Essential SQLAlchemy by Rick Copeland

By Rick Copeland

Essential SQLAlchemy introduces a high-level open-source code library that makes it more uncomplicated for Python programmers to entry relational databases akin to Oracle, DB2, MySQL, PostgreSQL, and SQLite. SQLAlchemy has develop into more and more renowned seeing that its free up, however it nonetheless lacks reliable offline documentation. This sensible booklet fills the space, and since a developer wrote it, you get an goal examine SQLAlchemy's instruments instead of an advocate's description of all of the "cool" features.

SQLAlchemy comprises either a database server-independent SQL expression language and an object-relational mapper (ORM) that allows you to map "plain outdated Python objects" (POPOs) to database tables with out considerably altering your latest Python code. Essential SQLAlchemy demonstrates tips on how to use the library to create an easy database program, walks you thru easy queries, and explains easy methods to use SQLAlchemy to hook up with a number of databases at the same time with a similar Metadata. you furthermore mght find out how to:

* Create customized kinds for use on your schema, and whilst it's precious to exploit customized instead of integrated types
* Run queries, updates, and deletes with SQLAlchemy's SQL expression language
* construct an item mapper with SQLAlchemy, and comprehend the diversities among this and lively checklist styles utilized in different ORMs
* Create items, store them to a consultation, and flush them to the database
* Use SQLAlchemy to version item orientated inheritance
* offer a declarative, lively list development to be used with SQLAlchemy utilizing the Elixir extension
* Use the SQLSoup extension to supply an automated metadata and item version in keeping with database reflection

In addition, you'll find out how and whilst to take advantage of different extensions to SQLAlchemy, together with AssociationProxy, OrderingList, and more.

Essential SQLAlchemy is the much-needed advisor for each Python developer utilizing this code library. rather than a feature-by-feature documentation, this publication takes an "essentials" procedure that offers you precisely what you want to develop into effective with SQLAlchemy correct away.

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In this case, the application machine’s native Python time resolution is greater than the current_timestamp provided by SQLite. Though we did not specify an update to the modified column, SQLAlchemy provides an update value based on the onupdate parameter of the column definition. Passive defaults Passive defaults are default values provided by the database itself. If a column is marked with a PassiveDefault instance, then the column will have a database-level default value and SQLAlchemy will make the Engine aware of the passive default.

In **kwargs, default False. onupdate Specifies an active default value (generated by SQLAlchemy rather than the database server) to be used when updating (but not inserting) a row in the table. In **kwargs, the default is None. autoincrement Indicates that integer-based primary keys should have autoincrementing behavior. This is applicable only if the column has no default value and is a type or subtype of Integer. In **kwargs, the default is True. quote This forces the column name to be escaped and quoted before being sent to the database (useful for column names that conflict with SQL keywords, for example).

User object at 0xb688d0>, ... User object at 0xb68910>, ... User object at 0xb68c10>] >>> for user in query: ... user_name ... filter_by(display_name='Rick Copeland'): ... password ... like('rick%')): ... password ... c attribute of the User object. It was added by the mapper as a convenience to access the names of mapped columns. user_name, and vice versa. save(newuser) Due to the UOW pattern, the new user has not yet been saved to the database. 50 ... INSERT INTO tf_user (user_name, password, display_name, created) ...

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