How can we effectively store and retrieve functions in data structures like lists and dictionaries?

Storing and Invoking Functions in Data Structures

In programming, we often need to organize and manage functions for efficient execution. One common approach is to store functions in data structures like lists and dictionaries, allowing us to reference and invoke them dynamically. However, the question arises: how can we effectively store and retrieve functions in these structures?

For example, consider the following approach:

<code class="python">mydict = {
    'funcList1': [foo(), bar(), goo()],
    'funcList2': [foo(), goo(), bar()]}</code>

This approach attempts to store the results of function calls (i.e., return values) in a dictionary, but it will not work as expected. Instead, we need a way to store the actual function objects themselves.

In Python, functions are first-class objects, which means they can be treated as values and stored in data structures. To effectively store functions in a dictionary, we need to assign the function objects to keys, not their return values. For example:

<code class="python">dispatcher = {'foo': foo, 'bar': bar}</code>

where foo and bar are function objects.

To invoke a function from this dictionary, we simply call it using its key:

<code class="python">dispatcher['foo']()  # calls the foo function</code>

If we need to run multiple functions stored in a list, we can use a helper function to iterate through the list and invoke each function:

<code class="python">dispatcher = {'foobar': [foo, bar], 'bazcat': [baz, cat]}

def fire_all(func_list):
    for f in func_list:
        f()

fire_all(dispatcher['foobar'])</code>

This approach allows us to organize and invoke functions dynamically, facilitating code organization and reducing the number of def statements needed.

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