Get Essential SQL AIchemy PDF

By Rick Copeland

ISBN-10: 0596516142

ISBN-13: 9780596516147


"'Essential SQLAlchemy' richtet sich an Python-Entwickler, die eine SQL-Schnittstelle sowie einen item Relational Mapper nutzen wollen - die SQLAlchemy-Bibliothek [...]" - iX, August 2009 "SQLAlchemy ist in Python-Kreisen verbreitet und erfreut sich mittlerweile großer Beliebtheit - leider fehlte bisher aber eine umfassende Dokumentation, die die Möglichkeiten von SQLAlchemy angemessen darstellt. Das vorliegende Buch aus dem O'Reilly Verlag schafft hier Abhilfe, erläutert den Umgang und die Handhabung auf nachvollziehbare Weise und liefert diesbezüglich jede Menge nützlicher Beispiele sowie viel fabric für die sofortige Verwendung." - entwickler-magazin, Februar 2009


Essential SQLAlchemy introduces a high-level open-source code library that makes it more straightforward for Python programmers to entry relational databases comparable to Oracle, DB2, MySQL, PostgreSQL, and SQLite. SQLAlchemy has develop into more and more renowned on the grounds that its liberate, however it nonetheless lacks strong offline documentation. This sensible publication fills the space, and since a developer wrote it, you get an aim examine SQLAlchemy's instruments instead of an advocate's description of all of the "cool" gains. SQLAlchemy contains either a database server-independent SQL expression language and an object-relational mapper (ORM) that permits you to map "plain previous Python gadgets" (POPOs) to database tables with out considerably altering your present Python code. crucial SQLAlchemy demonstrates find out how to use the library to create an easy database program, walks you thru easy queries, and explains how one can use SQLAlchemy to hook up with a number of databases at the same time with an analogous Metadata. you furthermore mght the best way to: * Create customized varieties for use on your schema, and while it really is beneficial to exploit customized instead of integrated kinds * Run queries, updates, and deletes with SQLAlchemy's SQL expression language * construct an item mapper with SQLAlchemy, and comprehend the variations among this and lively checklist styles utilized in different ORMs * Create gadgets, store them to a consultation, and flush them to the database * Use SQLAlchemy to version item orientated inheritance * offer a declarative, energetic list trend to be used with SQLAlchemy utilizing the Elixir extension * Use the SQLSoup extension to supply an automated metadata and item version in response to database mirrored image additionally, you are going to find out how and while to take advantage of different extensions to SQLAlchemy, together with AssociationProxy, OrderingList, and extra. crucial SQLAlchemy is the much-needed consultant for each Python developer utilizing this code library. rather than a feature-by-feature documentation, this publication takes an "essentials" strategy that provides you precisely what you want to turn into efficient with SQLAlchemy at once.

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D0 ... d0 ... COMMIT Foreign keys Foreign keys are references from a row in one table to a row in another table. The usual way to specify simple (non-complex) foreign keys is by passing a ForeignKey object to the Column constructor. columnname, that specifies the referenced column. constraint The owning ForeignKeyConstraint, if any. If left unspecified, a new ForeignKeyCon straint will be created and added to the parent table. The default is None. use_alter Use an ALTER TABLE command to create the constraint (passed along to the owning ForeignKeyConstraint).

Orm -- control logging of ORM functions. INFO logs configurations and unit of work dumps. attributes -- Logs instrumented attribute operations. mapper -- Logs mapper configurations and operations. unitofwork -- Logs unit of work operations, including dependency graphs. strategies -- Logs relation loader operations (lazy and eager loads). sync -- Logs synchronization of attributes from one object to another during a flush. execute('select user_name, email_address from ... Connection class, which serves as a proxy for the particular DB-API connection object.

Brand_table = Table('brand', metadata, Column('name', Unicode(255)), # override the reflected type autoload=True) If you want to reflect the entire database schema, you may do so by specifying reflect=True in the metadata constructor. Of course, in this case, the MetaData must 42 | Chapter 3: Engines and MetaData be created as a bound MetaData. tables['brand'] You can also use the reflect( ) method of the MetaData to load the schema. reflect( bind=None, schema=None, only=None) takes the following arguments: bind A Connectable used to access the database; required only when the MetaData is unbound.

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Essential SQL AIchemy by Rick Copeland

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