Class 23 — Friday October 16

Form with function

The task before us — Turn the abstract to concrete – Functions are at hand

Being functional — Is your mantra from now on — Embrace to your core

---

Look both ways

• Back or ahead

---

Agenda

• Start function-based chrestomathics

---

Examples

• Module harb.py

• Program inger.py

---

• Module olio.py

• Program use_olio.py

---

To do

• Look over artifacts (f any)

• Look at Hands on Python

• Look at function epistle

---

Slides

• PDF

• Slide show available at bottom of this page.

---

Program wc.py — proves my point about importance of functions

''' Purpose: determine number of lines, words, and characters in a user-specified

  web file.

'''

# import module for internet access

import url

# get the lines of text from a user-specified file

reply = input( 'Enter web file link: ' )

link = reply.strip()

contents = url.get_contents( link )

# count the number of lines, words, and characters in the contents

nbr_lines = contents.count( '\n' )

words = contents.split()

nbr_words = len( words )

nbc_chars = len( contents )

# display result

print( 'nl =', nbr_lines )

print( 'nw =', nbr_words )

print( 'nc =', nbc_chars )

---

Here we go

• Question: Why bother with functions?

• Makes problem solving possible. Without them you would need to figure out

• How to communicate with your keyboard to read what it’s being typed

• How to communicate to your display so that information can be displayed

• How to specify the range of integers a for statement uses to loop.

• How to ...

• Question: What built-in functions are missing — how should Python be updated?

• The url.py module is an attempt by me to let you skip the tedious web processing setup to do something interesting

• One of your classmates asked whether there was some function ints() that would handle a string containing a bunch of integers.

• We will get to that likely the end of next week.

---

You are already experienced with functions and modules (e.g,, wc.py)

• Used built-in functions

• Used string and list manipulating functions

• Imported standard modules and then made use of their functions

• Imported url.py and then made use of its functions

---

Module harb.py

Function add()

• Has two parameters a and b. Returns the value of a + b

• If the following code segment from program inger.py is executed

import harb

 

n1, n2 = 3, 14

n3, n4 = 15, 92

 

t1 = harb.add( n1, n2 )

t2 = harb.add( n3, n4 )

 

print( "add(", n1, ",", n2, "):", t1 )

print( "add(", n3, ",", n4, "):", t2 )

then the output should be

add( 3 , 14 ): 17

add( 15 , 92 ): 107

---

Function negate( x )

• Has one integer parameter x. Returns the additive inverse of x; i.e, -x

n5, n6 = -6, 53

 

i1 = harb.negate( n5 )

i2 = harb.negate( n6 )

 

print( "negate(", n5, "):", i1 )

print( "negate(", n6, "):", i2 )

then the output should be

negate( -6 ): 6

negate( 53 ): -53

---

Modules

• A module is a named collection of functions

• Module name required to be a legal identifier

• The functions of a module are stored in a Python file (.py) that matches the module name

• All modules we develop will be kept in your CS 1112 class folder

• Access to a module capabilities is via importing

import harb

 

...

 

---

Functions

• A function is a named block of code to carry out some specific task

• Function name required to be a legal identifier (just like variables are)

• Functions can have special variables called parameters to store start up values

• Access to a module capabilities is via invocation

module_name . function_name ( arguments )

• The module_name is the name of the .py file containing the definition of function_name().

• The function_name is the name of the function being invoked.

• The module and function names must be identifiers.

• Operator . is the selection operator. The operator indicates that a component of the indicated module is to be accessed.

• The arguments are a list of start up values copied/passed to the function so that it can carry out its task.

• The arguments are used to initialize the parameters of the function.

• For example, the below code segment twice invokes module harb function add().

t1 = harb.add( n1, n2 )

t2 = harb.add( n3, n4 )

• The first invocation passes the values of n1 and n2 to add() to use as the start up values respectively for its parameters a and b.

• The second invocation passes the values of n3 and n4 to add() to use as the start up values respectively for its parameters a and b.

• Functions can produce information that is handed back via a return statement

return return expression

• For functions that end without return statements, Python supplies the value None

 

---

Function syntax

• A function definition looks like the following

def function_name( parameters ) :

  ''' header_comment

  '''

  action

• The keyword def signals that a function is being defined

• The function_name is an identifier that names the task

• The parameters are a parenthesized list of variable names (identifiers)

• The function_name along with the parameters form the function header

• The colon  :  is a separator of the function header from the function and its action

• The header comment (docstring) describes the function

• The action is a non-empty block of statements that run when the function is invoked

• For example, the definition of function add() from module harb.py is

def add( a, b ) : # function named add(), parameters named a and b

  ''' Returns value of a + b

  '''

 

  result = a + b # compute value of interest

 

  return result # function hands back its result

---

Function invocation

• Checks whether the number of arguments in the invocation and parameters in the definition match

• No match: an execution error occurs

• Match: arguments are evaluated (values are determined)

t1 = harb.add( n1, n2 ) # good: correct number of arguments

t2 = harb.add( n3, n4 ) # good: correct number of arguments

t3 = harb.add( ) # bad: too few arguments

t4 = harb.add( n1, n2, n3, n4 ) # bad: too many arguments

• Sets aside some computer memory for carrying out the function

• That memory is called an activation record or a frame

• Stores values of the parameter variables

• The parameter variables are initialized with the argument evaluations

• Stores the values of other variables needed to perform its task

def add( a, b ) : # function named add(), parameters named a and b

  ''' Returns value of a + b

  '''

 

  result = a + b # compute value of interest

 

  return result # function hands back its result

• The function’s code runs; i.e., it has the flow of control

• Function completition process

• A function completes as soon as it reaches a return statement or when it finished executing all of the code of the function, whatever happens first.

• When the function completes, the flow of control goes back to the code that did the invocation, and it is that code now continues being executed

• If a return statement is reached, the return value is determined

• If there is an expression following keyword return, its value is the return value

• If there is no expression following keyword return, the return value is None

• If the code complete without reaching a return statement,

• The return value is set None

• Once the return value is set, the execution of the function immediately stops and

• The flow of control goes back to the statement that did the invocation

• The value of the invocation – its evaluation – is the return value

 

---

Taxonomy

• The two main kinds of functions are

• Functions that have parameters and return values

• Functions that have parameters and have None as the return value

• There can also be

• Functions that do not have parameters, but do return values

• Functions that do not have parameters and have None as the return value

---

Implementing functions

• When designing a function we need to

• Determine what information is needed upon startup

• Determine what information is to be produced

• Provide an algorithm for going from one to the other

---

What's next

• Look at Hands on Python

• Two www.python.org resources should be examined now and also re-examined later.

• The Python Tutorial includes a section on functions. I recommend before going there to thoroughly review the discussion presented here.

• Python enhancement proposal 008 (PEP 008) includes recommended practices for naming modules, functions, and variables. The recommendations suggest that function and variable names are as a rule written in _snakecase; that is, lower-case words joined by underscores. Module names are expected to be short, lower-case, and no separation between words. I will add that function names are often action or verb phrases; e.g., input_integer().

---

Slide show

---

 

---

© 2020 Jim Cohoon

Resources from previous semesters are available.