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Fast Data Transfer 0.8.0
Fast Data Transfer is an application for efficient data transfers that is capable of reading and writing at disk speed. more>>
Fast Data Transfer is an application for efficient data transfers that is capable of reading and writing at disk speed over wide area networks (with standard TCP).
It can be used to stream a large set of files across the network, so a large dataset composed of thousands of files can be sent or received at full speed, without the network transfer restarting between files.
The project is written in Java, runs an all major platforms, and is easy to use.
Main features:
- Streams a dataset (list of files) continuously, using a managed pool of buffers through one or more TCP sockets.
- Uses independent threads to read and write on each physical device
- Transfers data in parallel on multiple TCP streams, when necessary
- Uses appropriate-sized buffers for disk I/O and for the network
- Restores the files from buffers asynchronously
- Resumes a file transfer session without loss, when needed
<<lessIt can be used to stream a large set of files across the network, so a large dataset composed of thousands of files can be sent or received at full speed, without the network transfer restarting between files.
The project is written in Java, runs an all major platforms, and is easy to use.
Main features:
- Streams a dataset (list of files) continuously, using a managed pool of buffers through one or more TCP sockets.
- Uses independent threads to read and write on each physical device
- Transfers data in parallel on multiple TCP streams, when necessary
- Uses appropriate-sized buffers for disk I/O and for the network
- Restores the files from buffers asynchronously
- Resumes a file transfer session without loss, when needed
Download (0.35MB)
Added: 2007-08-21 License: Other/Proprietary License Price:
797 downloads
Simple File Transfer 0.4.14
Simple File Transfer is a pure useless program which allows you exchange files with remote computers via Internet. more>>
Simple File Transfer is a pure useless program which allows you exchange files with remote computers via Internet. This program has been written for personnal use, so dont blame me if you think I am stupid doing such tool for the others.
It should run on every POSIX compliant Operating System, but I cant give you any complete list.
If you want to compile it under *BSD, maybe youll have to disable the uname() call by running the configure script with the --with-uname=no option.
Enhancements:
- Added the support of hostnames for the destination server
<<lessIt should run on every POSIX compliant Operating System, but I cant give you any complete list.
If you want to compile it under *BSD, maybe youll have to disable the uname() call by running the configure script with the --with-uname=no option.
Enhancements:
- Added the support of hostnames for the destination server
Download (0.088MB)
Added: 2006-08-01 License: GPL (GNU General Public License) Price:
1186 downloads
Apple Disk Transfer ProDOS 1.0.2
Apple Disk Transfer ProDOS transfers diskettes and logical disk images between Apple ][-era computers and the modern world. more>>
Apple Disk Transfer ProDOS (or ADTPro for short) transfers diskettes and logical disk images between Apple ][-era computers and the modern world. If youre familiar with the original ADT, ADTPro extends ADTs reach by working with more logical disk formats, drive types, communications devices, and host operating systems.
Main features:
- Compatibility with any device ProDOS can read
- Compatibility with any Apple ][ (or clone) computer with 64k memory
- Compatibility with many logical disk image formats: .DSK, .PO, .NIB, 2IMG
- Server compatibility with original ADT client program
- Server compatibility with Windows, Mac OSX, Linux, and probably Solaris
- Ability to bootstrap an Apple ][ from bare metal over serial or cassette ports
- Ability to send floppies in "batch" mode without having to name each one
Server
The server program runs on a computer capable of running Java. Depending on how you want to connect to your Apple, you might also need a serial port and cables, an Uthernet card for your apple, or a couple of audio patch cables. The server offers a compact user interface that shows what communications are taking place between the host and the Apple ][.
The servers primary role is to send and receive disk images as requested from the client. But if you have recently acquired an Apple and a disk drive, and you have no software for it - youre in a bit of a tricky situation if you want to move software from the Internet all the way to your shiny new Apple. ADTPros server can help get you get bootstrapped.
Client
The client side runs on the Apple ][. It handles most of the user interaction. When choosing disks/volumes to transfer, anything that ProDOS can see is fair game. Transferring data occurs with a 20k buffer on the Apple, so all transfers are broken up into 20k chunks. A progress indicator shows how far it is into the current chunk, as well as a running count of the total progress.
Enhancements:
- This release has been enhanced with Jean-Marc Boutillon (Deckard)s FASTDSK fast Disk II reading routines.
- This results in a speed boost of 25%-33% for Disk II to host transfers.
- Bootstrapping operations have been reduced, as there is no longer a dependency on ProDOS BASIC.
<<lessMain features:
- Compatibility with any device ProDOS can read
- Compatibility with any Apple ][ (or clone) computer with 64k memory
- Compatibility with many logical disk image formats: .DSK, .PO, .NIB, 2IMG
- Server compatibility with original ADT client program
- Server compatibility with Windows, Mac OSX, Linux, and probably Solaris
- Ability to bootstrap an Apple ][ from bare metal over serial or cassette ports
- Ability to send floppies in "batch" mode without having to name each one
Server
The server program runs on a computer capable of running Java. Depending on how you want to connect to your Apple, you might also need a serial port and cables, an Uthernet card for your apple, or a couple of audio patch cables. The server offers a compact user interface that shows what communications are taking place between the host and the Apple ][.
The servers primary role is to send and receive disk images as requested from the client. But if you have recently acquired an Apple and a disk drive, and you have no software for it - youre in a bit of a tricky situation if you want to move software from the Internet all the way to your shiny new Apple. ADTPros server can help get you get bootstrapped.
Client
The client side runs on the Apple ][. It handles most of the user interaction. When choosing disks/volumes to transfer, anything that ProDOS can see is fair game. Transferring data occurs with a 20k buffer on the Apple, so all transfers are broken up into 20k chunks. A progress indicator shows how far it is into the current chunk, as well as a running count of the total progress.
Enhancements:
- This release has been enhanced with Jean-Marc Boutillon (Deckard)s FASTDSK fast Disk II reading routines.
- This results in a speed boost of 25%-33% for Disk II to host transfers.
- Bootstrapping operations have been reduced, as there is no longer a dependency on ProDOS BASIC.
Download (MB)
Added: 2007-08-13 License: GPL (GNU General Public License) Price:
816 downloads
Upstream Log Transfer System 0.2.0
Upstream is a collection of tools that allow users to send in system specific log and troubleshooting data to support personnel. more>>
Upstream is a collection of tools that allow users to send in system specific log and troubleshooting data to support personnel. The project can be easily modified to output data to any pastebin or support tracker.
Upstream aims to simplify the support cycle and make it more efficient. One of the main problems that support staff face when helping people via IRC or mailing lists is getting user log files across.
Often this process is time consuming, and many new users may even be unable to find / copy these logs. Upstream does this for them by finding and transmitting the log files relevant to a specific issue.
Usage:
We hope to turn this,
< newuser >hi, something is wrong with my resolution, how can i fix it?
< support_person >newuser, what is your video card, and which driver is xorg using?
< newuser >err... how can i find out?
< support_person > cat /var/log/Xorg.0.log and pastebin it
< newuser >pastebin?
< support_person >http://pastebin.ca
< newuser >how do i copy? it wont copy!
In to this,
< newuser >hi, something is wrong with my resolution, how can i fix it?
< support_person >newuser, please run Canoe (System -> Help -> Canoe) and choose Video support. Give me the url you get once its done.
<<lessUpstream aims to simplify the support cycle and make it more efficient. One of the main problems that support staff face when helping people via IRC or mailing lists is getting user log files across.
Often this process is time consuming, and many new users may even be unable to find / copy these logs. Upstream does this for them by finding and transmitting the log files relevant to a specific issue.
Usage:
We hope to turn this,
< newuser >hi, something is wrong with my resolution, how can i fix it?
< support_person >newuser, what is your video card, and which driver is xorg using?
< newuser >err... how can i find out?
< support_person > cat /var/log/Xorg.0.log and pastebin it
< newuser >pastebin?
< support_person >http://pastebin.ca
< newuser >how do i copy? it wont copy!
In to this,
< newuser >hi, something is wrong with my resolution, how can i fix it?
< support_person >newuser, please run Canoe (System -> Help -> Canoe) and choose Video support. Give me the url you get once its done.
Download (0.11MB)
Added: 2006-12-13 License: GPL (GNU General Public License) Price:
1045 downloads
Data::CTable 1.03
Data::CTable is a Perl module that helps you read, write, manipulate tabular data. more>>
Data::CTable is a Perl module that helps you read, write, manipulate tabular data.
SYNOPSIS
## Read some data files in various tabular formats
use Data::CTable;
my $People = Data::CTable->new("people.merge.mac.txt");
my $Stats = Data::CTable->new("stats.tabs.unix.txt");
## Clean stray whitespace in fields
$People->clean_ws();
$Stats ->clean_ws();
## Retrieve columns
my $First = $People->col(FirstName);
my $Last = $People->col(LastName );
## Calculate a new column based on two others
my $Full = [map {"$First->[$_] $Last->[$_]"} @{$People->all()}];
## Add new column to the table
$People->col(FullName => $Full);
## Another way to calculate a new column
$People->col(Key);
$People->calc(sub {no strict vars; $Key = "$Last,$First";});
## "Left join" records matching Stats:PersonID to People:Key
$Stats->join($People, PersonID => Key);
## Find certain records
$Stats->select_all();
$Stats->select(Department => sub {/Sale/i }); ## Sales depts
$Stats->omit (Department => sub {/Resale/i}); ## not Resales
$Stats->select(UsageIndex => sub {$_ > 20.0}); ## high usage
## Sort the found records
$Stats->sortspec(DeptNum , {SortType => Integer});
$Stats->sortspec(UsageIndex, {SortType => Number });
$Stats->sort([qw(DeptNum UsageIndex Last First)]);
## Make copy of table with only found/sorted data, in order
my $Report = $Stats->snapshot();
## Write an output file
$Report->write(_FileName => "Rept.txt", _LineEnding => "mac");
## Print a final progress message.
$Stats->progress("Done!");
## Dozens more methods and parameters available...
OVERVIEW
Data::CTable is a comprehensive utility for reading, writing, manipulating, cleaning and otherwise transforming tabular data. The distribution includes several illustrative subclasses and utility scripts.
A Columnar Table represents a table as a hash of data columns, making it easy to do data cleanup, formatting, searching, calculations, joins, or other complex operations.
The objects hash keys are the field names and the hash values hold the data columns (as array references).
Tables also store a "selection" -- a list of selected / sorted record numbers, and a "field list" -- an ordered list of all or some fields to be operated on. Select() and sort() methods manipulate the selection list. Later, you can optionally rewrite the table in memory or on disk to reflect changes in the selection list or field list.
Data::CTable reads and writes any tabular text file format including Merge, CSV, Tab-delimited, and variants. It transparently detects, reads, and preserves Unix, Mac, and/or DOS line endings and tab or comma field delimiters -- regardless of the runtime platform.
In addition to reading data files, CTable is a good way to gather, store, and operate on tabular data in memory, and to export data to delimited text files to be read by other programs or interactive productivity applications.
To achieve extremely fast data loading, CTable caches data file contents using the Storable module. This can be helpful in CGI environments or when operating on very large data files. CTable can read an entire cached table of about 120 megabytes into memory in about 10 seconds on an average mid-range computer.
For simple data-driven applications needing to store and quickly retrieve simple tabular data sets, CTable provides a credible alternative to DBM files or SQL.
For data hygiene applications, CTable forms the foundation for writing utility scripts or compilers to transfer data from external sources, such as FileMaker, Excel, Access, personal organizers, etc. into compiled or validated formats -- or even as a gateway to loading data into SQL databases or other destinations. You can easily write short, repeatable scripts in Perl to do reporting, error checking, analysis, or validation that would be hard to duplicate in less-flexible application environments.
The data representation is simple and open so you can directly access the data in the object if you feel like it -- or you can use accessors to request "clean" structures containing only the data or copies of it. Or you can build your own columns in memory and then when youre ready, turn them into a table object using the very flexible new() method.
The highly factored interface and implementation allow fine-grained subclassing so you can easily create useful lightweight subclasses. Several subclasses are included with the distribution.
Most defaults and parameters can be customized by subclassing, overridden at the instance level (avoiding the need to subclass too often), and further overridden via optional named-parameter arguments to most major method calls.
<<lessSYNOPSIS
## Read some data files in various tabular formats
use Data::CTable;
my $People = Data::CTable->new("people.merge.mac.txt");
my $Stats = Data::CTable->new("stats.tabs.unix.txt");
## Clean stray whitespace in fields
$People->clean_ws();
$Stats ->clean_ws();
## Retrieve columns
my $First = $People->col(FirstName);
my $Last = $People->col(LastName );
## Calculate a new column based on two others
my $Full = [map {"$First->[$_] $Last->[$_]"} @{$People->all()}];
## Add new column to the table
$People->col(FullName => $Full);
## Another way to calculate a new column
$People->col(Key);
$People->calc(sub {no strict vars; $Key = "$Last,$First";});
## "Left join" records matching Stats:PersonID to People:Key
$Stats->join($People, PersonID => Key);
## Find certain records
$Stats->select_all();
$Stats->select(Department => sub {/Sale/i }); ## Sales depts
$Stats->omit (Department => sub {/Resale/i}); ## not Resales
$Stats->select(UsageIndex => sub {$_ > 20.0}); ## high usage
## Sort the found records
$Stats->sortspec(DeptNum , {SortType => Integer});
$Stats->sortspec(UsageIndex, {SortType => Number });
$Stats->sort([qw(DeptNum UsageIndex Last First)]);
## Make copy of table with only found/sorted data, in order
my $Report = $Stats->snapshot();
## Write an output file
$Report->write(_FileName => "Rept.txt", _LineEnding => "mac");
## Print a final progress message.
$Stats->progress("Done!");
## Dozens more methods and parameters available...
OVERVIEW
Data::CTable is a comprehensive utility for reading, writing, manipulating, cleaning and otherwise transforming tabular data. The distribution includes several illustrative subclasses and utility scripts.
A Columnar Table represents a table as a hash of data columns, making it easy to do data cleanup, formatting, searching, calculations, joins, or other complex operations.
The objects hash keys are the field names and the hash values hold the data columns (as array references).
Tables also store a "selection" -- a list of selected / sorted record numbers, and a "field list" -- an ordered list of all or some fields to be operated on. Select() and sort() methods manipulate the selection list. Later, you can optionally rewrite the table in memory or on disk to reflect changes in the selection list or field list.
Data::CTable reads and writes any tabular text file format including Merge, CSV, Tab-delimited, and variants. It transparently detects, reads, and preserves Unix, Mac, and/or DOS line endings and tab or comma field delimiters -- regardless of the runtime platform.
In addition to reading data files, CTable is a good way to gather, store, and operate on tabular data in memory, and to export data to delimited text files to be read by other programs or interactive productivity applications.
To achieve extremely fast data loading, CTable caches data file contents using the Storable module. This can be helpful in CGI environments or when operating on very large data files. CTable can read an entire cached table of about 120 megabytes into memory in about 10 seconds on an average mid-range computer.
For simple data-driven applications needing to store and quickly retrieve simple tabular data sets, CTable provides a credible alternative to DBM files or SQL.
For data hygiene applications, CTable forms the foundation for writing utility scripts or compilers to transfer data from external sources, such as FileMaker, Excel, Access, personal organizers, etc. into compiled or validated formats -- or even as a gateway to loading data into SQL databases or other destinations. You can easily write short, repeatable scripts in Perl to do reporting, error checking, analysis, or validation that would be hard to duplicate in less-flexible application environments.
The data representation is simple and open so you can directly access the data in the object if you feel like it -- or you can use accessors to request "clean" structures containing only the data or copies of it. Or you can build your own columns in memory and then when youre ready, turn them into a table object using the very flexible new() method.
The highly factored interface and implementation allow fine-grained subclassing so you can easily create useful lightweight subclasses. Several subclasses are included with the distribution.
Most defaults and parameters can be customized by subclassing, overridden at the instance level (avoiding the need to subclass too often), and further overridden via optional named-parameter arguments to most major method calls.
Download (0.15MB)
Added: 2007-07-13 License: Perl Artistic License Price:
833 downloads
Fast Icon Users for Linux -
User icons with functions like: add, chat, edit, offline, remove, send, upload more>> Description:
11 icons of users.
Content:
User icons with functions like: add, chat, edit, offline, remove, send, upload, user, user group, video chat, voice chat<<less
Download (313KB)
Added: 2009-04-04 License: Freeware Price:
211 downloads
GNOME Transfer Manager 0.4.12
GNOME Transfer Manager allows the user to retrieve multiple files from the web. more>>
GNOME Transfer Manager allows the user to retrieve multiple files from the web.
These files can be retrieved in multiple parts and each part retrieved on a separate session that the user is connected to the Internet. This is most useful to users with dialup connections. The program performs these tasks using wget as its back-end.
The program supports CORBA. This makes it easy for other programs to use GTransferManager to handle the transfer of files from the Internet.
The program also has an applet which communicates with program using CORBA. The applet can launch the program, request for a new download or accept drops of URLs from netscape, gFTP, gmc and give these URLs to GTM.
<<lessThese files can be retrieved in multiple parts and each part retrieved on a separate session that the user is connected to the Internet. This is most useful to users with dialup connections. The program performs these tasks using wget as its back-end.
The program supports CORBA. This makes it easy for other programs to use GTransferManager to handle the transfer of files from the Internet.
The program also has an applet which communicates with program using CORBA. The applet can launch the program, request for a new download or accept drops of URLs from netscape, gFTP, gmc and give these URLs to GTM.
Download (0.48MB)
Added: 2006-07-12 License: GPL (GNU General Public License) Price:
1208 downloads
DataDraw 3.0.7
DataDraw is an ultra-fast persistent database for high performance programs written in C. more>>
DataDraw is an ultra-fast persistent database for high performance programs written in C. The DataDraw project is so fast that many programs keep all their data in a DataDraw database, even while being manipulated in inner loops of compute intensive applications.
Unlike slow SQL databases, DataDraw databases are compiled, and directly link into your C programs. DataDraw databases are resident in memory, making data manipulation even faster than if they were stored in native C data structures (really).
DataDraw databases can be persistent.
Modifications to persistent data are written to disk as they are made, which of course dramatically slows write times. However, DataDraw databases can also be volatile. Volatile databases exist only in memory, and only for the duration that your program needs it. Volatile databases can be directly manipulated faster than C structures, since data is better organized in memory to optimize cache performance.
DataDraw supports modular design. An application can have one or more common persistent databases, and multiple volatile databases to support various tools data structures. Classes in a tools database can extend classes in the common database.
DataDraw is also 64-bit optimized, allowing programs to run much faster and in less memory than standard C programs using 64-bit pointers. This is because DataDraw databases supports over 4 billion objects of a given class with 32-bit object references.
DataDraw is released under the GNU Library General Public License, Version 2. It costs you nothing to use, and does not restrict your application in any way. Only the DataDraw program itself is covered by the license.
When to use DataDraw vs MySQL and PHP
LAMP is a very powerful combination for creating web applications: Linux, Apache, MySQL, and PHP. Apache provides an incredibly powerful framework built around a world-class web server. PHP provides a powerful language for developing web applications rapidly. MySQL provides a way for these web applications to manage data. DataDraw is not meant to replace any of this.
However, Apache is bloated, PHP is a slow interpreted language, and MySQL interprets ASCII commands that it reads through sockets that communicate with PHP. All this slows the system down 100-1000X, relative to plain old C code. Most applications dont care: if Im just trying to sell stuff over the Internet, being able to process even one transaction per second is probably fine.
DataDraw is for demanding applications for which LAMP is too slow and/or bloated. While running, a DataDraw application owns the database, and does not share it with others. That makes it well suited for implementing some tasks, and not others. For example, it is well suited for building SQL servers, or BitTorrent trackers, and embedded servers, but not well suited for Apache modules. In these cases, consider embedding both DataDraw, and a free, fast, tiny HTML server, such as the MiniWeb HTTP server, directly in your application. This will allow you to serve many times more requests per second, in far less memory..
Installation:
DataDraw3.0 is under heavy development, so it is wise to download and compile it directly from source. Use subversion like this:
$ svn co https://svn.sourceforge.net/svnroot/datadraw/trunk datadraw
Then, just switch to the datadraw directory, and type:
$ makemake
$make
This should create a datadraw executable. To figure out how to use it, read the manual, found in "manual.odt".
<<lessUnlike slow SQL databases, DataDraw databases are compiled, and directly link into your C programs. DataDraw databases are resident in memory, making data manipulation even faster than if they were stored in native C data structures (really).
DataDraw databases can be persistent.
Modifications to persistent data are written to disk as they are made, which of course dramatically slows write times. However, DataDraw databases can also be volatile. Volatile databases exist only in memory, and only for the duration that your program needs it. Volatile databases can be directly manipulated faster than C structures, since data is better organized in memory to optimize cache performance.
DataDraw supports modular design. An application can have one or more common persistent databases, and multiple volatile databases to support various tools data structures. Classes in a tools database can extend classes in the common database.
DataDraw is also 64-bit optimized, allowing programs to run much faster and in less memory than standard C programs using 64-bit pointers. This is because DataDraw databases supports over 4 billion objects of a given class with 32-bit object references.
DataDraw is released under the GNU Library General Public License, Version 2. It costs you nothing to use, and does not restrict your application in any way. Only the DataDraw program itself is covered by the license.
When to use DataDraw vs MySQL and PHP
LAMP is a very powerful combination for creating web applications: Linux, Apache, MySQL, and PHP. Apache provides an incredibly powerful framework built around a world-class web server. PHP provides a powerful language for developing web applications rapidly. MySQL provides a way for these web applications to manage data. DataDraw is not meant to replace any of this.
However, Apache is bloated, PHP is a slow interpreted language, and MySQL interprets ASCII commands that it reads through sockets that communicate with PHP. All this slows the system down 100-1000X, relative to plain old C code. Most applications dont care: if Im just trying to sell stuff over the Internet, being able to process even one transaction per second is probably fine.
DataDraw is for demanding applications for which LAMP is too slow and/or bloated. While running, a DataDraw application owns the database, and does not share it with others. That makes it well suited for implementing some tasks, and not others. For example, it is well suited for building SQL servers, or BitTorrent trackers, and embedded servers, but not well suited for Apache modules. In these cases, consider embedding both DataDraw, and a free, fast, tiny HTML server, such as the MiniWeb HTTP server, directly in your application. This will allow you to serve many times more requests per second, in far less memory..
Installation:
DataDraw3.0 is under heavy development, so it is wise to download and compile it directly from source. Use subversion like this:
$ svn co https://svn.sourceforge.net/svnroot/datadraw/trunk datadraw
Then, just switch to the datadraw directory, and type:
$ makemake
$make
This should create a datadraw executable. To figure out how to use it, read the manual, found in "manual.odt".
Download (0.26MB)
Added: 2007-01-10 License: GPL (GNU General Public License) Price:
1019 downloads
Parallel Three-Dimensional Fast Fourier Transforms 2.1
Parallel Three-Dimensional Fast Fourier Transforms is a library for computational computing in a wide range of sciences. more>>
Parallel Three-Dimensional Fast Fourier Transforms, dubbed P3DFFT, is a library for computational computing in a wide range of sciences, such as physics, climatology, chemistry.
This project was developed at SDSC by Dmitry Pekurovsky as a product of a Strategic Applications Collaborations (SAC) project.
Main features:
- Parallel implementation with 2D data decomposition, overcoming an important limitation to scalability of other 3D FFT libraries implementing 1D, or slab, decomposition.
- Optimized for parallel communication and single-CPU performance.
- Built on top of well-optimized and flexible 1D FFT libraries.
Enhancements:
- Assorted minor bugfixes and code speedups.
<<lessThis project was developed at SDSC by Dmitry Pekurovsky as a product of a Strategic Applications Collaborations (SAC) project.
Main features:
- Parallel implementation with 2D data decomposition, overcoming an important limitation to scalability of other 3D FFT libraries implementing 1D, or slab, decomposition.
- Optimized for parallel communication and single-CPU performance.
- Built on top of well-optimized and flexible 1D FFT libraries.
Enhancements:
- Assorted minor bugfixes and code speedups.
Download (MB)
Added: 2007-06-07 License: GPL (GNU General Public License) Price:
869 downloads
Data::Region 1.0
Data::Region Perl module can define hierarchical areas with behaviors. more>>
Data::Region Perl module can define hierarchical areas with behaviors.
SYNOPSIS
use Data::Region;
$r = Data::Region->new( 8.5, 11, { data => PageObj->new() } );
$r->data( PageObj->new() );
foreach my $c ( $r->subdivide(2.5,3) ) {
$a = $c->area(0.25,0.25, 2.25,2.75);
$a2 = $c->area(0.25,0.25, -0.25,-0.25); # as offset from lower right
($t,$m,$b) = $a->split_vertical(2,5,1); # sequential heights
($t,$m,$b) = $a->split_vertical_abs(0,2,7); # absolute offsets
($l,$r) = $a->split_horizontal(2); # $l gets width of 2, $r gets the rest
my($x1,$y1,$x2,$y2) = $a->coords();
my $data = $a->data(); # data inherits from parent, if not set
$a->action( sub { $data->setfont("Times-Bold", 10);
$data->text($x1,$y1, "Some Text");
$data->line( $_[0]->coords() ); # the non-closure way
} );
}
$r->render(); # heirarchically perform all the actions
# Get some info about a region:
($w,$h) = ( $a->width(), $a->height() );
($x1,$y1, $x2,$y2) = $a->coords();
($x1,$y1) = $a->top_left();
($x2,$y1) = $a->top_right();
($x1,$y2) = $a->bottom_left();
($x2,$y2) = $a->bottom_right();
Data::Region allows you to easily define a set of nested (2-dimensional) areas, defined by related coordinates, and to associate actions with them. The actions can then be performed hierarchically from any root of the tree.
Data::Region was written to provide an easy way to do simple page layout, but has, perhaps, more general uses.
<<lessSYNOPSIS
use Data::Region;
$r = Data::Region->new( 8.5, 11, { data => PageObj->new() } );
$r->data( PageObj->new() );
foreach my $c ( $r->subdivide(2.5,3) ) {
$a = $c->area(0.25,0.25, 2.25,2.75);
$a2 = $c->area(0.25,0.25, -0.25,-0.25); # as offset from lower right
($t,$m,$b) = $a->split_vertical(2,5,1); # sequential heights
($t,$m,$b) = $a->split_vertical_abs(0,2,7); # absolute offsets
($l,$r) = $a->split_horizontal(2); # $l gets width of 2, $r gets the rest
my($x1,$y1,$x2,$y2) = $a->coords();
my $data = $a->data(); # data inherits from parent, if not set
$a->action( sub { $data->setfont("Times-Bold", 10);
$data->text($x1,$y1, "Some Text");
$data->line( $_[0]->coords() ); # the non-closure way
} );
}
$r->render(); # heirarchically perform all the actions
# Get some info about a region:
($w,$h) = ( $a->width(), $a->height() );
($x1,$y1, $x2,$y2) = $a->coords();
($x1,$y1) = $a->top_left();
($x2,$y1) = $a->top_right();
($x1,$y2) = $a->bottom_left();
($x2,$y2) = $a->bottom_right();
Data::Region allows you to easily define a set of nested (2-dimensional) areas, defined by related coordinates, and to associate actions with them. The actions can then be performed hierarchically from any root of the tree.
Data::Region was written to provide an easy way to do simple page layout, but has, perhaps, more general uses.
Download (0.008MB)
Added: 2007-08-03 License: Perl Artistic License Price:
812 downloads
Transfer to Media Device 0.8
Transfer to Media Device is a script for transferring selected playlist items to your iPod. more>>
Transfer to Media Device is a script that creates a new Playlist Right Click Menu item for transferring selected playlist items to your iPod via the Media Device Browser.
This script now also supports generic copy to operation for USB mass storage devices. Currently the script will prompt for a destination directory on first copy, in the future this setting will be saved in a configuration file.
This script works with amaroK 1.3beta3 and above.
Usage:
Run from the amaroK script manager. A new menu item will appear in the Playlist right mouse button menu.
Select files in the playlist and Right click -> Transfer to -> iPod for transfering to an iPod.
Select files in the playlist and Right click -> Transfer to -> USB Device for transfering to a USB device.
Enhancements:
- Add support for Creative Nomad Jukebox devices using the kionjb kioslave. Thanks to Ralf T for the patch.
<<lessThis script now also supports generic copy to operation for USB mass storage devices. Currently the script will prompt for a destination directory on first copy, in the future this setting will be saved in a configuration file.
This script works with amaroK 1.3beta3 and above.
Usage:
Run from the amaroK script manager. A new menu item will appear in the Playlist right mouse button menu.
Select files in the playlist and Right click -> Transfer to -> iPod for transfering to an iPod.
Select files in the playlist and Right click -> Transfer to -> USB Device for transfering to a USB device.
Enhancements:
- Add support for Creative Nomad Jukebox devices using the kionjb kioslave. Thanks to Ralf T for the patch.
Download (0.003MB)
Added: 2005-12-23 License: GPL (GNU General Public License) Price:
1409 downloads
Fast Secure File System 0.1.1
Fast Secure File System is a secure, distributed, scalable, user-space file system. more>>
Fast Secure File System exports existing directories securely over the network, letting users store and retrieve encrypted data in a scalable and transparent way. FSFS is written in C and works on GNU/Linux systems on x86 and PPC architectures, with help from FUSE and OpenSSL.
File systems are easily the most evident, from the point of view of users, component of an operating system. Through file systems it is possible to organize data in a wide variety of ways, and access resources through a common interface.
Users can nowadays not only store and retrieve documents, but also find information on running processes and system settings (through ProcFS), access and manipulate e-mail (for example with GmailFS), or perform several other operations.
In several circumstances and scenarios it is desirable to protect stored files and directories from manipulation by unknown or malicious users: financial or health-related data, confidential documents, or any kind of personal or sensitive data may need to be stored securely, in such a way that it can not be examined or modified freely by third parties.
Most file systems do not take action in this sense, and external cryptographic utilities are sometimes employed to secure data before storage. While this can be a perfectly secure solution, it is not transparent to users.
Distributed file systems propose efficient ways of accessing data remotely as if it resided on the local machine; when it comes to dealing with securely stored data as in the examples above, care must be taken to preserve confidentiality and integrity also during network transfer.
Not all distributed file systems accomplish this task, weakening the overall security of the system, or do so inefficiently, making it inconvenient for users.
FSFS is a secure, distributed file system in users space, written in C with much help from FUSE and OpenSSL. It lets users store and retrieve data securely and transparently, knowing that it is protected both on permanent storage devices and while in transit over the network.
It is also concerned with scalability, therefore separates data cryptography from the server, leaving it to the clients; this approach is similar to the one used in CFS, and opposite to those taken on by other secure file system solutions (like NFS on top of IPsec).
FSFS is written as a pair of user space daemons that act as client and server. Because of this, it needs no kernel support (unlike NFS over IPsec), save the FUSE loadable kernel module on clients, included in Linux since 2.6.14; servers dont use FUSE and depend only on user space OpenSSL libraries.
Servers export an existing file system (of virtually any kind) to clients over the network through two separate channels: a TLS connection set up with OpenSSL, and a clear channel. Requests from the clients to the servers are sent via the TLS socket, thus they are encrypted and authenticated, according to TLS v1 specifications, by the channel itself and decrypted on receipt, as they are usually very short and the relevant cryptography does not constitute a great overhead; simple server replies undergo the same process.
Cryptography in this case happens at both ends of the transmission.
In a distributed file system, large amounts of data may be transferred between clients and servers, thus encrypting and decrypting everything may become too cumbersome for both parties, and as more clients are added to the system the server may severely lose performance; moreover, file data should be stored encrypted anyway, so the cryptography could be moved to the clients, in such a way that each encrypts data before a write operation sends it over the network to the server, and decrypts it after a read retrieves it.
This way servers only deal with TLS details and can concentrate on serving client requests by doing the relevant I/O on the underlying, "physical" file system. As the data is already encrypted, it does not need to go through the TLS channel and the corresponding overhead, but can be sent via the clear channel, provided the messages are authenticated.
Enhancements:
- This release fixes two bugs. One bug related to socket creation and would cause problems on some systems (namely OpenSUSE 10.2). The other bug related to server configuration creation when using the Python configuration utilities. Users dont need to upgrade to this release if theyre not experiencing problems or are not using the Python configuration utilities.
<<lessFile systems are easily the most evident, from the point of view of users, component of an operating system. Through file systems it is possible to organize data in a wide variety of ways, and access resources through a common interface.
Users can nowadays not only store and retrieve documents, but also find information on running processes and system settings (through ProcFS), access and manipulate e-mail (for example with GmailFS), or perform several other operations.
In several circumstances and scenarios it is desirable to protect stored files and directories from manipulation by unknown or malicious users: financial or health-related data, confidential documents, or any kind of personal or sensitive data may need to be stored securely, in such a way that it can not be examined or modified freely by third parties.
Most file systems do not take action in this sense, and external cryptographic utilities are sometimes employed to secure data before storage. While this can be a perfectly secure solution, it is not transparent to users.
Distributed file systems propose efficient ways of accessing data remotely as if it resided on the local machine; when it comes to dealing with securely stored data as in the examples above, care must be taken to preserve confidentiality and integrity also during network transfer.
Not all distributed file systems accomplish this task, weakening the overall security of the system, or do so inefficiently, making it inconvenient for users.
FSFS is a secure, distributed file system in users space, written in C with much help from FUSE and OpenSSL. It lets users store and retrieve data securely and transparently, knowing that it is protected both on permanent storage devices and while in transit over the network.
It is also concerned with scalability, therefore separates data cryptography from the server, leaving it to the clients; this approach is similar to the one used in CFS, and opposite to those taken on by other secure file system solutions (like NFS on top of IPsec).
FSFS is written as a pair of user space daemons that act as client and server. Because of this, it needs no kernel support (unlike NFS over IPsec), save the FUSE loadable kernel module on clients, included in Linux since 2.6.14; servers dont use FUSE and depend only on user space OpenSSL libraries.
Servers export an existing file system (of virtually any kind) to clients over the network through two separate channels: a TLS connection set up with OpenSSL, and a clear channel. Requests from the clients to the servers are sent via the TLS socket, thus they are encrypted and authenticated, according to TLS v1 specifications, by the channel itself and decrypted on receipt, as they are usually very short and the relevant cryptography does not constitute a great overhead; simple server replies undergo the same process.
Cryptography in this case happens at both ends of the transmission.
In a distributed file system, large amounts of data may be transferred between clients and servers, thus encrypting and decrypting everything may become too cumbersome for both parties, and as more clients are added to the system the server may severely lose performance; moreover, file data should be stored encrypted anyway, so the cryptography could be moved to the clients, in such a way that each encrypts data before a write operation sends it over the network to the server, and decrypts it after a read retrieves it.
This way servers only deal with TLS details and can concentrate on serving client requests by doing the relevant I/O on the underlying, "physical" file system. As the data is already encrypted, it does not need to go through the TLS channel and the corresponding overhead, but can be sent via the clear channel, provided the messages are authenticated.
Enhancements:
- This release fixes two bugs. One bug related to socket creation and would cause problems on some systems (namely OpenSUSE 10.2). The other bug related to server configuration creation when using the Python configuration utilities. Users dont need to upgrade to this release if theyre not experiencing problems or are not using the Python configuration utilities.
Download (MB)
Added: 2007-08-12 License: GPL (GNU General Public License) Price:
806 downloads
GtkDatabox 0.7.0.1
GtkDatabox is a widget for the Gtk+-library designed to display large amounts of numerical data fast and easy. more>>
GtkDatabox is a widget for the Gtk+-library designed to display large amounts of numerical data fast and easy. One or more data sets of thousands of data points (X and Y coordinate) may be displayed and updated in split seconds.
The widget is therfore used in many scientific and private projects that need to show quickly changing data "live".
GtkDatabox offers the ability to zoom into and out of the data and to navigate through your data by scrolling.
In addition to rulers and a simple coordinate cross, GtkDatabox now also allows you to add one (or even more) configurable grids like on an oscilloscope.
Data may be presented as dots, lines connecting the data, or vertical bars. The widget allows you to easily transform pixel coordinates into data coordinates, thus allowing you to easily create powerful applications for data analysis.
GtkDatabox is free software distributed under the GNU LESSER General Public License (LGPL).
Enhancements:
- Bugfix release.
- A potential memory leak has been removed from one of the graph classes (marker).
<<lessThe widget is therfore used in many scientific and private projects that need to show quickly changing data "live".
GtkDatabox offers the ability to zoom into and out of the data and to navigate through your data by scrolling.
In addition to rulers and a simple coordinate cross, GtkDatabox now also allows you to add one (or even more) configurable grids like on an oscilloscope.
Data may be presented as dots, lines connecting the data, or vertical bars. The widget allows you to easily transform pixel coordinates into data coordinates, thus allowing you to easily create powerful applications for data analysis.
GtkDatabox is free software distributed under the GNU LESSER General Public License (LGPL).
Enhancements:
- Bugfix release.
- A potential memory leak has been removed from one of the graph classes (marker).
Download (0.33MB)
Added: 2007-03-21 License: GPL (GNU General Public License) Price:
949 downloads
Earn-Fast-Cash 1.0
The Ultimate Safe Money Guide -Free Online Money Guide Make Your Online Money The Safe Way And Generate a Daily Income Stream. The best thing I came ... more>> <<less
Download (2117KB)
Added: 2009-04-19 License: Freeware Price: Free
189 downloads
assniffer 0.1 Alpha
assniffer is an auto saving sniffer for windows and linux. more>>
assniffer is an auto saving sniffer for windows and linux.
assniffer can monitor (using pcap) a network, and for every HTTP transfer it sees, save a copy of the transferred data.
This is less for sinister uses, and more for taking advantage of the already-transferred data that your computer may be exposed to.
Linux users should install libpcap, and tools to enable compiling.
Compilation:
- Go to the source/assniffer directory and type make.
<<lessassniffer can monitor (using pcap) a network, and for every HTTP transfer it sees, save a copy of the transferred data.
This is less for sinister uses, and more for taking advantage of the already-transferred data that your computer may be exposed to.
Linux users should install libpcap, and tools to enable compiling.
Compilation:
- Go to the source/assniffer directory and type make.
Download (0.030MB)
Added: 2006-03-10 License: Freeware Price:
1325 downloads
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