Why the Interactive Prompt?

The interactive prompt runs code and echoes results as you go, but it doesn’t save your code in a file. Although this means you won’t do the bulk of your coding in interactive sessions, the interactive prompt turns out to be a great place to both experiment with the language and test program files on the fly.

Experimenting

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Because code is executed immediately, the interactive prompt is a perfect place to experiment with the language and will be used often in this book to demonstrate smaller examples. In fact, this is the first rule of thumb to remember: if you’re ever in doubt about how a piece of Python code works, fire up the interactive command line and try it out to see what happens.

For instance, suppose you’re reading a Python program’s code and you come across an expression like 'Spam!' * 8 whose meaning you don’t understand. At this point, you can spend 10 minutes wading through manuals and books to try to figure out what the code does, or you can simply run it interactively:

>>> 'Spam!' * 8                                  <== Learning by trying
'Spam!Spam!Spam!Spam!Spam!Spam!Spam!Spam!'

The immediate feedback you receive at the interactive prompt is often the quickest way to deduce what a piece of code does. Here, it’s clear that it does string repetition: in Python * means multiply for numbers, but repeat for strings—it’s like concatenating a string to itself repeatedly (more on strings in Chapter 4).

Chances are good that you won’t break anything by experimenting this way—at least, not yet. To do real damage, like deleting files and running shell commands, you must really try, by importing modules explicitly (you also need to know more about Python’s system interfaces in general before you will become that dangerous!). Straight Python code is almost always safe to run.

For instance, watch what happens when you make a mistake at the interactive prompt:

>>> X                                            <== Making mistakes
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
NameError: name 'X' is not defined

In Python, using a variable before it has been assigned a value is always an error (otherwise, if names were filled in with defaults, some errors might go undetected). We’ll learn more about that later; the important point here is that you don’t crash Python or your computer when you make a mistake this way. Instead, you get a meaningful error message pointing out the mistake and the line of code that made it, and you can continue on in your session or script. In fact, once you get comfortable with Python, its error messages may often provide as much debugging support as you’ll need (you’ll read more on debugging in the sidebar Debugging Python Code).

Testing

Besides serving as a tool for experimenting while you’re learning the language, the interactive interpreter is also an ideal place to test code you’ve written in files. You can import your module files interactively and run tests on the tools they define by typing calls at the interactive prompt.

For instance, the following tests a function in a precoded module that ships with Python in its standard library (it prints the name of the directory you’re currently working in), but you can do the same once you start writing module files of your own:

>>> import os
>>> os.getcwd()                                  <== Testing on the fly
'c:\\Python30'

More generally, the interactive prompt is a place to test program components, regardless of their source—you can import and test functions and classes in your Python files, type calls to linked-in C functions, exercise Java classes under Jython, and more. Partly because of its interactive nature, Python supports an experimental and exploratory programming style you’ll find convenient when getting started.