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3.8. Shortcircuitevaluationoflogicalexpressions
37
inp = = raw_input(
'
Enter Fahrenheit Temperature:
'
)
try:
fahr = float(inp)
cel = (fahr r - - 32.0) * * 5.0 0 / 9.0
print cel
except:
print
'
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) >
2
,itevaluatestheexpressionfromleft-to-right.Becauseofthedefinitionof
and
,
if
x
islessthan2,theexpression
x >= 2
is
False
andsothewholeexpressionis
False
regardlessofwhether
(x/y) > 2
evaluatesto
True
or
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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38
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
y
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
is
False
sotheevaluationstopsatthe
and
.
Inthesecondlogicalexpression
x >= 2
is
True
but
y != 0
is
False
sowenever
reach
(x/y)
.
Inthethirdlogicalexpression,the
y != 0
isafterthe
(x/y)
calculationsothe
expressionfailswithanerror.
Inthesecondexpression,wesaythat
y != = 0
actsasaguardtoinsurethatwe
onlyexecute
(x/y)
if
y
isnon-zero.
3.9 Debugging
ThetracebackPythondisplayswhenanerroroccurscontainsalotofinformation,
butitcanbeoverwhelming,especiallywhentherearemanyframesonthestack.
Themostusefulpartsareusually:
• Whatkindoferroritwas,and
• Whereitoccurred.
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3.10. Glossary
39
Syntaxerrorsareusuallyeasytofind,butthereareafewgotchas.Whitespaceer-
rorscanbetrickybecausespacesandtabsareinvisibleandweareusedtoignoring
them.
>>> x x = = 5
>>>
y = = 6
File "<stdin>", , line 1
y = = 6
ˆ
SyntaxError: invalid syntax
Inthisexample,theproblemisthatthesecondlineisindentedbyonespace.But
theerrormessagepointsto
y
, whichismisleading. . Ingeneral,errormessages
indicatewheretheproblemwasdiscovered,buttheactualerrormightbeearlier
inthecode,sometimesonapreviousline.
Thesameistrueofruntimeerrors.Supposeyouaretryingtocomputeasignal-to-
noiseratioindecibels.TheformulaisSNR
db
=10log
10
(P
signal
/P
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
1
:
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
or
False
.
1
InPython3.0,younolongergetanerrormessage;thedivisionoperatorperformsfloating-point
divisionevenwithintegeroperands.
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40
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
,
or
,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
41
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
A
>= 0.8
B
>= 0.7
C
>= 0.6
D
< 0.6
F
Enter score: 0.95
A
Enter score: perfect
Bad score
Enter score: 10.0
Bad score
Enter score: 0.75
C
Enter score: 0.5
F
Run the programrepeatedlyas shown above to testthevarious differentvalues for
input.
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42
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
'
)
'
w
'
>>> min(
'
Hello world
'
)
' '
>>>
44
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
'
)
11
>>>
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(
'
32
'
)
32
>>> 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)
3
>>> 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)
'
32
'
>>> str(3.14159)
'
3.14159
'
4.4. Random numbers
45
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)
5
>>> random.randint(5, 10)
9
46
Chapter 4. Functions
To choose an element from a sequence at random, you can use
choice
:
>>> t = [1, 2, 3]
>>> random.choice(t)
2
>>> random.choice(t)
3
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
e
.
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
pi
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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