Python

Search for '{{search_term}}'

Plain function or Callback - An example in Python

CMOS is the Code-Maven Open Source podcast that also includes video interviews. Subscribe to this feed RSS feed with your Podcast listener app or via iTunes iTunes.

What if you need to process a series of values to answer a certain question, that you cannot store in memory as a list? For example when you read a huge file? Or if you can calculate the next value based on some of the previous values and some external information that comes to light during processing. Even a random series. Or if the series is infinite and you don't know up-front how far you need to go to find your answer.

In this article we are going to see 2 solutions:

  • A plain function.
  • A function with a callback.

Then you can follow-up with a solution using iterators and another solution using generators.

In order to avoid the need to explain a complex algorithm, we are going to use the well-known Fibonacci series and the question we need to answer is "What is the first number in the series that can be divided by 17."

A much more complex use-case like that would be if you needed to go over DNA sequences in a database, constantly refining your request for the next sequence before locating one that fits your requirements.

In the case of the Fibonacci series we could compute the first few elements of the list up-front, but that won't help in the general case. Even in the case of the Fibonacci series no fixed sublist will be able to answer any arbitrary question, and in the case of the DNA sequences, it is quite clear that we don't even have enough memory to prepare the list up-front.

Simple Fibonacci function

So let's see a simple implementation of the Fibonacci series and then tweak that solution.

examples/python/fibonacci_function.py

#!/usr/bin/env python
from __future__ import print_function

def fibonacci():
    values = []
    while(True):
        if len(values) < 2:
            values.append(1)
        else:
            values = [values[-1], values[-1] + values[-2]]

if __name__ == '__main__':
    fibonacci()

There is nothing fancy in this implementation, but I don't recommend that you run it, as it does not have any output, and it does not have a stop condition. So if you run it, it will appear to be "stuck".

You could include a

print(values[-1])

in the loop to see what's going on and you could include something like this:

if (values[-1] > 100):
    break;

to limit the series.

Our "question" - divide by 17

Just to remind you that our task is to "research the Fibonacci series", and the first question we need to answer is "What is the first number in the Fibonacci series that can be divided by 17?"

So we enhance the function to return the first value that can be divided by 17:

examples/python/fibonacci_function_mod_17.py

#!/usr/bin/env python
from __future__ import print_function

def fibonacci():
    values = []
    while(True):
        if len(values) < 2:
            values.append(1)
        else:
            values = [values[-1], values[-1] + values[-2]]

        if values[-1] % 17 == 0:
            return(values[-1])

if __name__ == '__main__':
    res = fibonacci()
    print(res)

We just included the following statement, which checks if the current value of the series can be wholly divided by 17:

if values[-1] % 17 == 0:
    return(values[-1])

We have also changed the code to return the Fibonacci number that fulfills our requirement. It is much better now that the program prints the result.

Running that script will stop at 34.

Later we might have other question we need to answer. What if there is no answer at all? In case we'd better add some safety measures so the code will stop.

Safety measures - limit the loop

By including a limitation like this, we can make sure our code will eventually stop, even if we don't have an answer to our particular question.

if values[-1] > 10000:
    return

Of course we could use a much bigger number for that or we could base our limitation on the number of elements checked.

The full code is here:

examples/python/fibonacci_function_with_safety.py

from __future__ import print_function

def fibonacci():
    values = []
    while(True):
        if len(values) < 2:
            values.append(1)
        else:
            values = [values[-1], values[-1] + values[-2]]

        if values[-1] % 17 == 0:
            return(values[-1])

        if values[-1] > 10000:
            return

if __name__ == '__main__':
    res = fibonacci()
    if (res != None):
        print(res)

What was the problem?

We now have a simple function that can check a specific condition and return the first value that matches the condition. If tomorrow I'll need to answer "What is the first Fibonacci number that can be divided by 19?", or maybe "What is the first Fibonacci number that is the square of another number?",

I can just copy-paste the function and change the condition.

That sounds simple, but that means we have lots of copies of the code implementing the Fibonacci function. What if our algorithm is much larger? Do we still want to have that code to be copied over and over again?

What if we find a bug in our algorithm (or just found a better way to calculate it) after we have created 20 copies to answer various question?

That's clearly not a good path to go down.

Let's have a different approach. Let's change the Fibonacci function so it will accept a function as parameter and will call that function for every element in the Fibonacci sequence.

Callback function

The fibonacci function now looks like this: it accepts a parameter called cb which is expected to be a function and once we have calculated the new element in the series we call the callback function passing the most recent element to it: cb(values[-1]).

The returned value is expected to be a list or a tuple in which the first element will be True or False indicating if we have found the answer (True) or not yet (False). If it i True, we return the second element of the result.

def fibonacci(cb):
    values = []
    while(True):
        if len(values) < 2:
            values.append(1)
        else:
            values = [values[-1], values[-1] + values[-2]]

        r = cb(values[-1])
        if (r[0]):
            return(r[1])

Based on this the callback function must accept a single value and return a tuple of list in which the first element is True/False and the second element is the value matching our condition.

The callback function looks like this: It accepts a value v, the current value of the series. It returns True and the value it found once it found a value that can be divided by 17.

It returns True and None if it reached the safety limit we set. The True will indicate to the fibonacci function that the search has ended, and the None will indicate to the end-user that no answer was found.

Lastly, we return a tuple with only one False value indicating to the fibonacci function that this was not a good value and we are expecting to be called with another value.

def check_17(v):
    if v % 17 == 0:
        return (True, v)

    if v > 10000:
        return (True, None)

    return (False,)

The full implementation look like this:

examples/python/fibonacci_function_callback.py

#!/usr/bin/env python
from __future__ import print_function

def fibonacci(cb):
    values = []
    while(True):
        if len(values) < 2:
            values.append(1)
        else:
            values = [values[-1], values[-1] + values[-2]]

        r = cb(values[-1])
        if (r[0]):
            return(r[1])

def check_17(v):
    if v % 17 == 0:
        return (True, v)

    if v > 10000:
        return (True, None)

    return (False,)


if __name__ == '__main__':
    res = fibonacci(check_17)
    if (res != None):
        print(res)

This solution is much better than the one had earlier. Now we don't need to change the fibonacci function based on the question we are asking. We could move the fibonacci function to a module, import it and use it as an external resource. If it needs fixing, it can be fixed in one place, and all the places it is used will benefit from that.

Even better, the functions we create as callback can also be reused for by calling each other or by passing them to other sequence-generating functions.

Iterators and Generators

There are two additional solutions to this problem. One is by creating an iterator, and the other one is by creating a generator.

Comments

In the comments, please wrap your code snippets within <pre> </pre> tags and use spaces for indentation.
comments powered by Disqus