_db_cnx()returns a connection from the pool of connections. This connection needs to be returned, and Trac is written so that the return will happen automatically by the garbage collector if the code is written to follow a simple rule. When the garbage collector determines the pooled database connection is no longer being used, its
__del__method will return the pooled connection to the pool for reuse. If you have set a lexical variable in the function's body to the pooled connection, this typically occurs when the function is returning. In the example above of
myFuncit occurs at the return statement since
dbis a variable local to
With the context managers introduced in Trac 1.0, we're able to return this Connection to the pool in a much more robust and direct way:
When the control flow exits a context manager (either
Environment.db_transaction), and if that context manager is the "outermost" one in case multiple contexts where nested, then the
Connectionis immediately returned to the pool, regardless of the behavior of the garbage collector.
This means that even if a variable still contains a reference to the
Connection, it won't be possible to use it outside of the context:
>>> from trac.env import open_environment >>> env = open_environment('...-trac') >>> with env.db_query as db: ... print db("SELECT count(*) FROM wiki") ... [(563,)] >>> db <trac.db.util.ConnectionWrapper object at 0x026146E8> >>> print db("SELECT count(*) FROM wiki") Traceback (most recent call last): File "<stdin>", line 1, in <module> File "trac\db\util.py", line 123, in __call__ cursor = self.cnx.cursor() File "trac\db\util.py", line 108, in __getattr__ return getattr(self.cnx, name) AttributeError: 'NoneType' object has no attribute 'cursor'
… which is a good thing!
Rules for DB API Usage
Different DB API modules have different ways to pass parameters to the cursors'
execute method, and different ways to access query results. To keep the database API as thin as possible, Trac uses a relatively common subset in all database code.
Always use the "format" parameter style, and always with
%s, because that's the only type that pyPgSQL supports. Statement parameters always need to be passed into execute as an actual sequence (list or tuple).
So the following statements are okay:
cursor.execute("SELECT author, ipnr, comment FROM wiki WHERE name = %s", [thename]) cursor.execute("SELECT id FROM ticket WHERE time >= %s AND time <= %s", (start, stop))
The following uses are not okay:
cursor.execute("SELECT author, ipnr, comment FROM wiki WHERE name = ?", thename) cursor.execute("SELECT id FROM ticket WHERE time >= %i AND time <= %i", start, stop)
At any cost, avoid string formatting to get values into the SQL statement. The database automatically escapes values you pass using
execute() arguments, but the same is not true if you use string formatting, opening your code up to SQL injection attacks.
On the other hand, you must use string formatting to dynamically specify names of tables or columns, ie anything that is not a value as such:
cursor.execute("SELECT time FROM %s WHERE name = %%s" % db.quote(table), (thename,))
For convenience, cursors returned by the database connection object are iterable after having executed an SQL query. Individual fields in result rows may only be accessed using integer indices:
cursor.execute("SELECT author, ipnr, comment FROM wiki WHERE name = %s", (thename,)) for row in cursor: print 'Author: %s (%s)' % (row, row) print row
Accessing fields using the column names is not supported by all database modules, so it should not be used. Automatically unpacking rows into tuples of named variables often provides better readability:
cursor.execute("SELECT author, ipnr, comment FROM wiki WHERE name = %s", (thename,)) for author, ipnr, comment in cursor: print 'Author: %s (%s)' % (author, ipnr) print comment
Guidelines for SQL Statements
As you may know, support for the SQL syntax varies among database systems. Trac adheres to a common subset that is supported by the majority of databases:
- no native
timedatabase types; store date and time information in seconds as
intfields (before 0.12) or better, in microseconds and
int64fields (since 0.12, mapped by each
trac.db.IDatabaseConnectorto a suitable database specific type)
- no triggers
- you may use views if you feel you need them, but this not used within Trac core
For anything not portable (and you really fall quickly in there), you need to use some methods from the connection when building your SQL query, such as
db.get_last_id(cursor, table, col).
cursor.execute(""" SELECT DISTINCT rev FROM node_change WHERE repos = %%s AND rev >= %%s AND rev <= %%s AND (path = %%s OR path %s)""" % db.like(), (self.id, sfirst, slast, path, db.like_escape(path + '/') + '%'))
As you can see, the legibility of long SQL statements can be improved by using Python's multiline string syntax.