4.9. Summary
Description: Python from novice to pro
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# Dive Into Python Python from novice to pro | Find:

## 4.9. Summary

The `apihelper.py` program and its output should now make perfect sense.

    def info(object, spacing=10, collapse=1):
        """Print methods and doc strings.

        Takes module, class, list, dictionary, or string."""
        methodList = [method for method in dir(object) if callable(getattr(object, method))]
        processFunc = collapse and (lambda s: " ".join(s.split())) or (lambda s: s)
        print "\n".join(["%s %s" %
                          (method.ljust(spacing),
                           processFunc(str(getattr(object, method).__doc__)))
                         for method in methodList])

    if __name__ == "__main__":
        print info.__doc__

Here is the output of `apihelper.py`:

    >>> from apihelper import info
    >>> li = []
    >>> info(li)
    append     L.append(object) -- append object to end
    count      L.count(value) -> integer -- return number of occurrences of value
    extend     L.extend(list) -- extend list by appending list elements
    index      L.index(value) -> integer -- return index of first occurrence of value
    insert     L.insert(index, object) -- insert object before index
    pop        L.pop([index]) -> item -- remove and return item at index (default last)
    remove     L.remove(value) -- remove first occurrence of value
    reverse    L.reverse() -- reverse *IN PLACE*
    sort       L.sort([cmpfunc]) -- sort *IN PLACE*; if given, cmpfunc(x, y) -> -1, 0, 1

Before diving into the next chapter, make sure you're comfortable doing all of these things:

- Defining and calling functions with optional and named arguments
- Using `str` to coerce any arbitrary value into a string representation
- Using `getattr` to get references to functions and other attributes dynamically
- Extending the list comprehension syntax to do list filtering
- Recognizing the `and-or` trick and using it safely
- Defining `lambda` functions
- Assigning functions to variables and calling the function by referencing the variable. I can't emphasize this enough, because this mode of thought is vital to advancing your understanding of Python. You'll see more complex applications of this concept throughout this book.