19.2. Persistence Options in Python
In this chapter, our focus is on persistent datathe kind that outlives a program that creates it. That's not true by default for objects a script constructs; things like lists, dictionaries, and even class instance objects live in your computer's memory and are lost as soon as the script ends. To make data live longer, we need to do something special. In Python programming, there are today at least six traditional ways to save information in between program executions:
In some sense, Python's interfaces to network-based object transmission protocols such as SOAP, XML-RPC, and CORBA also offer persistence options, but they are beyond the scope of this chapter. Here, our interest is in techniques that allow a program to store its data directly and, usually, on the local machine. Although some database servers may operate on a physically remote machine on a network, this is largely transparent to most of the techniques we'll study here.
We studied Python's simple (or "flat") file interfaces in earnest in Chapter 4, and we have been using them ever since. Python provides standard access to both the stdio filesystem (through the built-in open function), as well as lower-level descriptor-based files (with the built-in os module). For simple data storage tasks, these are all that many scripts need. To save for use in a future program run, simply write data out to a newly opened file on your computer and read it back from that file later. As we've seen, for more advanced tasks, Python also supports other file-like interfaces such as pipes, fifos, and sockets.
Since we've already explored flat files, I won't say more about them here. The rest of this chapter introduces the remaining topics on the preceding list. At the end, we'll also meet a GUI program for browsing the contents of things such as shelves and DBM files. Before that, though, we need to learn what manner of beast these are.