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Python Persistence ManagementBy Patrick O'Brien2005-04-05 
Use serialization to store Python objects
Persistence is all about keeping objects around, even between executions of a program. In this article you'll get a general understanding of various persistence mechanisms for Python objects, from relational databases to Python pickles and beyond. You'll also take an in-depth look at Python's object serialization capabilities. What is persistence? The basic idea of persistence is fairly simple. Let's say you've got a Python program, perhaps to manage your daily to-do list, and you want to save your application objects (your to-do items) between uses of the program. In other words, you want to store your objects to disk and retrieve them later. That's persistence. To accomplish that goal you've got several options, each with advantages and disadvantages. For example, you could store your object's data in some kind of formatted text file, such as a CSV file. Or you could use a relational database, such as Gadfly, MySQL, PostgreSQL, or DB2. These file formats and databases are well established, and Python has robust interfaces for all of these storage mechanisms. One thing these storage mechanisms all have in common is that data is stored independent of the objects and programs that operate on the data. The benefit is that the data then becomes available as a shared resource for other applications. The drawback is that allowing access to an object's data in this way violates the object-oriented principle of encapsulation, in which an object's data should only be accessible through its own, public interface. For some applications, then, the relational database approach may not be ideal. In particular, it's because relational databases do not understand objects. Instead, relational databases impose their own type system and their own data model of relations (tables), each containing a set of tuples (rows) made up of a fixed number of statically typed fields (columns). If the object model for your application doesn't translate easily into the relational model, you'll have quite a challenge mapping your objects to tuples and back again. This challenge is often referred to as an impedence-mismatch problem. Tutorial Pages: » Use serialization to store Python objects » Object persistence » A peck of pickled Python » Pickle power » Schema evolution » Conclusion » Resources First published by IBM DeveloperWorks
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