PyDAO / Aplikacja.info

PyDAO

Dariusz Cieslak, cieslakd@users.sourceforge.net

PyDAO is very thin object-relational mapper similar to Hibernate (but much simpler). It's created to speed-up application development. It's very simple, but powerful, based on POPO (Plain Old Python Objects).

Main features

can use any database that has DB-API interface
can work without database at all (useful for early phases of development)
speeds up unit testing (dedicated in memory database)

What is not handled

automatic scheme generation (one have to create scheme "by hand")
separate query language (it's possible to use plain SQL if filtering by example is not sufficient)
automated handling of associations (foreign keys are visible in source code)

Download

You can reach latest version of PyDAO on SourceForge:

http://sourceforge.net/projects/pydao

Small example how to use PyDAO

    class User:
        def __init__(self):
            self.id = None
            self.login = None
            self.password = None

    dao = pydao.InMemoryDao()

    # filling database
    user = User()
    user.login = "user1"
    user.password = "roh8OoPh"
    dao.save(user)

    # filtering based on example
    userSearch = User()
    userSearch.login = "user1"
    userList = dao.list(userSearch)

    # updating
    user.password = "eew8Me8g"
    dao.update(user)

More examples how to use API can be found in AbstractDaoTest.py and SqlDaoTest.py. Also see: PyDAO User Guide.

Supported databases

InMemoryDao - objects stored in memory
MysqlDao - objects stored in MySQL database (tested with MySQLdb)
PostgresqlDao - objects stored in PostgreSQL database (tested with psycopg)

Logging

You can redirect logs to any open stream (sys.stderr for example) to see API calls and resulting SQL queries (if back-end is SQL type).

  save(): User {login='u1' }
    INSERT INTO TEST_USER(login,password,companyID) VALUES(%s,%s,%s)
  list(): User {}
    SELECT T.*, TC.NAME AS _companyName FROM TEST_USER T\
    LEFT JOIN TEST_COMPANY TC ON T.COMPANYID = TC.ID
  save(): User {login='u2' }
    INSERT INTO TEST_USER(login,password,companyID) VALUES(%s,%s,%s)
  list(): User {}
    SELECT T.*, TC.NAME AS _companyName FROM TEST_USER T\
    LEFT JOIN TEST_COMPANY TC ON T.COMPANYID = TC.ID
  delete(): User {}
    DELETE FROM TEST_USER

API

AbstractDao
- SimpleDao
  - InMemoryDao
  - XmlStorageDao
- SqlDao
  - MysqlDao
  - PostgresqlDao
Condition
- InRangeCondition
- InSequenceCondition
- IsNullCondition
- NotNullCondition
- LikeCondition
- ArbitraryCondition

Quality Assurance

Project is tested using unit tests. Quality of testing is visible in coverage report. Coverage is based on coverage.py module (thanks to Ned Batchelder).
Additionally public API is instrumented with Design By Contract expressions. I'm using pycontract module (thanks to Terence Way).
Method of declaring attributes is compatible with lint-like tools for Python. For static analysis I'm currently using pylint.

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