= Trac SQL Database API =

Trac uses a very thin layer on top of the standard [http://www.python.org/peps/pep-0249.html Python Database API 2.0] for interfacing with supported relational database systems such as [http://sqlite.org/ SQLite] or [http://www.postgresql.org/ PostgreSQL].

 ''Note that Trac prior to version 0.9 used the PySQLite APIs directly, and has no support for other database systems. This document describes the thin DB API abstraction layer introduced in version 0.9.''

You can find the specifics of the database API in the [source:/trunk/trac/db/ trac.db] package. This package provides:
 * Simple pooling of database connections
 * Iterable cursors
 * Selection of DB modules based of connection URIs.

== Accessing the Database ==
=== API before Trac 0.12

Code accessing the database in Trac go through this layer simply by using the {{{Environment}}} method {{{get_db_cnx()}}} in order 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.  

{{{
#!python
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

As we dropped support for Python 2.3, we could make use of decorators to get rid of some of the boilerplate code.

{{{
#!python
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#with_transaction] paragraph.

The use of `env.get_db_cnx()` is still possible, but **deprecated**.
An alternative `env.get_read_db()` method can be used to get a "read" only access to the database (for performing `SELECT` queries).

==== Nested Transactions ====
With the API described above (since ''0.12'') it's possible to have nested transactions. A nested transaction is best explained by an example. Consider the following code:

{{{
#!python
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 important thing to notice is:

  '''Nested transactions are atomic! '''

This means that either the ''whole'' (outer) transaction is 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 (i.e. including the changes made by the nested transaction).

''Note:'' Using `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).

''Note:'' 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.

=== Trac 0.13dev and 1.0 API #Trac0.13API 

As we dropped support for Python 2.4, we could simplify the code a bit more by using the `with` keyword and context managers:

{{{
#!python
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.

**The use of `env.get_db_cnx()` is now strongly discouraged.**

Symmetrically, a second context manager is provided for performing read-only accesses:

{{{
#!python
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 `commit()` or `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: in order 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:
{{{
#!python
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.cast()` or `db.like()`, you can simply do:

{{{
#!python
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 `env.db_transaction` and `env.db_query`).

=== Configuration
The {{{get_db_cnx}}} method looks at the value of the {{{database}}} configuration option in [wiki:TracIni 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 [http://sqlobject.org/SQLObject.html#declaring-the-class SQLObject] (see also the section on SQLObject [http://sqlobject.org/SQLObject.html#declaring-a-connection connections]). The only supported URI schemes at this point are `sqlite`, `postgres` and `mysql`.''

=== Pooled Connections ===

Trac used to operate the following way:
 The {{{Environment}}} method {{{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 {{{myFunc}}} it occurs at the return statement since {{{db}}} is a variable local to {{{myFunc}}}

With the context managers introduced in Trac 0.13, 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_query` or `Environment.db_transaction`), and if that context manager is the "outermost" one in case multiple contexts where nested, then the `Connection` is 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:
{{{#!pycon
>>> 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, the Trac team has decided to use a relatively common subset in all database code.

=== Parameter passing ===

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:
{{{
#!python
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:
{{{
#!python
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, try avoiding the use of [http://docs.python.org/library/stdtypes.html#string-formatting string formatting] to get values into the SQL statement. The database automatically escapes values you pass using {{{execute()}}} arguments, the same is not true if you use string formatting, opening your code up to [http://en.wikipedia.org/wiki/SQL_injection SQL injection] attacks.

On the other hand, you '''must''' use string formatting to dynamically specify names of tables or columns, i.e. anything that is not a value as such:

{{{
#!python
cursor.execute("SELECT time FROM %s WHERE name=%%s" % table, (thename,))

}}}

=== Retrieving results ===

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:
{{{
#!python
cursor.execute("SELECT author,ipnr,comment FROM wiki WHERE name=%s", (thename,))
for row in cursor:
    print 'Author: %s (%s)' % (row[0], row[1])
    print row[2]
}}}

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:
{{{
#!python
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 SQL varies among different database systems. The requirements of Trac are relatively trivial, so we try to stick to a common subset that is supported by the majority of databases.

 - no native `date` or `time` database types; store date and time information in seconds as `int` fields (before 0.12) or better, in microseconds and `bigint` fields (since 0.12)
 - no triggers 
 - you may use views if you feel you need them (but so far we didn't feel the need for Trac itself)

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 (e.g. `db.cast(column, type)`, `db.concat(*params)`, `db.like()`, `db.like_escape()`, `db.quote(param)`, `db.get_last_id(cursor, table, col)`).

For example: 
{{{#!python
            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 + '/') + '%'))
}}}
 ([source:tags/trac-0.12/trac/versioncontrol/cache.py@:324-328#L304 cache.py])

As you can see, the readability of long SQL statements can improved by using Python's multiline string syntax.

----
See also: TracDev, TracDev/DatabaseSchema, TracDev/DatabaseUpgrades, TracDev/CodingStyle