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3.8. Shortcircuitevaluationoflogicalexpressions

inp = = raw_input(

Enter Fahrenheit Temperature:

)

try:

fahr = float(inp)

cel = (fahr r - - 32.0) * * 5.0 0 / 9.0

print cel

except:

Please enter a a number

Pythonstartsbyexecutingthesequenceofstatementsinthe

try

block.Ifallgoes

well,itskipsthe

except

blockandproceeds. Ifanexceptionoccursinthe

try

block,Pythonjumpsoutofthe

try

blockandexecutesthesequenceofstatements

inthe

except

block.

python fahren2.py

Enter Fahrenheit Temperature:72

22.2222222222

python fahren2.py

Enter Fahrenheit Temperature:fred

Please enter r a number

Handlinganexceptionwitha

try

statementiscalledcatchinganexception. In

thisexample,the

except

clauseprintsanerrormessage. Ingeneral,catchingan

exceptiongivesyouachancetoﬁxtheproblem,ortryagain,oratleastendthe

programgracefully.

3.8 Shortcircuitevaluationoflogicalexpressions

WhenPythonisprocessingalogicalexpressionsuchas

x >= 2 and (x/y) >

,itevaluatestheexpressionfromleft-to-right.Becauseofthedeﬁnitionof

and

islessthan2,theexpression

x >= 2

False

andsothewholeexpressionis

False

regardlessofwhether

(x/y) > 2

evaluatesto

True

False

WhenPythondetectsthatthereisnothingtobegainedbyevaluatingtherestof

alogicalexpression,itstopsitsevaluationanddoesnotdothecomputationsin

therestofthelogicalexpression. Whentheevaluationofalogicalexpression

stopsbecausetheoverallvalueisalreadyknown,itiscalledshort-circuitingthe

evaluation.

Whilethismayseemlikeaﬁnepoint,theshortcircuitbehaviorleadstoaclever

techniquecalledtheguardianpattern.Considerthefollowingcodesequencein

thePythoninterpreter:

>>> x x = = 6

>>> y y = = 2

>>> x x >= = 2 and (x/y) > 2

True

>>> x x = = 1

>>> y y = = 0

>>> x x >= = 2 and (x/y) > 2

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Chapter3. Conditionalexecution

False

>>> x x = = 6

>>> y y = = 0

>>> x x >= = 2 and (x/y) > 2

Traceback (most t recent t call last):

File "<stdin>", , line 1, , in n <module>

ZeroDivisionError: integer r division n or modulo by zero

>>>

ThethirdcalculationfailedbecausePythonwasevaluating

(x/y)

and

waszero

whichcausesaruntimeerror. Butthesecondexampledidnotfailbecausethe

ﬁrstpartoftheexpression

x >= 2

evaluatedto

False

sothe

(x/y)

wasnotever

executedduetotheshortcircuitruleandtherewasnoerror.

Wecanconstructthelogicalexpressiontostrategicallyplaceaguardevaluation

justbeforetheevaluationthatmightcauseanerrorasfollows:

>>> x x = = 1

>>> y y = = 0

>>> x x >= = 2 and y y != = 0 and d (x/y) ) > 2

False

>>> x x = = 6

>>> y y = = 0

>>> x x >= = 2 and y y != = 0 and d (x/y) ) > 2

False

>>> x x >= = 2 and (x/y) > 2 and y != 0

Traceback (most t recent t call last):

File "<stdin>", , line 1, , in n <module>

ZeroDivisionError: integer r division n or modulo by zero

>>>

Intheﬁrstlogicalexpression,

x >= 2

False

sotheevaluationstopsatthe

and

Inthesecondlogicalexpression

x >= 2

True

but

y != 0

False

sowenever

reach

(x/y)

Inthethirdlogicalexpression,the

y != 0

isafterthe

(x/y)

calculationsothe

expressionfailswithanerror.

Inthesecondexpression,wesaythat

y != = 0

actsasaguardtoinsurethatwe

onlyexecute

(x/y)

isnon-zero.

3.9 Debugging

ThetracebackPythondisplayswhenanerroroccurscontainsalotofinformation,

butitcanbeoverwhelming,especiallywhentherearemanyframesonthestack.

Themostusefulpartsareusually:

• Whatkindoferroritwas,and

• Whereitoccurred.

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3.10. Glossary

Syntaxerrorsareusuallyeasytoﬁnd,butthereareafewgotchas.Whitespaceer-

rorscanbetrickybecausespacesandtabsareinvisibleandweareusedtoignoring

them.

>>> x x = = 5

>>>

y = = 6

File "<stdin>", , line 1

y = = 6

SyntaxError: invalid syntax

Inthisexample,theproblemisthatthesecondlineisindentedbyonespace.But

theerrormessagepointsto

, whichismisleading. . Ingeneral,errormessages

indicatewheretheproblemwasdiscovered,buttheactualerrormightbeearlier

inthecode,sometimesonapreviousline.

Thesameistrueofruntimeerrors.Supposeyouaretryingtocomputeasignal-to-

noiseratioindecibels.TheformulaisSNR

=10log

signal

noise

). InPython,

youmight write something like this:

import math

signal_power = 9

noise_power = 10

ratio = signal_power / noise_power

decibels = 10 * math.log10(ratio)

print decibels

But when you run it, you getan error message

Traceback (most recent call last):

File "snr.py", line 5, in ?

decibels = 10 * math.log10(ratio)

OverflowError: math range error

The error message indicates line 5, but there is nothing wrong with that line. To

ﬁnd the real error, it might be useful to print the value of

ratio

, which turns

out to be 0. The problem is in line 4, because dividing two integers does ﬂoor

division. The solution is to represent signalpower and noise power with ﬂoating-

point values.

In general, error messages tell you where the problem was discovered, but that is

often not where it was caused.

3.10 Glossary

body: The sequence of statements within a compound statement.

boolean expression: An expressionwhose value is either

True

False

InPython3.0,younolongergetanerrormessage;thedivisionoperatorperformsﬂoating-point

divisionevenwithintegeroperands.

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Chapter 3. Conditionalexecution

branch: One of the alternative sequences of statements in a conditional state-

ment.

chained conditional: A conditional statement with a series of alternative

branches.

comparisonoperator: One of the operators that compares its operands:

,and

conditional statement: A statement that controls the ﬂow of execution depend-

ing on some condition.

condition: The boolean expression in a conditional statement that determines

which branch is executed.

compound statement: A statement that consists of a header and a body. The

header ends with a colon (:). The bodyis indented relative to the header.

guardian pattern: Where weconstruct alogicalexpressionwithadditionalcom-

parisons totake advantage of the shortcircuit behavior.

logical operator: One of the operators that combines boolean expressions:

and

,and

not

nestedconditional: A conditional statement that appears in one of the branches

of another conditionalstatement.

traceback: A list of the functions that are executing, printed when an exception

occurs.

short circuit: When Python is part-way through evaluating a logical expression

and stops the evaluation because Python knows the ﬁnal value for the ex-

pressionwithout needing to evaluate the rest of the expression.

3.11 Exercises

Exercise 3.1 Rewrite your pay computation to give the employee 1.5 times the

hourly rate for hours worked above 40 hours.

Enter Hours: 45

Enter Rate: 10

Pay: 475.0

Exercise 3.2 Rewrite your pay program using

try

and

except

so that your pro-

gram handles non-numeric input gracefully by printing a message and exiting the

program. The following shows twoexecutions of the program:

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3.11. Exercises

Enter Hours: 20

Enter Rate: nine

Error, please enter numeric input

Enter Hours: forty

Error, please enter numeric input

Exercise 3.3 Write a program to prompt for a score between 0.0 and 1.0. If the

score is out of range print an error. If the score is between 0.0 and 1.0, print a

grade using the following table:

Score

Grade

>= 0.9

>= 0.8

>= 0.7

>= 0.6

< 0.6

Enter score: 0.95

Enter score: perfect

Bad score

Enter score: 10.0

Bad score

Enter score: 0.75

Enter score: 0.5

Run the programrepeatedlyas shown above to testthevarious differentvalues for

input.

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Chapter 3. Conditionalexecution

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Chapter 4

Functions

4.1 Function calls

In the context of programming, a function is a named sequence of statements that

performs a computation. When you deﬁne a function, you specify the name and

the sequence of statements. Later, you can “call” the function by name. We have

alreadyseen one example of a functioncall:

>>> type(32)

<type

int

The name of the function is

type

. The expression in parentheses is called the

argument of thefunction. The argumentis a value or variable thatweare passing

into the function as input to the function. The result, for the

type

function, is the

type of the argument.

It is common to say that a function “takes” an argument and “returns” a result.

The resultis called the return value.

4.2 Built-in functions

Python provides a number of important built-in functions thatwe can use without

needing to provide the function deﬁnition. The creators of Python wrote a set of

functions to solve common problems and included them in Python for us to use.

The

max

and

min

functions give us the largest andsmallestvalues ina list, respec-

tively:

>>> max(

Hello world

)

>>> min(

Hello world

)

' '

>>>

Chapter 4. Functions

The

max

function tells us the “largestcharacter”inthe string(whichturnsoutto be

the letter “w”) and the

min

function shows us the smallest character which turns

outto be a space.

Another very common built-in function is the

len

function which tells us how

many items are in its argument. If the argument to

len

is a string, it returns the

number of characters in the string.

>>> len(

Hello world

)

>>>

These functions are not limited to looking at strings, they can operate on any set

of values as we will see in later chapters.

Youshouldtreatthe names of built-in functions as reserved words (i.e. avoid using

“max” as a variable name).

4.3 Type conversion functions

Python also provides built-in functions that convert values from one type to an-

other. The

int

function takes any value and converts it to an integer, if it can, or

complains otherwise:

>>> int(

)

>>> int(

Hello

)

ValueError: invalid literal for int(): Hello

int

can convert ﬂoating-point values to integers, but it doesn’t roundoff; itchops

off the fraction part:

>>> int(3.99999)

>>> int(-2.3)

-2

float

converts integers and strings to ﬂoating-point numbers:

>>> float(32)

32.0

>>> float(

3.14159

)

3.14159

Finally,

str

converts its argumentto a string:

>>> str(32)

>>> str(3.14159)

3.14159

4.4. Random numbers

4.4 Random numbers

Given the same inputs, most computer programs generate the same outputs every

time, so they are said to be deterministic. Determinism is usually a good thing,

since we expect the same calculation to yield the same result. For some applica-

tions, though, we want the computer to be unpredictable. Games are an obvious

example, butthere are more.

Making a program truly nondeterministic turns out to be not so easy, but there

are ways to make it at least seem nondeterministic. One of them is to use algo-

rithms that generate pseudorandom numbers. Pseudorandom numbers are not

truly random because they are generated by a deterministic computation, but just

by lookingatthenumbers itisallbutimpossibleto distinguish them fromrandom.

The

random

module provides functions that generate pseudorandom numbers

(which I will simply call “random” from here on).

The function

random

returns a random ﬂoat between 0.0 and 1.0 (including 0.0

but not 1.0). Each time you call

random

,you get the nextnumber in a longseries.

To see a sample, runthis loop:

import random

for i in range(10):

x = random.random()

print x

This program produces the following listof 10 random numbers between 0.0 and

up to but notincluding 1.0.

0.301927091705

0.513787075867

0.319470430881

0.285145917252

0.839069045123

0.322027080731

0.550722110248

0.366591677812

0.396981483964

0.838116437404

Exercise 4.1 Run the program on your system and see what numbers you get.

Run the program more thanonce and see whatnumbers youget.

The

random

function is only one of many functions which handle random num-

bers. The function

randint

takes parameters

low

and

high

andreturns an integer

between

low

and

high

(including both).

>>> random.randint(5, 10)

Chapter 4. Functions

To choose an element from a sequence at random, you can use

choice

>>> t = [1, 2, 3]

>>> random.choice(t)

The

random

module also provides functions to generate random values from con-

tinuous distributions including Gaussian, exponential, gamma, and a few more.

4.5 Math functions

Python has a math module that provides most of the familiar mathematical func-

tions. Before we can use the module, we have to import it:

>>> import math

This statement creates a module object named math. If you print the module

object, you get some information aboutit:

>>> print math

<module

math

from

/usr/lib/python2.5/lib-dynload/math.so

The module object contains the functions and variables deﬁned in the module. To

access one of the functions, you have to specify the name of the module and the

name of the function, separated by a dot (also known as a period). This format is

called dot notation.

>>> ratio = signal_power / noise_power

>>> decibels = 10 * math.log10(ratio)

>>> radians = 0.7

>>> height = math.sin(radians)

The ﬁrst example computes the logarithm base 10 of thesignal-to-noise ratio. The

mathmodulealso provides a function called

log

that computes logarithms base

The second example ﬁnds the sine of

radians

.The name of the variable is a hint

that

sin

and the other trigonometric functions (

cos

tan

,etc.) take arguments in

radians. To convertfrom degrees to radians, divide by 360 and multiply by 2π:

>>> degrees = 45

>>> radians = degrees / 360.0 * 2 * math.pi

>>> math.sin(radians)

0.707106781187

The expression

math.pi

gets the variable

from the math module. The value of

this variable is anapproximation of π, accurate to about 15 digits.

If youknow your trigonometry, youcan checkthe previous resultbycomparing it

to the square root of two divided by two:

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