Main > Free Download Search >

Free data permaisuri software for linux

data permaisuri

Sponsored Links
Sponsored Links
Secleted [ 0 ] software to compare
Results 1 - 15 of about 4871
Data.FormValidator 0.04

Data.FormValidator 0.04


Data.FormValidators aim is to bring all the benefits of the perl module Data::FormValidator over to javascript. more>>
Data.FormValidators aim is to bring all the benefits of the perl module Data::FormValidator over to javascript, using the same input profiles (they can be dumped into javascript objects using the perl module Data::JavaScript.
Data.FormValidator library lets you define profiles which declare the required and optional fields and any constraints they might have.
The results are provided as an object which makes it easy to handle missing and invalid results, return error messages about which constraints failed, or process the resulting valid data.
IMPORTANT NOTE: JavaScript form validation is NOT a replacement for data validation in your backend scripts. This is the primary reason this module was written... so that it would be easy to share the same validation profile for both the frontend (via Data.FormValidator.js) and backend (via Data::FormValidator.pm).
Enhancements:
- A problem where some functions were not terminated by a semi-colon, so JavaScript compactors would end up creating broken code was fixed.
<<less
Download (0.047MB)
Added: 2006-01-20 License: GPL (GNU General Public License) Price:
1372 downloads
Data::Serializer 0.41

Data::Serializer 0.41


Data::Serializer package contains modules that serialize data structures. more>>
Data::Serializer package contains modules that serialize data structures.

SYNOPSIS

use Data::Serializer;

$obj = Data::Serializer->new();

$obj = Data::Serializer->new(
serializer => Storable,
digester => MD5,
cipher => DES,
secret => my secret,
compress => 1,
);

$serialized = $obj->serialize({a => [1,2,3],b => 5});
$deserialized = $obj->deserialize($serialized);
print "$deserialized->{b}n";

Provides a unified interface to the various serializing modules currently available. Adds the functionality of both compression and encryption.

EXAMPLES

Please see Data::Serializer::Cookbook(3)

METHODS

new - constructor
$obj = Data::Serializer->new();


$obj = Data::Serializer->new(
serializer => Data::Dumper,
digester => SHA-256,
cipher => Blowfish,
secret => undef,
portable => 1,
compress => 0,
serializer_token => 1,
options => {},
);

new is the constructor object for Data::Serializer objects.

The default serializer is Data::Dumper
The default digester is SHA-256
The default cipher is Blowfish
The default secret is undef
The default portable is 1
The default encoding is hex
The default compress is 0
The default compressor is Compress::Zlib
The default serializer_token is 1
The default options is {} (pass nothing on to serializer)
serialize - serialize reference

$serialized = $obj->serialize({a => [1,2,3],b => 5});

Serializes the reference specified.
Will compress if compress is a true value.
Will encrypt if secret is defined.
deserialize - deserialize reference

$deserialized = $obj->deserialize($serialized);

Reverses the process of serialization and returns a copy of the original serialized reference.

freeze - synonym for serialize
$serialized = $obj->freeze({a => [1,2,3],b => 5});

thaw - synonym for deserialize
$deserialized = $obj->thaw($serialized);

raw_serialize - serialize reference in raw form
$serialized = $obj->raw_serialize({a => [1,2,3],b => 5});

This is a straight pass through to the underlying serializer, nothing else is done. (no encoding, encryption, compression, etc)

raw_deserialize - deserialize reference in raw form
$deserialized = $obj->raw_deserialize($serialized);

This is a straight pass through to the underlying serializer, nothing else is done. (no encoding, encryption, compression, etc)

secret - specify secret for use with encryption
$obj->secret(mysecret);

Changes setting of secret for the Data::Serializer object. Can also be set in the constructor. If specified than the object will utilize encryption.

portable - encodes/decodes serialized data

Uses encoding method to ascii armor serialized data

Aids in the portability of serialized data.

compress - compression of data

Compresses serialized data. Default is not to use it. Will compress if set to a true value $obj->compress(1);

serializer - change the serializer

Currently have 8 supported serializers: Storable, FreezeThaw, Data::Denter, Config::General, YAML, PHP::Serialization, XML::Dumper, and Data::Dumper.
Default is to use Data::Dumper.

Each serializer has its own caveats about usage especially when dealing with cyclical data structures or CODE references. Please see the appropriate documentation in those modules for further information.

cipher - change the cipher method

Utilizes Crypt::CBC and can support any cipher method that it supports.

digester - change digesting method

Uses Digest so can support any digesting method that it supports. Digesting function is used internally by the encryption routine as part of data verification.

compressor - changes compresing module

This method is included for possible future inclusion of alternate compression method Currently Compress::Zlib is the only supported compressor.

encoding - change encoding method

Encodes data structure in ascii friendly manner. Currently the only valid options are hex, or b64.

The b64 option uses Base64 encoding provided by MIME::Base64, but strips out newlines.

serializer_token - add usage hint to data

Data::Serializer prepends a token that identifies what was used to process its data. This is used internally to allow runtime determination of how to extract Serialized data. Disabling this feature is not recommended.

options - pass options through to underlying serializer

Currently is only supported by Config::General, and XML::Dumper.

my $obj = Data::Serializer->new(serializer => Config::General,
options => {
-LowerCaseNames => 1,
-UseApacheInclude => 1,
-MergeDuplicateBlocks => 1,
-AutoTrue => 1,
-InterPolateVars => 1
},
) or die "$!n";

or

my $obj = Data::Serializer->new(serializer => XML::Dumper,
options => { dtd => 1, }
) or die "$!n";
store - serialize data and write it to a file (or file handle)
$obj->store({a => [1,2,3],b => 5},$file, [$mode, $perm]);

or

$obj->store({a => [1,2,3],b => 5},$fh);

Serializes the reference specified using the serialize method and writes it out to the specified file or filehandle.

If a file path is specified you may specify an optional mode and permission as the next two arguments. See IO::File for examples.

Trips an exception if it is unable to write to the specified file.

retrieve - read data from file (or file handle) and return it after deserialization

my $ref = $obj->retrieve($file);

or

my $ref = $obj->retrieve($fh);

Reads first line of supplied file or filehandle and returns it deserialized.

<<less
Download (0.025MB)
Added: 2007-07-12 License: Perl Artistic License Price:
834 downloads
MIDI Data Miner 3

MIDI Data Miner 3


MIDI Data Miner uses a neural network to learn correlations between notes and control changes in a MIDI file. more>>
MIDI Data Miner uses a neural network to learn correlations between notes and control changes in a MIDI file.

After training MDM can augment a live MIDI stream, adding control changes based on notes received.

Briefly: use MDM by connecting a MIDI device, open preferences and set MIDI input and output ports. Open a MIDI file, create a new neural net and train. Now play notes on your MIDI device, MDM will automatically add control changes.

MDM creates a collection of note and controller pairs from the file and uses them to train a net. The notes are used as inputs and the controls as outputs. The window is the number of previous notes considered when determining the output for the current note. Larger windows give less predictable more interesting responses. Enter a number in the window box and press enter to set the window size.

This is an early alpha release, buggy and incomplete. Please send feedback! Note that this alpha version only reads from the first track in a MIDI file, and only uses the first controller. Look at the included MIDI file in the working/midi folder for details.

<<less
Download (0.69MB)
Added: 2006-09-19 License: Free To Use But Restricted Price:
1131 downloads
Common Data Format 3.1

Common Data Format 3.1


Common Data Format is a self-describing data abstraction for the storage and manipulation of multidimensional data. more>>
Common Data Format is a self-describing data abstraction for the storage and manipulation of multidimensional data in a platform- and discipline-independent fashion.
It consists of a scientific data management package (known as the "CDF Library") that allows programmers and application developers to manage and manipulate scalar, vector, and multi-dimensional data arrays.
Enhancements:
- Adds new sets of APIs to allow Standard Interface to interact with zVariables and other CDF-related information.
- Adds MingW and FreeBSD ports.
- Adds support for Intel C++ and Fortran for Linux.
- Adds the ability to create legacy CDF 2.7 files.
- Fixes a bug that prevented directories from having .cdf or .skt extensions.
<<less
Download (1.5MB)
Added: 2006-03-13 License: Public Domain Price:
1320 downloads
Data::BenchmarkResults 0.01

Data::BenchmarkResults 0.01


Data::BenchmarkResults is a Perl extension for averaging and comparing multiple benchmark runs. more>>
Data::BenchmarkResults is a Perl extension for averaging and comparing multiple benchmark runs.

SYNOPSIS

use Data::BenchmarkResults;
$conditionA_results = new Data::BenchmarkResults;
$conditionB_results = new Data::BenchmarkResults;

#Load test result runs for the first condition
$conditionA_results->add_result_set("test1","run1",@data1);
$conditionA_results->add_result_set("test2","run1",@data2);
$conditionA_results->add_result_set("test1","run2",@data3);
$conditionA_results->add_result_set("test2","run2",@data4);

#Load test result runs for the second condition
$conditionB_results->add_result_set("test1","run1",@data5);
$conditionB_results->add_result_set("test2","run2",@data6);
$conditionB_results->add_result_set("test1","run1",@data7);
$conditionB_results->add_result_set("test2","run2",@data8);

#Average (mean average) the results of all the the runs of test1
# w/o tossing the highest and lowest values (replace the 0 with 1to
# toss the highest and lowest values

my $computed = $conditionA_results->process_result_set("test1","mean",0);
my $computed2 = $conditionB_results->process_result_set("test1","mean",0);

#OR process all of the tests at once (tossing the highest and lowest value) :

$conditionA_results->process_all_result_sets("mean",1);
$conditionB_results->process_all_result_sets("mean",1);


#Print out all of the processed test results
print "Condition A results.... nn"
$conditionA_results->print_calculated_sets;
print "Condition B results.... nn"
$conditionB_results->print_calculated_sets;


#Compare results of test1 of condition B against those with condition A
# as a percentage change from A to B

my $compared = $conditionB_results->compare_result_set($conditionA_results,"test1");

#OR compare all the processed test results from one condition to those of another
my $total_comparison = $conditionB_results->compare_all_result_sets($conditionA_results);

<<less
Download (0.009MB)
Added: 2007-08-16 License: Perl Artistic License Price:
799 downloads
Data::Dumper 2.121

Data::Dumper 2.121


Data::Dumper module contains stringified perl data structures, suitable for both printing and eval. more>>
Data::Dumper module contains stringified perl data structures, suitable for both printing and eval.

SYNOPSIS

use Data::Dumper;

# simple procedural interface
print Dumper($foo, $bar);

# extended usage with names
print Data::Dumper->Dump([$foo, $bar], [qw(foo *ary)]);

# configuration variables
{
local $Data::Dumper::Purity = 1;
eval Data::Dumper->Dump([$foo, $bar], [qw(foo *ary)]);
}

# OO usage
$d = Data::Dumper->new([$foo, $bar], [qw(foo *ary)]);
...
print $d->Dump;
...
$d->Purity(1)->Terse(1)->Deepcopy(1);
eval $d->Dump;

Given a list of scalars or reference variables, writes out their contents in perl syntax. The references can also be objects. The contents of each variable is output in a single Perl statement. Handles self-referential structures correctly.
The return value can be evaled to get back an identical copy of the original reference structure.

Any references that are the same as one of those passed in will be named $VARn (where n is a numeric suffix), and other duplicate references to substructures within $VARn will be appropriately labeled using arrow notation. You can specify names for individual values to be dumped if you use the Dump() method, or you can change the default $VAR prefix to something else. See $Data::Dumper::Varname and $Data::Dumper::Terse below.

The default output of self-referential structures can be evaled, but the nested references to $VARn will be undefined, since a recursive structure cannot be constructed using one Perl statement. You should set the Purity flag to 1 to get additional statements that will correctly fill in these references.
In the extended usage form, the references to be dumped can be given user-specified names. If a name begins with a *, the output will describe the dereferenced type of the supplied reference for hashes and arrays, and coderefs. Output of names will be avoided where possible if the Terse flag is set.

In many cases, methods that are used to set the internal state of the object will return the object itself, so method calls can be conveniently chained together.
Several styles of output are possible, all controlled by setting the Indent flag.

<<less
Download (0.031MB)
Added: 2007-07-02 License: Perl Artistic License Price:
853 downloads
Data::Password::Manager 0.02

Data::Password::Manager 0.02


Data::Password::Manager is a Perl module to generate, check, manage crypt - des passwords. more>>
Data::Password::Manager is a Perl module to generate, check, manage crypt - des passwords.

SYNOPSIS

use Data::Password::Manager qw(
pw_gen
pw_valid
pw_obscure
pw_clean
pw_get
);

$password = pw_gen($cleartext);
$ok = pw_valid($cleartxt,$password);
$clean_text = pw_clean($dirty_text);
($code,$text) = $pw_obscure($newpass,$oldpass,$min_len);
$passwd = pw_get($user,$passwd_file,$error);

$password = pw_gen($cleartext);
Generate a 13 character DES password string from clear text
input: string<<less
Download (0.013MB)
Added: 2007-02-20 License: Perl Artistic License Price:
978 downloads
Data::PropertyList 1998.1217

Data::PropertyList 1998.1217


Data::PropertyList is a Perl module that can convert arbitrary objects to/from strings. more>>
Data::PropertyList is a Perl module that can convert arbitrary objects to/from strings.

SYNOPSIS

use Data::PropertyList qw(astext fromtext);

$hash_ref = { items => [ 7 .. 11 ], key => value };
$string = astext($hash_ref);
# ...
$hash_ref = fromtext($string);
print $hash_ref->{items}[0];

$array_ref = [ 1, { key => value }, Omega ];
$string = astext($array_ref);
# ...
$array_ref = fromtext($string, -array=>1 );
print $array_ref->[1]{key};

Data::Propertylist provides functions that turn data structures with nested references into NeXTs Property List text format and back again.

You may find this useful for saving and loading application information in text files, or perhaps for generating error messages while debugging.

astext( $reference ) : $propertylist_string;

Writes out a nested Perl data structure in NeXT property list format.

fromtext( $propertylist_string ) : $hash_ref

fromtext( $propertylist_string, -array=>1 ) : $array_ref

Reconstructs a Perl data structure of nested references and scalars from a NeXT property list. Use the -array flag if the string encodes an array rather than a hash.

<<less
Download (0.008MB)
Added: 2006-08-17 License: Perl Artistic License Price:
1163 downloads
Data Display Debugger 3.3.11

Data Display Debugger 3.3.11


Data Display Debugger is a common graphical user interface for GDB, DBX and XDB. more>>
GNU DDD is a graphical front-end for command-line debuggers such as GDB, DBX, WDB, Ladebug, JDB, XDB, the Perl debugger, the bash debugger, or the Python debugger.

Besides "usual front-end features such as viewing source texts, DDD has become famous through its interactive graphical data display, where data structures are displayed as graphs.
<<less
Download (7.3MB)
Added: 2005-04-18 License: GPL (GNU General Public License) Price:
1661 downloads
Data::Locations 5.4

Data::Locations 5.4


Data::Locations is a virtual file manager which allows to read/write data to and from virtual files. more>>
Data::Locations - magic insertion points in your data
Did you already encounter the problem that you had to produce some data in a particular order, but that some piece of the data was still unavailable at the point in the sequence where it belonged and where it should have been produced?
Did you also have to resort to cumbersome and tedious measures such as storing the first and the last part of your data separately, then producing the missing middle part, and finally putting it all together?
In this simple case, involving only one deferred insertion, you might still put up with this solution.
But if there is more than one deferred insertion, requiring the handling of many fragments of data, you will probably get annoyed and frustrated.
You might even have to struggle with limitations of the file system of your operating system, or handling so many files might considerably slow down your application due to excessive file input/output.
And if you dont know exactly beforehand how many deferred insertions there will be (if this depends dynamically on the data being processed), and/or if the pieces of data you need to insert need additional (nested) insertions themselves, things will get really tricky, messy and troublesome.
In such a case you might wonder if there wasnt an elegant solution to this problem.
This is where the "Data::Locations" module comes in: It handles such insertion points automatically for you, no matter how many and how deeply nested, purely in memory, requiring no (inherently slower) file input/output operations.
(The underlying operating system will automatically take care if the amount of data becomes too large to be handled fully in memory, though, by swapping out unneeded parts.)
Moreover, it also allows you to insert the same fragment of data into SEVERAL different places.
This increases space efficiency because the same data is stored in memory only once, but used multiple times.
Potential infinite recursion loops are detected automatically and refused.
In order to better understand the underlying concept, think of "Data::Locations" as virtual files with almost random access: You can write data to them, you can say "reserve some space here which I will fill in later", and continue writing data.
And you can of course also read from these virtual files, at any time, in order to see the data that a given virtual file currently contains.
When you are finished filling in all the different parts of your virtual file, you can write out its contents in flattened form to a physical, real file this time, or process it otherwise (purely in memory, if you wish).
You can also think of "Data::Locations" as bubbles and bubbles inside of other bubbles. You can inflate these bubbles in any arbitrary order you like through a straw (i.e., the bubbles object reference).
Note that this module handles your data completely transparently, which means that you can use it equally well for text AND binary data.
You might also be interested in knowing that this module and its concept have already been heavily used in the automatic code generation of large software projects.
Enhancements:
- Fixed test file "02___refcount.t" to auto-adjust the offset dealing with self-ties not incrementing
- the refcount in some Perl versions.
- Added a warning to "Makefile.PL" that Perl versions including and between v5.6.1 and v5.7.0 are not fully supported (test file "11_______dump.t" dumps core).
<<less
Download (0.043MB)
Added: 2005-04-29 License: Artistic License Price:
1638 downloads
Data::Generate 0.01

Data::Generate 0.01


Data::Generate allows you to create various types of synthetic data by parsing regex-like data creation rules. more>>
Data::Generate allows you to create various types of synthetic data by parsing "regex-like" data creation rules.

This module generates data by parsing given text statements (data creation rules). These statements are flexible and powerful regex-like way to control the production of synthetic data. Think about a program that instead of selecting data which matches a regex filter expression, produces it. For example, from the rule [a-c], the generator would produce the array a,b,c. The module works as following:

Specify data creation rules.
my $generator= Data::Generate::parse(VC(24) [0-9][2-3]);
At this step first you define one kind of output datatype (for ex. VC(24)= "output is a string with max length 24") and then with the rest of the expression define what it should look like. If parsing is successful a Data Generator object is instantiated.

Get data
my $Data= $generator->get_unique_data(10);
To really get the data, users must call the get_unique_data method by indicating the desired number of output values. The generator returns the values contained in an array reference. Please remark that output format is fixed according to the data type.

<<less
Download (0.025MB)
Added: 2007-03-31 License: Perl Artistic License Price:
937 downloads
Local Data Manager 6.6.5

Local Data Manager 6.6.5


Local Data Manager is a collection of cooperating programs that select, capture, manage, and distribute arbitrary data products. more>>
Local Data Manager (LDM) is a collection of cooperating programs that select, capture, manage, and distribute arbitrary data products.
The system is designed for event-driven data distribution, and is currently used in the Unidata Internet Data Distribution (IDD) project. The LDM system includes network client and server programs and their shared protocols.
An important characteristic of the LDM is its support for flexible, site-specific configuration.
Enhancements:
- Fixes for timestamp bugs.
<<less
Download (0.61MB)
Added: 2007-08-09 License: BSD License Price:
809 downloads
Data::Page 2.00

Data::Page 2.00


Data::Page is a Perl module that helps when paging through sets of results. more>>
Data::Page is a Perl module that helps when paging through sets of results.

SYNOPSIS

use Data::Page;

my $page = Data::Page->new();
$page->total_entries($total_entries);
$page->entries_per_page($entries_per_page);
$page->current_page($current_page);

print " First page: ", $page->first_page, "n";
print " Last page: ", $page->last_page, "n";
print "First entry on page: ", $page->first, "n";
print " Last entry on page: ", $page->last, "n";

When searching through large amounts of data, it is often the case that a result set is returned that is larger than we want to display on one page. This results in wanting to page through various pages of data. The maths behind this is unfortunately fiddly, hence this module.

The main concept is that you pass in the number of total entries, the number of entries per page, and the current page number. You can then call methods to find out how many pages of information there are, and what number the first and last entries on the current page really are.

For example, say we wished to page through the integers from 1 to 100 with 20 entries per page. The first page would consist of 1-20, the second page from 21-40, the third page from 41-60, the fourth page from 61-80 and the fifth page from 81-100. This module would help you work this out.

<<less
Download (0.006MB)
Added: 2006-10-31 License: Perl Artistic License Price:
1088 downloads
Data::Page::Viewport 1.02

Data::Page::Viewport 1.02


Data::Page::Viewport is a Perl module to scroll thru data a page, or just an item, at a time. more>>
Data::Page::Viewport is a Perl module to scroll thru data a page, or just an item, at a time.

Synopsis

This is a complete, tested, runnable program.
#!/usr/bin/perl

use strict;
use warnings;

use Data::Page::Viewport;

# -----------------------------------------------

my(@data) = (qw/zero one two three four five six
seven eight nine ten eleven twelve thirteen fourteen/);
my($page) = Data::Page::Viewport -> new
(
data_size => scalar @data,
page_size => 4
);

print "Data bounds: 0 .. $#data. n";
print "Data: ", join(, , @data), ". n";
print "Page bounds: 0 .. 3. n";
print "Page data: ", join(, , @data[0 .. 3]), ". n";
print "n";

my(@bound);

for (-2, 1, 4, 4, 1, 3, 3, -2, 1, 2, 1, -4, -4,
-1, 1, 2, -1, -2, -2, -1, -4, 4, 4, 4)
{
print "Offset: $_. n";

@bound = $page -> offset($_) -> bounds();

print "Page bounds: $bound[0] .. $bound[1]. n";
print Page data: ,
join(, , @data[$bound[0] .. $bound[1] ]),
". n";
print - x 50, "n";
}

Data::Page::Viewport is a pure Perl module.

This module keeps track of what items are on the current page, when you scroll forwards or backwards within a data set.

Similarly to Data::Page, you can call sub offset(N), for + or - N, to scroll thru the data a page at a time.

And, like Set::Window, you can call sub offset(N), for + or - 1, to scroll thru the data an item at a time.

Clearly, N does not have to be fixed.

The viewport provides access to the current page, and the code shifts indexes into and out of the viewport, according to the parameter passed to sub offset().

Note that the data is not passed into this module. The module only keeps track of the indexes within the viewport, i.e. indexes on the current page.

You call sub bounds() on the object (of type Set::Window) returned by sub offset(), to determine what indexes are on the current page at any particular point in time.

Also note that, unlike Set::Window, the boundaries of the viewport are rigid, so that changes to the indexes caused by sub offset() are limited by the size of the data set.

This means, if you do this:

my($page) = Data::Page::Viewport -> new
(
data_size => $#data, # 0 .. $#data.
page_size => $page_size, # 1 .. N.
);

my(@bound) = $page -> offset(- 1) -> bounds();

the call to sub offset(- 1) will have no effect.

That is, when trying to go back past the beginning of the data set, the bounds will be locked to values within 0 .. data_size.

Similarly, a call which would go beyond the other end of the data set, will lock the bounds to the same range.

In short, you cant fall off the edge by calling sub offset().

This in turn means that the values returned by sub bounds() will always be valid indexes within the range 0 .. data_size.

The module implements this by building 2 objects of type Set::Window, one for the original data set (which never changes), and one for the current page, which changes each time sub offset() is called (until the boundaries are hit, of course).

Note: No range checking is performed on the parameters to sub new().

Note: It should be obvious by now that this module differs from Data::Page, and indeed all such modules, in that they never change the items which are on a given page. They only allow you to change the page known as the current page. This module differs, in that, by calling sub offset(+ or - N), you are effectively changing the items which are deemed to be on the current page.

<<less
Download (0.008MB)
Added: 2006-10-03 License: Perl Artistic License Price:
1117 downloads
Secure Data Manager 2.1.0

Secure Data Manager 2.1.0


Secure Data Manager is a manager for passwords and other private data. more>>
Secure Data Manager project is a manager for passwords and other private data.
Secure Data Manager (SDM) is a full-featured password manager application written entirely in Java (so it can run on Unix or Windows). It encrypts logins and other private information for Web sites, computers, credit cards, etc.
Main features:
- Many great features and more coming each month based on user feedback!
- No limit to how you use the product or how often!
- Trusted since you and everyone else can see the code that protects your passwords -- keeping the application clear of any trojans or bad business practices.
- Open source -- so if you know how to write code, you can add any feature you want!
- Free.
<<less
Download (1.9MB)
Added: 2007-01-18 License: GPL (GNU General Public License) Price:
1012 downloads
Secleted [ 0 ] software to compare
  • Page: 1 of 5
  • 1
  • 2
  • 3
  • 4
  • 5