3.1.9. Functions

3.1.9.1. Purpose of Functions

  • Functions are reusable pieces of programs that take an input and produce an output.

  • Functions are Abstract Methods in other words they are not associated with an object and cannot be instantiated

3.1.9.2. Separation of Interface and Implementation

  • Everything within the box is the implementation

  • Everything outside the box is the interface

../_images/functions_classless_methods_7_0.png

3.1.9.3. Comments

  • Decide what the function must do and type this as a docstring

def function_name():
    """ Purpose and Interface of a function """
    return 0
  • Any comments about implementation w.r.t. mathematics can be included in the body as an inline comment:

a = simple_formula # Implementation comment

3.1.9.4. Syntax of Functions

  • A function definition consists of a header and a body

  • The header includes:

    • the keyword def (short for define)

    • the function name

    • 0 or more parameters enclosed by parentheses ()

    • followed by a colon :

  • The body includes:

    • a sequence of sentences, all indented by 4 spaces

    • can return or print a value

    • can include the word pass if you know you need a function, but are not sure about implementation

3.1.9.5. Deciding Names

  • All valid variable names are valid function names - but a function should not have the same name as a variable name - and should not be a built-in function

  • Function names must be descriptive, e.g. triangle_area

  • Parameter names must be descriptive, e.g. base and height

3.1.9.6. Unit Test Functions

  • To evaluate a function call, replace the function’s parameters in the body of the function by their associated values in the call and execute the body of the function

  • Do this over a range of values

  • If there is no returned value, None is returned

  • If you forget the brackets in the function call, it won’t throw an error, but assume that it’s a variable

3.1.9.7. Global and Local Variables

  • Local Variables are only available inside a function

  • Global Variables are available inside and outside a function

  • If you want to modify Global Variables from within functions, they must be declared at the start using: global variable_name

3.1.9.8. Built-in functions

print int(3.0) #convert to int
print float("3") #convert to float
print str(34) #convert to string
print abs(-5) #absolute value
print max(3,5,6,7) #maximum of a set of numbers
print min(-50, -40, -20) #minimum of a set of numbers
print round(0.123456, 4) #round to 4 d.p.
3
3.0
34
5
7
-50
0.1235

3.1.9.9. Examples of Functions

# Computes the area of a triangle
def triangle_area(base, height):    # header
    area = (1.0 / 2) * base * height             # body of function
    return area                 # output         # body of function
a1 = triangle_area(3, 8)
print a1   # you must always know what to expect from a function answer = 12
12.0
a1 = triangle_area(4, 7)
print a1  # output is 14
14.0
# Converts farenheit to celcius
def fahrenheit2celcius(fahrenheit):
    celcius = (5.0 / 9) * (fahrenheit - 32)
    return celcius

# test
c1 = fahrenheit2celcius(32)
c2 = fahrenheit2celcius(212)
print c1,c2
0.0 100.0
# Converts fahrenheit to kelvin
def fahrenheit2kelvin(fahrenheit):
    c = fahrenheit2celcius(fahrenheit) # code is reused - not re-written
    kelvin = c + 273.15
    return kelvin

#test
k1 = fahrenheit2kelvin(32)
k2 = fahrenheit2kelvin(212)
print k1, k2
273.15 373.15
# prints hello world
def hello():     #no inputs
    print "Hello, world"
    #no outputs
#test
hello()
h = hello()
print h    # None shows because there is no returned value
Hello, world
Hello, world
None

3.1.9.10. Lambda Functions

Python supports the creation of anonymous functions (i.e. functions that are not bound to a name) at runtime, using a construct called “lambda”. This is not exactly the same as lambda in functional programming languages, but it is a very powerful concept that’s well integrated into Python and is often used in conjunction with typical functional concepts like filter(), map() and reduce().

This piece of code shows the difference between a normal function definition (“f”) and a lambda function (“g”):

In [1]: def f (x): return x**2

In [2]: print f(8)
  File "<ipython-input-2-2fbe5cf80045>", line 1
    print f(8)
          ^
SyntaxError: invalid syntax


In [3]: g = lambda x: x**2

In [4]: print (g(8))
64

As you can see, f() and g() do exactly the same and can be used in the same ways. Note that the lambda definition does not include a “return” statement – it always contains an expression which is returned. Also note that you can put a lambda definition anywhere a function is expected, and you don’t have to assign it to a variable at all.