Differences between revisions 18 and 20 (spanning 2 versions)
Revision 18 as of 2007-07-12 16:03:34
Size: 3598
Editor: niemeyer
Comment:
Revision 20 as of 2007-07-13 08:30:28
Size: 3369
Editor: niemeyer
Comment:
Deletions are marked like this. Additions are marked like this.
Line 10: Line 10:
 * Storm works well with existing database schemas. '''Design'''

 * Clean and lightweight API offers a short learning curve and long-term
 maintainability.
 * Storm is developed in a test-driven manner. An untested line of code is
 considered a bug.
 * Storm needs no special class constructors, nor imperative base classes.
 * Storm is well designed (different classes have very clear boundaries,
 with small and clean public APIs).
 * Designed from day one to work both with thin relational databases, such
 as SQLite, and big iron systems like PostgreSQL and MySQL.
 * Storm is easy to debug, since its code is written with a KISS principle,
 and thus is easy to understand.
Line 14: Line 26:
 * Clean and lightweight API offers a short learning curve and long-term
 maintainability.
 * Designed from day one to work both with thin relational databases, such
 as SQLite, and big iron systems like PostgreSQL and MySQL.
 * Distributed database integrity using two-phase commit (if your Python
 driver and database backend support it).
 * It's very easy to write and support backends for Storm (current backends
 have around 100 lines of code).

'''Features'''
Line 24: Line 35:
 * Storm is developed in a test-driven manner. An untested line of code is
 considered a bug.
 * It's very easy to write and support backends for Storm (current backends
 have around 100 lines of code).
 * Storm needs no special class constructors, nor imperative base classes.
 * Clean and lightweight API offers a short learning curve and long-term
 maintainability.
 * Storm is developed in a test-driven manner. An untested line of code is
 considered a bug.
 * It's very easy to write and support backends for Storm (current backends
 have around 100 lines of code).
 * Storm is well designed (different classes have very clear boundaries,
 with small and clean public APIs).
 * Storm is easy to debug, since its code is written with a KISS principle,
 and thus is easy to understand.
 * Storm handles composed primary keys with ease (no need for surrogate keys).
Line 40: Line 37:
 manage the schema as wanted.
 * As
a result of the last point, creating classes in Storm is clean
and simple.
 manage the schema as wanted, and creating classes that work with Storm
is clean and simple.
Line 44: Line 40:
 same Python types (or different ones) with any of them.  same Python types (or different ones) with all of them.
Line 48: Line 44:
 * Storm handles relationships between objects even before they were
 added to a database.
 * Storm works well with existing database schemas.

What is Storm?

Storm is an object-relational mapper (ORM) for Python developed at Canonical. The project has been in development for more than a year for use in Canonical projects such as [https://launchpad.net Launchpad], and has recently been released as an open-source product.

Highlights

Design

  • Clean and lightweight API offers a short learning curve and long-term maintainability.
  • Storm is developed in a test-driven manner. An untested line of code is considered a bug.
  • Storm needs no special class constructors, nor imperative base classes.
  • Storm is well designed (different classes have very clear boundaries, with small and clean public APIs).
  • Designed from day one to work both with thin relational databases, such as SQLite, and big iron systems like PostgreSQL and MySQL.
  • Storm is easy to debug, since its code is written with a KISS principle, and thus is easy to understand.
  • Designed from day one to work both at the low end, with trivial small databases, and the high end, with applications accessing billion row tables and committing to multiple database backends.
  • It's very easy to write and support backends for Storm (current backends have around 100 lines of code).

Features

  • Storm lets you efficiently access and update large datasets by allowing you to formulate complex queries spanning multiple tables using Python.
  • Storm allows you to fallback to SQL if needed (or if you just prefer), allowing you to mix "old school" code and ORM code
  • Storm handles composed primary keys with ease (no need for surrogate keys).
  • Storm doesn't do schema management, and as a result you're free to manage the schema as wanted, and creating classes that work with Storm is clean and simple.
  • Storm works very well connecting to several databases and using the same Python types (or different ones) with all of them.
  • Storm can handle obj.attr = <A SQL expression> assignments, when that's really needed (the expression is executed at INSERT/UPDATE time).

  • Storm handles relationships between objects even before they were added to a database.
  • Storm works well with existing database schemas.

Documentation

There's a [:Tutorial: tutorial] available. More documentation will come in the near future. Questions are welcome in the mailing list.

  • [:Dependencies: Dependencies/Requirements]

License

Storm is licensed under the [http://www.gnu.org/licenses/old-licenses/lgpl-2.1.html LGPL 2.1].

Community

The Storm mailing list is publicly available at:

There is also a #storm IRC channel on irc.freenode.net; stop by and chat!

Development

Development of Storm may be tracked in Launchpad:

The source code may be obtained using [http://bazaar-vcs.org Bazaar]:

  • bzr branch http://bazaar.launchpad.net/~storm/storm/trunk

Code may be browsed at:

Download

You can find released files at:

FrontPage (last edited 2020-05-28 12:17:27 by cjwatson)