xiaojuan cai computational thinking 1 lecture 6 defining functions xiaojuan cai （蔡小娟）...
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Xiaojuan Cai Computational Thinking 1
Lecture 6
Defining Functions
Xiaojuan Cai（蔡小娟）
cxj@sjtu.edu.cn
Fall, 2015
Xiaojuan Cai Computational Thinking 2
Objective
• To understand why using functions.
• To be able to define new functions.
• To understand the details of function calls
and parameter passing.
• To write programs that use functions to
reduce code duplication and increase
program modularity.
Xiaojuan Cai Computational Thinking 3
Roadmap
• Functions, informally
• Function definition and call
• Getting results from functions
• Return values
• Modify params
• Functions and program structure
Xiaojuan Cai Computational Thinking 4
What is function?
• A function is like a subprogram, a small
program inside of a program.
• The basic idea:
• write a sequence of statements
• give that sequence a name (definition)
• execute this sequence at any time by the
name (function call).
Xiaojuan Cai Computational Thinking 5
Functions so far
• Our programs comprise a single function
called main().
• Built-in Python functions (abs)
• Functions from the standard libraries
(math.sqrt)
• Functions from the graphics module
(p.getX())
Xiaojuan Cai Computational Thinking 6
Motivating example• Happy Birthday lyrics…def main(): print "Happy birthday to you!" print "Happy birthday to you!" print "Happy birthday, dear Fred..."
print "Happy birthday to you!"
• Remove duplicates: def happy(): print "Happy birthday to you!“
Xiaojuan Cai Computational Thinking 7
Motivating example
• Using parameters• def sing(person): happy() happy() print "Happy birthday, dear", person + ".“ happy()
• A paramater is a variable that is
initialized when the function is called.
Xiaojuan Cai Computational Thinking 8
The function of functions
• Having similar or identical code in more than
one place has some drawbacks:
• writing the same code twice or more.
• this same code must be maintained in two separate
places.
• Functions can be used to reduce code
duplication and make programs more easily
understood and maintained.
Xiaojuan Cai Computational Thinking 9
Roadmap
• Functions, informally
• Function definition and call
• Getting results from functions
• Return values
• Modify params
• Functions and program structure
Xiaojuan Cai Computational Thinking 10
Functions, formally• A function definition looks like this:
def <name>(<formal-parameters>):
<body>
• The name of the function
must be an identifier
• Formal-parameters is a
possibly empty list of
variable names.
def func(x): y = x * x return y
a = func(2)
Xiaojuan Cai Computational Thinking 11
Function calls• <name>(<actual-parameters>)
• Four-step process:
• The calling program suspends at the point of the
call.
• The formal parameters of the function get assigned
(by position).
• The body of the function is executed.
• Control returns to the suspended point.
Xiaojuan Cai Computational Thinking 12
Function calls illustration
Xiaojuan Cai Computational Thinking 15
Scoping rule• The scope of a variable refers to the places in a
program a given variable can be referenced.
• The variables used inside of one function are local
to that function.
• The only way to see a variable from another
function is passing it as a parameter.x,y = 0,0
def f(x):
y = 1
print x,y
f(10)
print x,y
Xiaojuan Cai Computational Thinking 16
Global variables>>> x = 1
>>> def f():
print x
x = 2
>>> f()
>>> def h():
global x
print x
x = 2
print x
>>> h()
f() x
h() x
x
Xiaojuan Cai Computational Thinking 17
Roadmap
• Functions, informally
• Function definition and call
• Getting results from functions
• Return values
• Modify params
• Functions and program structure
Xiaojuan Cai Computational Thinking 18
Return values• Params are “inputs” of a function
• Return values are “outputs” of a function
• discRt = math.sqrt(b*b – 4*a*c)
• def square(x):
return x*x
• Functions without a return hand back a special
object, denoted None.
• Triangle2.py
Xiaojuan Cai Computational Thinking 19
Modifying params• Sometimes, we can communicate back to the caller by
making changes to the function parameters.
• def addInterest(balance, rate):
newBalance = balance * (1 + rate)
balance = newBalance
• def test():
amount = 1000
rate = 0.05
addInterest(amount, rate)
print amount
Xiaojuan Cai Computational Thinking 20
What went wrong?
Xiaojuan Cai Computational Thinking 21
What went wrong?
Xiaojuan Cai Computational Thinking 22
The same problem as alias• The formal parameters of a function
only receive the values of the actual
parameters.
Xiaojuan Cai Computational Thinking 23
Roadmap
• Functions, informally
• Function definition and call
• Getting results from functions
• Return values
• Modify params
• Functions and program structure
Xiaojuan Cai Computational Thinking 24
Program structure
• So far, functions have been used as a
mechanism for reducing code duplication.
• Another reason to use functions is to make
your programs more modular. (Even
though the amount of code increases)
• Example: 99-bottle-of-wine
Xiaojuan Cai Computational Thinking 25
Conclusion• A function is a kind of subprogram.
• A call to a function initiates a four-step process.
• 1. caller suspend, • 2. assign the formal params, • 3. execute the callee, • 4. return to the caller
• The scope of a variable is where it can be referenced.
• Functions can return values.
• Python passes parameters by value.
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