convert pdf to image c# ghostscript: Change security settings on pdf software Library dll windows .net asp.net web forms O'Reilly%20-%20Python%20Cookbook6-part1489

The built-in function

iter

, new in Python 2.2, returns an iterator, if possible.

for x

in s

implicitly calls the

iter

function, so the

canLoopOver

function can easily check if

for

applicable by calling

iter

explicitly and seeing if that raises an exception.

In Python 2.1 and earlier, there is no

iter

function, so we have to try more directly:

def canLoopOver(maybeIterable):

try:

for x in maybeIterable:

return 1

else:

return 1

except:

return 0

Here we have to rely on the

for

statement itself raising an exception if

maybeIterable

not iterable after all. Note that this approach is not fully suitable for Python 2.2: if

maybeIterable

is an iterator object, the

for

in this approach consumes its first item.

Neither of these implementations of

canLoopOver

is entirely satisfactory, by itself, as our

scalar-testing predicate. The problem is with strings, Unicode strings, and other string-like objects.

These objects are perfectly good sequences, and we could loop on them with a

for

statement, but

we typically want to treat them as scalars. And even if we didn't, we would at least have to treat

any string-like objects with a length of 1 as scalars. Otherwise, since such strings are iterable and

yield themselves as their only items, our

flatten

function would not cease recursion until it

exhausted the call stack and raised a

RuntimeError

due to "maximum recursion depth

exceeded."

Fortunately, we can easily distinguish string-like objects by attempting a typical string operation

on them:

def isStringLike(obj):

try: obj+''

except TypeError: return 0

else: return 1

Now, we finally have a good implementation for the scalar-checking predicate:

def isScalar(obj):

return isStringLike(obj) or not canLoopOver(obj)

By simply placing this

isScalar

function and the appropriate implementation of

canLoopOver

in our module, before the recipe's functions, we can change the signatures of

these functions to make them easier to call in most cases. For example:

def flatten22(sequence, scalarp=isScalar):

Now the caller needs to pass the

scalarp

argument only in those (hopefully rare) cases where

our definition of what is scalar does not quite meet the caller's application-specific needs.

1.13.4 See Also

The Library Reference section on sequence types.

Change security settings on pdf - C# PDF Digital Signature Library: add, remove, update PDF digital signatures in C#.net, ASP.NET, MVC, WPF

Help to Improve the Security of Your PDF File by Adding Digital Signatures

decrypt pdf file; secure pdf file

Change security settings on pdf - VB.NET PDF Digital Signature Library: add, remove, update PDF digital signatures in vb.net, ASP.NET, MVC, WPF

Guide VB.NET Programmers to Improve the Security of Your PDF File by Adding Digital Signatures

convert locked pdf to word online; secure pdf remove

1.14 Looping in Parallel over Index and Sequence Items

Credit: Alex Martelli

1.14.1 Problem

You need to loop on a sequence, but at each step you also need to know what index into the

sequence you have reached.

1.14.2 Solution

Together, the built-in functions

xrange

and

zip

make this easy. You need only this one

instance of

xrange

, as it is fully reusable:

indices = xrange(sys.maxint)

Here's how you use the

indices

instance:

for item, index in zip(sequence, indices):

something(item, index)

This gives the same semantics as:

for index in range(len(sequence)):

something(sequence[index], index)

but the change of emphasis allows greater clarity in many usage contexts.

Another alternative is to use class wrappers:

class Indexed:

def _ _init_ _(self, seq):

self.seq = seq

def _ _getitem_ _(self, i):

return self.seq[i], i

For example:

for item, index in Indexed(sequence):

something(item, index)

In Python 2.2, with

from _ _future_ _ import generators

, you can also use:

def Indexed(sequence):

iterator = iter(sequence)

for index in indices:

yield iterator.next( ), index

# Note that we exit by propagating StopIteration

when .next raises it!

Online Change your PDF file Permission Settings

easy as possible to change your PDF file permission settings. You can receive the locked PDF by simply clicking download and you are good to go!. Web Security.

advanced pdf encryption remover; decrypt a pdf

VB.NET PDF Password Library: add, remove, edit PDF file password

RasterEdge XDoc.PDF SDK provides some PDF security settings about password to help protect your PDF document Add password to PDF. Change PDF original password.

decrypt pdf password; copy paste encrypted pdf

However, the simplest roughly equivalent way remains the good old:

def Indexed(sequence):

return zip(sequence, indices)

1.14.3 Discussion

We often want to loop on a sequence but also need the current index in the loop body. The

canonical Pydiom for this is:

for i in range(len(sequence)):

using

sequence[i]

as the item reference in the loop's body. However, in many contexts, it is

clearer to emphasize the loop on the sequence items rather than on the indexes.

zip

provides an

easy alternative, looping on indexes and items in parallel, since it truncates at the shortest of its

arguments. Thus, it's okay for some arguments to be unbounded sequences, as long as not all the

arguments are unbounded. An unbounded sequence of indexes is trivial to write (

xrange

handy for this), and a reusable instance of that sequence can be passed to

zip

, in parallel to the

sequence being indexed.

The same

zip

usage also affords a client code-transparent alternative to the use of a wrapper

class

Indexed

, as demonstrated by the

Indexed

class, generator, and function shown in the

solution. Of these, when applicable,

zip

is simplest.

The performance of each of these solutions is roughly equivalent. They're all O(N) (i.e., they

execute in time proportional to the number of elements in the sequence), they all take O(1) extra

memory, and none is anything close to twice as fast or as slow as another.

Note that

zip

is not lazy (i.e., it cannot accept all argument sequences being unbounded).

Therefore, in certain cases in which

zip

cannot be used (albeit not the typical one in which

range(len(sequence))

is the alternative), other kinds of loop might be usable. See

Recipe 17.13

for lazy, iterator-based alternatives, including an

xzip

function (Python 2.2 only).

1.14.4 See Also

Recipe 17.13

; the Library Reference section on sequence types.

C# PDF Password Library: add, remove, edit PDF file password in C#

Able to change password on adobe PDF document in C#.NET. To help protect your PDF document in C# project, XDoc.PDF provides some PDF security settings.

create secure pdf online; pdf encryption

Online Split PDF file. Best free online split PDF tool.

You can use our .NET PDF SDK to set file split settings for your PDF You can receive the PDF files by simply clicking download and you are good to Web Security.

create pdf the security level is set to high; convert locked pdf to word doc

1.15 Looping Through Multiple Lists

Credit: Andy McKay

1.15.1 Problem

You need to loop through every item of multiple lists.

1.15.2 Solution

There are basically three approaches. Say you have:

a = ['a1', 'a2', 'a3']

b = ['b1', 'b2']

Using the built-in function

map

, with a first argument of

None

, you can iterate on both lists in

parallel:

print "Map:"

for x, y in map(None, a, b):

print x, y

The loop runs three times. On the last iteration,

will be

None

Using the built-in function

zip

also lets you iterate in parallel:

print "Zip:"

for x, y in zip(a, b):

print x, y

The loop runs two times; the third iteration simply is not done.

A list comprehension affords a very different iteration:

print "List comprehension:"

for x, y in [(x,y) for x in a for y in b]:

print x, y

The loop runs six times, over each item of

for each item of

1.15.3 Discussion

Using

map

with

None

as the first argument is a subtle variation of the standard

map

call, which

typically takes a function as the first argument. As the documentation indicates, if the first

argument is

None

, the identity function is used as the function through which the arguments are

mapped. If there are multiple list arguments,

map

returns a list consisting of tuples that contain

the corresponding items from all lists (in other words, it's a kind of transpose operation). The list

arguments may be any kind of sequence, and the result is always a list.

Note that the first technique returns

None

for sequences in which there are no more elements.

Therefore, the output of the first loop is:

Online Remove password from protected PDF file

If we need a password from you, it will not be read or stored. To hlep protect your PDF document in C# project, XDoc.PDF provides some PDF security settings.

decrypt pdf without password; secure pdf

VB.NET PDF Library SDK to view, edit, convert, process PDF file

PDF Document Protection. XDoc.PDF SDK allows users to perform PDF document security settings in VB.NET program. Password, digital

creating a secure pdf document; creating secure pdf files

Map:

a1 b1

a2 b2

a3 None

zip

lets you iterate over the lists in a similar way, but only up to the number of elements of the

smallest list. Therefore, the output of the second technique is:

Zip:

a1 b1

a2 b2

Python 2.0 introduced list comprehensions, with a syntax that some found a bit strange:

[(x,y) for x in a for y in b]

This iterates over list

for every element in

. These elements are put into a tuple

(x,

. We

then iterate through the resulting list of tuples in the outermost

for

loop. The output of the third

technique, therefore, is quite different:

List comprehension:

a1 b1

a1 b2

a2 b1

a2 b2

a3 b1

a3 b2

1.15.4 See Also

The Library Reference section on sequence types; documentation for the

zip

and

map

built-ins

in the Library Reference.

C# HTML5 Viewer: Deployment on AzureCloudService

RasterEdge.XDoc.PDF.HTML5Editor.dll. system.webServer> <validation validateIntegratedModeConfiguration="false"/> <security> <requestFiltering

cannot print pdf security; change security settings pdf reader

C# HTML5 Viewer: Deployment on ASP.NET MVC

RasterEdge.XDoc.PDF.HTML5Editor.dll. system.webServer> <validation validateIntegratedModeConfiguration="false"/> <security> <requestFiltering

can print pdf security; convert secure pdf to word

1.16 Spanning a Range Defined by Floats

Credit: Dinu C. Gherman, Paul M. Winkler

1.16.1 Problem

You need an arithmetic progression, just like the built-in function

range

, but with float values

(

range

works only on integers).

1.16.2 Solution

Although this functionality is not available as a built-in, it's not hard to code it with a loop:

def frange(start, end=None, inc=1.0):

"A range-like function that does accept float

increments..."

if end == None:

end = start + 0.0 # Ensure a float value for

'end'

start = 0.0

assert inc # sanity check

L = []

while 1:

next = start + len(L) * inc

if inc > 0 and next >= end:

break

elif inc < 0 and next <= end:

break

L.append(next)

return L

1.16.3 Discussion

Sadly missing in the Python standard library, the function in this recipe lets you use ranges, just as

with the built-in function

range

, but with float arguments.

Many theoretical restrictions apply, but this function is more useful in practice than in theory.

People who work with floating-point numbers all the time have many war stories about billion-

dollar projects that failed because someone did not take into consideration the strange things that

modern hardware does when comparing floating-point numbers. But for pedestrian cases, simple

approaches like this recipe generally work.

You can get a substantial speed boost by preallocating the list instead of calling

append

repeatedly. This also allows you to get rid of the conditionals in the inner loop. For one element,

this version is barely faster, but with more than 10 elements it's consistently about 5 times faster—

the kind of performance ratio that is worth caring about. I get identical output for every test case I

can think of:

def frange2(start, end=None, inc=1.0):

Online Convert Jpeg to PDF file. Best free online export Jpg image

the conversion settings you like, and download it with one click. The entire process is quick, free and very easy. Web Security. All your JPG and PDF files will

convert secure webpage to pdf; pdf security password

"A faster range-like function that does accept float

increments..."

if end == None:

end = start + 0.0

start = 0.0

else: start += 0.0 # force it to be a float

count = int((end - start) / inc)

if start + count * inc != end:

# Need to adjust the count. AFAICT, it always comes

up one short.

count += 1

L = [start] * count

for i in xrange(1, count):

L[i] = start + i * inc

return L

Both versions rely on a single multiplication and one addition to compute each item, to avoid

accumulating error by repeated additions. This is why, for example, the body of the

for

loop in

frange2

is not:

L[i] = L[i-1] + inc

In Python 2.2, if all you need to do is loop on the result of

frange

, you can save some memory

by turning this function into a simple generator, yielding an iterator when you call it:

from _ _future_ _ import generators

def frangei(start, end=None, inc=1.0):

"An xrange-like simple generator that does accept float

increments..."

if end == None:

end = start + 0.0

start = 0.0

assert inc # sanity check

i = 0

while 1:

next = start + i * inc

if inc > 0 and next >= end:

break

elif inc < 0 and next <= end:

break

yield next

i += 1

If you use this recipe a lot, you should probably take a look at Numeric Python and other third-

party packages that take computing with floating-point numbers seriously. This recipe, for

example, will not scale well to very large ranges, while those defined in Numeric Python will.

1.16.4 See Also

Documentation for the

range

built-in function in the Library Reference; Numeric Python

(http://www.pfdubois.com/numpy/

1.17 Transposing Two-Dimensional Arrays

Credit: Steve Holden

1.17.1 Problem

You need to transpose a list of lists, turning rows into columns and vice versa.

1.17.2 Solution

You must start with a list whose items are lists all of the same length:

arr = [[1,2,3], [4,5,6], [7,8,9], [10,11,12]]

A list comprehension offers a simple, handy way to transpose it:

print [[r[col] for r in arr] for col in range(len(arr[0]))]

[[1, 4, 7, 10], [2, 5, 8, 11], [3, 6, 9, 12]]

1.17.3 Discussion

This recipe shows a concise way (although not necessarily the fastest way) to turn rows into

columns. List comprehensions are known for being concise.

Sometimes data just comes at you the wrong way. For instance, if you use Microsoft's ADO

database interface, due to array element ordering differences between Python and Microsoft's

preferred implementation language (Visual Basic), the

GetRows

method actually appears to

return database columns in Python, despite its name. This recipe's solution to this common

problem was chosen to demonstrate nested list comprehensions.

Notice that the inner comprehension varies what is selected from (the row), while the outer

comprehension varies the selector (the column). This process achieves the required transposition.

If you're transposing large arrays of numbers, consider Numeric Python and other third-party

packages. Numeric Python defines transposition and other axis-swinging routines that will make

your head spin.

1.17.4 See Also

The Reference Manual section on list displays (the other name for list comprehensions); Numeric

Python (http://www.pfdubois.com/numpy/

1.18 Creating Lists of Lists Without Sharing References

Credit: David Ascher

1.18.1 Problem

You want to create a multidimensional list, but the apparently simplest solution is fraught with

surprises.

1.18.2 Solution

Use list comprehensions (also known as list displays) to avoid implicit reference sharing:

multilist = [[0 for col in range(5)] for row in range(10)]

1.18.3 Discussion

When a newcomer to Python is shown the power of the multiplication operation on lists, he often

gets quite excited about it, since it is such an elegant notation. For example:

>>> [0] * 5

[0, 0, 0, 0, 0]

The problem is that one-dimensional problems often grow a second dimension, so there is a

natural progression to:

>>> multi = [[0] * 5] * 3

>>> print multi

[[0, 0, 0, 0, 0], [0, 0, 0, 0, 0], [0, 0, 0, 0, 0]]

This appears to have worked, but the same newcomer is then often puzzled by bugs, which

typically can be boiled down to the following test:

>>> multi[0][0] = 'Changed!'

>>> print multi

[['Changed!', 0, 0, 0, 0], ['Changed!', 0, 0, 0, 0],

['Changed!', 0, 0, 0, 0]]

This problem definitely confuses most programmers at least once, if not a few times (see the FAQ

entry at http://www.python.org/doc/FAQ.html#4.50

). To understand it, it helps to decompose the

creation of the multidimensional list into two steps:

>>> row = [0] * 5 # a list with five references to

>>> multi = [row] * 3 # a list with three references to

the row object

The problem still exists in this version (Python is not that magical). The comments are key to

understanding the source of the confusion. The process of multiplying a sequence by a number

creates a new sequence with the specified number of new references to the original contents. In

the case of the creation of

row

, it doesn't matter whether references are being duplicated or not,

since the referent (the object being referred to) is immutable. In other words, there is no difference

Documents you may be interested

convert pdf to image c# ghostscript : Change security settings on pdf software Library dll windows .net asp.net web forms O'Reilly%20-%20Python%20Cookbook6-part1489