QAL is a collection of libraries for mixing, moving and updating data from and to SQL databases and files.
Sources and destinations include different database backends, files format like .csv, XML and excel. And even untidy HTML web pages.
For SQL backends, it has a database abstraction layer that supports basic connectivity to Postgres, MySQL, DB2, Oracle and MS SQL server.
It uses XML formats(the SQL schema is self-generated) for representation of queries, transformation and merging, making it all scriptable.
With regards to SQL, QAL uses a subset of SQL features and data types, which while not complete however should be sufficient for most usages. It is however easy to instead use backend specific SQL when the queries don't have to be backend-agnostic.
It is currently only distributed as a Python Library (.egg), but more formats are coming.
It is related to the Optimal BPM and UBE projects. Historically, the Optimal BPM project used to be DAL/QAL.
- Data transformation
- Query Abstraction layer
- SQL server
- flat file
- Multi platform
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