<%flags>inherit='document_base.myt'</%flags>
+<%attr>title='Advanced Data Mapping'</%attr>
<&|doclib.myt:item, name="adv_datamapping", description="Advanced Data Mapping" &>
<p>This section is under construction. For now, it has just the basic recipe for each concept without much else. </p>
+++ /dev/null
-<%flags>inherit='document_base.myt'</%flags>
-
-
-
-<&|doclib.myt:item, name="coolthings", description="Cool Things You Can Do With SQLAlchemy" &>
-
-<&|formatting.myt:code, syntaxtype="python" &>
- # first, some imports
- from sqlalchemy.sql import *
- from sqlalchemy.schema import *
-
-
- # make a database engine based on sqlite
- import sqlalchemy.databases.sqlite as sqlite_db
- db = sqlite_db.engine('foo.db', pool_size = 10, max_overflow = 5)
-
- # define metadata for a table
-
- users = Table('users', db,
- Column('user_id', INT),
- Column('user_name', VARCHAR(20)),
- Column('password', CHAR(10))
- )
-
-
- # select rows from the table
-
- query = users.select()
- cursor = query.execute()
- rows = cursor.fetchall()
-
-
- # select rows from the table where user_name=='ed'
- rows = users.select(users.c.user_name == 'ed').execute().fetchall()
-
- # make a query with a bind param
- query = select([users], users.c.user_id == bindparam('userid'))
-
- # execute with params
- rows = query.execute(userid = 7).fetchall()
-
-
- # make another table
- addresses = Table('addresses', db,
- Column('address_id', INT),
- Column('user_id', INT),
- Column('street', VARCHAR(20)),
- Column('city', VARCHAR(20)),
- Column('state', CHAR(2)),
- Column('zip', CHAR(5))
- )
-
- # no, really, make this table in the DB via CREATE
- addresses.build()
-
-
- # make a nonsensical query that selects from an outer join, and
- # throws in a literally-defined EXISTS clause
- query = select(
- [users, addresses],
- and_(
- addresses.c.street == 'Green Street',
- addresses.c.city == 'New York',
- users.c.user_id != 12,
- "EXISTS (select 1 from special_table where user_id=users.user_id)"
- ),
- from_obj = [ outerjoin(users, addresses, addresses.user_id==users.user_id) ]
- )
-
-
- # insert into a table
- users.insert().execute(user_id = 7, user_name = 'jack')
-
- # update the table
- users.update(users.c.user_id == 7).execute(user_name = 'fred')
-
-
- # get DBAPI connections from the higher-level engine
- c = db.connection()
-
-
- # use the connection pooling directly:
-
- # import a real DBAPI database
- from pysqlite2 import dbapi2 as sqlite
-
- # make an implicit pool around it
- import sqlalchemy.pool as pool
- sqlite = pool.manage(sqlite, pool_size = 10, max_overflow = 5, use_threadlocal = True)
-
- # get a pooled connection local to the current thread
- c = sqlite.connect('foo.db')
- cursor = c.cursor()
-
- # return the connection to the pool
- cursor = None
- c = None
-
-</&>
-
-</&>
<%flags>inherit='document_base.myt'</%flags>
+<%attr>title='Data Mapping'</%attr>
+
<&|doclib.myt:item, name="datamapping", description="Basic Data Mapping" &>
<p>Data mapping describes the process of defining <b>Mapper</b> objects, which associate table metadata with user-defined classes.
<%flags>inherit='document_base.myt'</%flags>
+<%attr>title='Database Engines'</%attr>
+
<&|doclib.myt:item, name="dbengine", description="Database Engines" &>
<p>A database engine is a subclass of <span class="codeline">sqlalchemy.engine.SQLEngine</span>, and is the starting point for where SQLAlchemy provides a layer of abstraction on top of the various DBAPI2 database modules. It serves as an abstract factory for database-specific implementation objects as well as a layer of abstraction over the most essential tasks of a database connection, including connecting, executing queries, returning result sets, and managing transactions.</p>
<%flags>inherit='document_base.myt'</%flags>
+<%attr>title='Modules and Classes'</%attr>
<&|doclib.myt:item, name="docstrings", description="Modules and Classes" &>
<%init>
import sqlalchemy.schema as schema
version = '0.91'
</%attr>
+<%method title>
+% try:
+# avoid inheritance via attr instead of attributes
+ <% m.base_component.attr['title'] %> - SQLAlchemy Documentation
+% except KeyError:
+ SQLAlchemy Documentation
+%
+</%method>
<%flags>inherit='document_base.myt'</%flags>
+<%attr>title='Database Meta Data'</%attr>
<&|doclib.myt:item, name="metadata", description="Database Meta Data" &>
<&|doclib.myt:item, name="tables", description="Describing Tables with MetaData" &>
<p>The core of SQLAlchemy's query and object mapping operations is table metadata, which are Python objects that describe tables. Metadata objects can be created by explicitly naming the table and all its properties, using the Table, Column, ForeignKey, and Sequence objects imported from <span class="codeline">sqlalchemy.schema</span>, and a database engine constructed as described in the previous section, or they can be automatically pulled from an existing database schema. First, the explicit version: </p>
<%flags>inherit='document_base.myt'</%flags>
+<%attr>title='Connection Pooling'</%attr>
<&|doclib.myt:item, name="pooling", description="Connection Pooling" &>
<P><b>Note:</b>This section describes the connection pool module of SQLAlchemy, which is the smallest component of the library that can be used on its own. If you are interested in using SQLAlchemy for query construction or Object Relational Mapping, this module is automatically managed behind the scenes; you can skip ahead to <&formatting.myt:link,path="dbengine"&> in that case.</p>
<p>At the base of any database helper library is a system of efficiently acquiring connections to the database. Since the establishment of a database connection is typically a somewhat expensive operation, an application needs a way to get at database connections repeatedly without incurring the full overhead each time. Particularly for server-side web applications, a connection pool is the standard way to maintain a "pool" of database connections which are used over and over again among many requests. Connection pools typically are configured to maintain a certain "size", which represents how many connections can be used simultaneously without resorting to creating more newly-established connections.
<%flags>inherit='document_base.myt'</%flags>
+<%attr>title='Roadmap'</%attr>
<&|doclib.myt:item, name="roadmap", description="Roadmap" &>
<p>SQLAlchemy includes several components, each of which are useful by themselves to give varying levels of assistance to a database-enabled application. Below is a roadmap of the "knowledge dependencies" between these components indicating the order in which concepts may be learned.
</p>
<%flags>inherit='document_base.myt'</%flags>
+<%attr>title='Constructing SQL Queries via Python Expressions'</%attr>
+
<&|doclib.myt:item, name="sql", description="Constructing SQL Queries via Python Expressions" &>
<p><b>Note:</b> This section describes how to use SQLAlchemy to construct SQL queries and receive result sets. It does <b>not</b> cover the object relational mapping capabilities of SQLAlchemy; that is covered later on in <&formatting.myt:link, path="datamapping"&>. However, both areas of functionality work similarly in how selection criterion is constructed, so if you are interested just in ORM, you should probably skim through basic <&formatting.myt:link, path="sql_select_whereclause"&> construction before moving on.</p>
<p>Once you have used the <span class="codeline">sqlalchemy.schema</span> module to construct your tables and/or reflect them from the database, performing SQL queries using those table meta data objects is done via the <span class="codeline">sqlalchemy.sql</span> package. This package defines a large set of classes, each of which represents a particular kind of lexical construct within a SQL query; all are descendants of the common base class <span class="codeline">sqlalchemy.sql.ClauseElement</span>. A full query is represented via a structure of ClauseElements. A set of reasonably intuitive creation functions is provided by the <span class="codeline">sqlalchemy.sql</span> package to create these structures; these functions are described in the rest of this section. </p>
<%flags>inherit='document_base.myt'</%flags>
+<%attr>title='The Types System'</%attr>
+
<&|doclib.myt:item, name="types", description="The Types System" &>
<p>The package <span class="codeline">sqlalchemy.types</span> defines the datatype identifiers which may be used when defining <&formatting.myt:link, path="metadata", text="table metadata"&>. This package includes a set of generic types, a set of SQL-specific subclasses of those types, and a small extension system used by specific database connectors to adapt these generic types into database-specific type objects.
</p>
<%flags>inherit='document_base.myt'</%flags>
+<%attr>title='Unit of Work'</%attr>
+
<&|doclib.myt:item, name="unitofwork", description="Unit of Work" &>
<&|doclib.myt:item, name="overview", description="Overview" &>
</&>
projects / thirdparty / sqlalchemy / sqlalchemy.git / commitdiff
