Class 30 — November 6

Part two is ending — Soon time to show mastery — Expect to do well

Functioning

---

Look both aways

• Back or ahead

---

Agenda

• Take stock

---

Come on down

---

Accomodations

• Students with test accomodations please see me at the end of class.

---

What to expect for the test

• Understanding of function and function invocation vocabulary, syntax, and semantics.

• Knowledge of if, for, and while statements; along with the ability to use them when problem solving.

• Ability to write functions using numbers, strings, lists, dicts, datasets, and random

• Short answer / objective questions, analysis, and implementation

---

List patterns — suppose alist, blist, and clist are lists and that value v is not a list

• To analyze a list use

result = ...

for element in alist :

  ...

return result

• To modify a list use

n = len( alist )

for i in range( 0, n ) :

  element = alist[ i ]

  ...

  alist[ i ] = element

• Important list operations

• alist.append( v )

• Appends v to end of alist.

• alist.remove( v )

• Removes first occurence of v from alist.

• alist.index( v )

• Index of first occurrence of v in alist.

• clist = alist + blist

• Concatenates alist and blist to make clist.

• v = alist.pop( )

• Removes the last element from alist. The value of that former element is the return value assigned to v.

• v = alist.pop( i )

• Removes the element at index i from alist. The value of that former element is the return value assigned to v.

• Major gotcha

blist = alist + v # cannot add a list and a non-list

blist = alist + [ v ] # can add a list with another list

---

Functions

• Functions can be invoked.

• The invocation identifies the function to be started up.

• The invocation includes the arguments. The arguments are evaluated. Copies of the values are used to initialize the parameters specified in the function definition.

• Functions must be defined. A function definition consists of a header followed by its body.

• Header: def name ( parameters ) :

• Body: remaining lines in function. How can you tell? They are indented. Body is also known as the statement list

• A return is a special statement in the body of function. When a return statement is reached in a function, the function stops executing its instructions; that is, the function immediately stop its execution.

• A return statement can optionally have a return expression following the keyword return. The expression is evaluated. A copy of that value is the return value of the function. The return value is said to be the value of the evaluation of the function invocation.

• All Python functions return values – if no return statement with a return expression is executed. The function returns None.

• A local variable is a variable initialized/defined inside a function definition.

• Local variables only exist inside the function definition (limited "scope")

• The parameters of a function are the variables listed with the parentheses in the function header.

• Parameters are local variables

• The arguments to a function are the values given within the parentheses of an invocation of the function.

• The Python way of handling the arguments is pass by value; that is, the arguments are evaluated to determine their values. Copies of those values are used to initialize the parameters.

• Because Python uses pass by value, the value of an argument is unchanged by a function invocation; that is, the value of an argument is the same after the invocation as it was before the invocation.

• Implication: not possible to write a swapping function in Python

• Because a parameter has the same value as its argument, if that argument is a list, the contents of that list can be modified. Such a change is called a side effect of the function. Functions with side effects generally have a return value of None.

---

Warnings

• A print() statement in a function is not supplying a return value. It is sending a message to the program user.

• An input() statement is wrong to include in a function body, information comes into a function through its parameters.

• No function you will be asked to implement should have a print() or input() statement.

---

Gotchas

`* Nested for-loops usually wrong unless using a list-of-lists (e.g., a dataset) or looking at one list in relation to another liset

---

Miscellaneous syntheses of past Q & A

Argument versus parameter

• Defining: e.g., in def sqrt( x ) variable x is the parameter. Parameters are variables defined in the parentheses of a function definition

• Using/Invoking: e.g., in math.sqrt( 3 ) literal 3 is the argument

---

print() versus return

• print:() display, output -- shows up in the console, not in the invoking python code

• return: produce, hand-back, give -- shows up in the invoking python code, not in the console

• Consider the following:

def f( x ) :

  print( x )

This function displays the value of x and returns None

• Consider the following:

def g( x ) :

  return x

This function does no display and returns the value of its parameter

---

How can a function change the contents of argument memory?

• Examples

def h ( my_list, my_dictionary ) :

  my_list[ index ] = ...

  my_list.remove( ... )

  my_list.append( ... )

  my_list.pop( ... )

  my_list.sort()

  my_dictionary[ key ] = value

• If we do not tell you to modify a parameter, don’t. This means do not use the above statements on a list or dictionary parameter unless we ask you to update its contents

• Does that mean we can

def f( x ) :

  y = x

  y.pop()

No! The assignment of x to y means modifying y affects x

• Does that me we can

def f( x ) :

  y = x[ : ] # or y = list( x ) or y = x.copy()

  y.pop()

Yes! The assignment to y makes it a copy of x and not x itself

---

Function sort() versus sorted():

• x.sort() modifies the contents of x to be in non-descending order and returns None

• sorted( x ) creates a new list that has the elements of x in non-descending order, returns that new list, and does not modify x

---

Dictionaries

• Unordered collection of key-value pairs

• Initialization examples

d = {} # empty dict

d = { 18 : 'voting', 67 : 'retirement', 'eighteen' : 18}

• Access values by key: d[ 18 ]

• Means the same thing as 'voting'

• Access values by key: d[ 21 ]

• Will be an error because 21 is not a key

• Access values by key: d[ 'voting' ]

• Will be an error because 'voting' is not a key

• Access values by key: d.get( 18 )

• Means the same thing as 'voting'

• Access values by key: d.get( 21 )

• Means the same thing as None (not an error)

• Access key by value: not easy, probably need a loop

• Collection of all keys: d.keys()

• Collection of all values: d.values()

• Indices: there are none (just keys)

• List of all keys: list( d.keys() )

• Set the value of a key:

d[ 100 ] = 'centarian' # makes association for key 100 to be 'centarian'

• How do we look at the keys a dict

for key in d.keys():

  # do something with key

• How do we look at the values of a dict

for value in d.values():

  # do something with value

• Trying to find and change a particular entry

• By key; e.g., change key 18 to 'adult'

d[ 18 ] = 'adult'

• By value (find key for value 18)

found = None

for key in d.keys():

  value = d[ key ]

  if value == 18:

  found = key

---

 

---

 

 

 
   
   
   
 

© 2019 Jim Cohoon

Resources from previous semesters are available.