aqua data
Sponsored Links
Sponsored Links
Secleted [ 0 ] software to compare
Results 1 - 15 of about 4881
Aqua Data Studio 6.0.10
Aqua Data Studio is a database query tool and administration tool that allows developers to easily create, edit, and execute SQL more>>
Aqua Data Studio program is a database query tool and administration tool that allows developers to easily create, edit, and execute SQL scripts, as well as browse and visually modify database structures.
Aqua Data Studio provides an integrated database environment with a single consistent interface to all major relational databases. This allows the database administrator or developer to tackle multiple tasks simultaneously from one application.
Main features:
Query Analyzer/Window
- Aqua Data Studios sophisticated Query Analyzer allows users to work on database scripts with specific RDBMS syntax highlighting and auto-completion to develop and test SQL scripts. Other features to speed up development include SQL automation, auto-describe and sortable multi-grid results. The query analyzer also provides client side variable binding, allowing a user to execute stored procedures or functions with local variables binded to receive out parameters. The query window also provides two modes of operation, using a SplitPane View or a MultiTab View for the editor and the query results.
Schema Browser & Visual Editing
- Its graphical browsing capabilities allow you to understand the structure and dependencies of the database schema with a single mouse click. The schema browser also allows you to visually edit any schema object with a graphical design form to CREATE, ALTER or DROP the object. Visual editing supports Tables, Indexes, Procedures, Data Types and other schema objects. The visual editors also provides an SQL preview of all the commands to be executed to commit the operation.
Schema Extraction & DDL Scripting
- Its graphical browsing allows you to extract the structure definition of all schema objects and to script the SQL DDL and DML (eg CREATE, ALTER, DROP, SELECT, INSERT, UPDATE and DELETE) syntax for database schema objects (including Tables, Views, Triggers, Stored Procedures and Functions).
Table Data Editor
- A powerful Table Data Editor allows you to modify your results graphically and save them. By writing a single table SELECT statement in the Query Analyzer and clicking on the Execute Edit button, a separate window is opened with the query results for you to edit and save. You may also browser to a table in the schema browser and select the Edit Table from the popup menu to edit the first 1000 records in a table.
Enhancements:
- Enhancements in this release include OS X Integration, Windows integration, complete and customizable keymapping, a schema difference tool, a directory difference tool, a file difference tool, a tab difference tool, a copy history difference tool, SQL Server DBA tools, and Sybase DBA tools.
- In total, there were over 100 new features.
<<lessAqua Data Studio provides an integrated database environment with a single consistent interface to all major relational databases. This allows the database administrator or developer to tackle multiple tasks simultaneously from one application.
Main features:
Query Analyzer/Window
- Aqua Data Studios sophisticated Query Analyzer allows users to work on database scripts with specific RDBMS syntax highlighting and auto-completion to develop and test SQL scripts. Other features to speed up development include SQL automation, auto-describe and sortable multi-grid results. The query analyzer also provides client side variable binding, allowing a user to execute stored procedures or functions with local variables binded to receive out parameters. The query window also provides two modes of operation, using a SplitPane View or a MultiTab View for the editor and the query results.
Schema Browser & Visual Editing
- Its graphical browsing capabilities allow you to understand the structure and dependencies of the database schema with a single mouse click. The schema browser also allows you to visually edit any schema object with a graphical design form to CREATE, ALTER or DROP the object. Visual editing supports Tables, Indexes, Procedures, Data Types and other schema objects. The visual editors also provides an SQL preview of all the commands to be executed to commit the operation.
Schema Extraction & DDL Scripting
- Its graphical browsing allows you to extract the structure definition of all schema objects and to script the SQL DDL and DML (eg CREATE, ALTER, DROP, SELECT, INSERT, UPDATE and DELETE) syntax for database schema objects (including Tables, Views, Triggers, Stored Procedures and Functions).
Table Data Editor
- A powerful Table Data Editor allows you to modify your results graphically and save them. By writing a single table SELECT statement in the Query Analyzer and clicking on the Execute Edit button, a separate window is opened with the query results for you to edit and save. You may also browser to a table in the schema browser and select the Edit Table from the popup menu to edit the first 1000 records in a table.
Enhancements:
- Enhancements in this release include OS X Integration, Windows integration, complete and customizable keymapping, a schema difference tool, a directory difference tool, a file difference tool, a tab difference tool, a copy history difference tool, SQL Server DBA tools, and Sybase DBA tools.
- In total, there were over 100 new features.
Download (53.2MB)
Added: 2007-01-16 License: Free for non-commercial use Price:
859 downloads
Yukatan data model 1.0
Yukatan data model project is the schema definition of the Yukatan webmail database. more>>
Yukatan data model project is the schema definition of the Yukatan webmail database.
The PostgreSQL database structures defined in this file can be used as a backend store of an email message handling application. The database should be created with the "UNICODE" encoding to properly support messages in different languages.
New data types
The special data types commonly used in the Yukatan data model have been made explicit by the introduction of seven new domains. The domains and the related COMMENT statements make field semantics more clear than before.
See the SQL schema file for more detailed documentation on these domains.
Explicitly named constraints
All the table constraints in the database are now explicitly named and documented. This change makes the database implementation more orthogonal and cleans up the documentation.
Renamed fields and tables
All the *address field names have been truncated to *addr, to make it visually clearer that they are always paired with the corresponding *name fields. The change also makes parts of the documentation less repetitive.
The referencesfield table has been renamed to referencefield to avoid the plural form in the table name. Also all the contained references* field names have been renamed to reference*.
Semantic changes
Quite a few changes have been made to the semantics of various fields. The unnecessarily tight constraints on sequence numbers have been replaced with clearer documentation, the format and encoding of most fields has been explicitly documented, and the previously allowed dual use of the enttext and enddata fields has been prohibited.
Dropped envelope data
The envelope data added in version 0.5 of the data model has for now been removed. The reason for the removal is that the envelope data is not an integral part of an email message, and I wanted to make the version 1.0 as clear as possible. The database now stores "email messages" - nothing less, nothing more. Envelope data can and probably will be reintroduced in an incremental version 1.x along with other extensions.
Enhancements:
- cleans up and documents the data model that has developed since version 0.1
- removal of the envelope data added in version 0.5
- enaming and redefinition of some of the fields and tables
- database structure has also been extensively documented
<<lessThe PostgreSQL database structures defined in this file can be used as a backend store of an email message handling application. The database should be created with the "UNICODE" encoding to properly support messages in different languages.
New data types
The special data types commonly used in the Yukatan data model have been made explicit by the introduction of seven new domains. The domains and the related COMMENT statements make field semantics more clear than before.
See the SQL schema file for more detailed documentation on these domains.
Explicitly named constraints
All the table constraints in the database are now explicitly named and documented. This change makes the database implementation more orthogonal and cleans up the documentation.
Renamed fields and tables
All the *address field names have been truncated to *addr, to make it visually clearer that they are always paired with the corresponding *name fields. The change also makes parts of the documentation less repetitive.
The referencesfield table has been renamed to referencefield to avoid the plural form in the table name. Also all the contained references* field names have been renamed to reference*.
Semantic changes
Quite a few changes have been made to the semantics of various fields. The unnecessarily tight constraints on sequence numbers have been replaced with clearer documentation, the format and encoding of most fields has been explicitly documented, and the previously allowed dual use of the enttext and enddata fields has been prohibited.
Dropped envelope data
The envelope data added in version 0.5 of the data model has for now been removed. The reason for the removal is that the envelope data is not an integral part of an email message, and I wanted to make the version 1.0 as clear as possible. The database now stores "email messages" - nothing less, nothing more. Envelope data can and probably will be reintroduced in an incremental version 1.x along with other extensions.
Enhancements:
- cleans up and documents the data model that has developed since version 0.1
- removal of the envelope data added in version 0.5
- enaming and redefinition of some of the fields and tables
- database structure has also been extensively documented
Download (0.035MB)
Added: 2007-02-19 License: GPL (GNU General Public License) Price:
983 downloads
Virtual Data Center 1.04-11
The Virtual Data Center (VDC) is a digital library system more>>
The Virtual Data Center (VDC) is a digital library system "in a box" for numeric data.
The VDC is a web application which provides everything necessary to maintain and disseminate collections of research studies: including facilities for the storage, archiving, cataloging, translation, and dissemination of each collection.
It includes on-line analysis, powered by the R Statistical environment. It also provides extensive support for distributed and federated collections including: location-independent naming of objects, distributed authentication and access control, federated metadata harvesting, remote repository caching, and distributed virtual
<<lessThe VDC is a web application which provides everything necessary to maintain and disseminate collections of research studies: including facilities for the storage, archiving, cataloging, translation, and dissemination of each collection.
It includes on-line analysis, powered by the R Statistical environment. It also provides extensive support for distributed and federated collections including: location-independent naming of objects, distributed authentication and access control, federated metadata harvesting, remote repository caching, and distributed virtual
Download (14.5MB)
Added: 2006-04-18 License: GPL (GNU General Public License) Price:
1287 downloads
MacOS-X Aqua Theme 1.2.1
MacOS-X Aqua Theme provides a GTK 2.x Theme/Style. more>>
MacOS-X Aqua Theme provides a GTK 2.x Theme/Style.
Installation guide :
[Part 1] GTK2 Theme
Step 1 : If you have got the old version before, then delete the old version.
rm -Rf ~/.themes/MacOS-X
if not, skip this step.
Step 2 : Unpack the downloaded file.
tar zxf 13548-Gnome_MacOS-X_Aqua_Theme_20040730.tar.gz
Step 3 : Move the entire folder named "MacOS-X" into ~/.themes
mv MacOS-X ~/.themes
Enhancements:
- Fixed bugs found in gtk theme.
- 72x72 and 96x96 icons added to Icon theme.
<<lessInstallation guide :
[Part 1] GTK2 Theme
Step 1 : If you have got the old version before, then delete the old version.
rm -Rf ~/.themes/MacOS-X
if not, skip this step.
Step 2 : Unpack the downloaded file.
tar zxf 13548-Gnome_MacOS-X_Aqua_Theme_20040730.tar.gz
Step 3 : Move the entire folder named "MacOS-X" into ~/.themes
mv MacOS-X ~/.themes
Enhancements:
- Fixed bugs found in gtk theme.
- 72x72 and 96x96 icons added to Icon theme.
Download (0.33MB)
Added: 2007-03-01 License: GPL (GNU General Public License) Price:
646 downloads
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
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.
<<lessThe 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.
Download (0.61MB)
Added: 2007-08-09 License: BSD License Price:
809 downloads
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.
<<lessSecure 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.
Download (1.9MB)
Added: 2007-01-18 License: GPL (GNU General Public License) Price:
1012 downloads
Data::Stag 0.10
Data::Stag is a Perl module with structured tags datastructures. more>>
Data::Stag is a Perl module with structured tags datastructures.
SYNOPSIS
# PROCEDURAL USAGE
use Data::Stag qw(:all);
$doc = stag_parse($file);
@persons = stag_find($doc, "person");
foreach $p (@persons) {
printf "%s, %s phone: %sn",
stag_sget($p, "family_name"),
stag_sget($p, "given_name"),
stag_sget($p, "phone_no"),
;
}
# OBJECT-ORIENTED USAGE
use Data::Stag;
$doc = Data::Stag->parse($file);
@persons = $doc->find("person");
foreach $p (@person) {
printf "%s, %s phone:%sn",
$p->sget("family_name"),
$p->sget("given_name"),
$p->sget("phone_no"),
;
}
This module is for manipulating data as hierarchical tag/value pairs (Structured TAGs or Simple Tree AGgreggates).
<<lessSYNOPSIS
# PROCEDURAL USAGE
use Data::Stag qw(:all);
$doc = stag_parse($file);
@persons = stag_find($doc, "person");
foreach $p (@persons) {
printf "%s, %s phone: %sn",
stag_sget($p, "family_name"),
stag_sget($p, "given_name"),
stag_sget($p, "phone_no"),
;
}
# OBJECT-ORIENTED USAGE
use Data::Stag;
$doc = Data::Stag->parse($file);
@persons = $doc->find("person");
foreach $p (@person) {
printf "%s, %s phone:%sn",
$p->sget("family_name"),
$p->sget("given_name"),
$p->sget("phone_no"),
;
}
This module is for manipulating data as hierarchical tag/value pairs (Structured TAGs or Simple Tree AGgreggates).
Download (0.43MB)
Added: 2006-10-03 License: Perl Artistic License Price:
1117 downloads
Test::Data 1.20
Test::Data is a Perl module to test functions for particular variable types. more>>
Test::Data is a Perl module to test functions for particular variable types.
SYNOPSIS
use Test::Data qw(Scalar Array Hash Function);
Test::Data provides utility functions to check properties and values of data and variables.
Functions
Plug-in modules define functions for each data type. See the appropriate module.
How it works
The Test::Data module simply emports functions from Test::Data::* modules. Each module defines a self-contained function, and puts that function name into @EXPORT. Test::Data defines its own import function, but that does not matter to the plug-in modules.
If you want to write a plug-in module, follow the example of one that already exists. Name the module Test::Data::Foo, where you replace Foo with the right name. Test::Data should automatically find it.
<<lessSYNOPSIS
use Test::Data qw(Scalar Array Hash Function);
Test::Data provides utility functions to check properties and values of data and variables.
Functions
Plug-in modules define functions for each data type. See the appropriate module.
How it works
The Test::Data module simply emports functions from Test::Data::* modules. Each module defines a self-contained function, and puts that function name into @EXPORT. Test::Data defines its own import function, but that does not matter to the plug-in modules.
If you want to write a plug-in module, follow the example of one that already exists. Name the module Test::Data::Foo, where you replace Foo with the right name. Test::Data should automatically find it.
Download (0.008MB)
Added: 2007-05-03 License: Perl Artistic License Price:
904 downloads
Data::ICal 0.11
Data::ICal is a Perl module that generates iCalendar (RFC 2445) calendar files. more>>
Data::ICal is a Perl module that generates iCalendar (RFC 2445) calendar files.
SYNOPSIS
use Data::ICal;
my $calendar = Data::ICal->new();
my $vtodo = Data::ICal::Entry::Todo->new();
$vtodo->add_properties(
# ... see Data::ICal::Entry::Todo documentation
);
# ... or
$calendar = Data::ICal->new(filename => foo.ics); # parse existing file
$calendar = Data::ICal->new(data => BEGIN:VCALENDAR...); # parse existing file
$calendar->add_entry($vtodo);
print $calendar->as_string;
# Or, if youre printing to something you want google to read:
print $calendar->as_string(fold => 0);
A Data::ICal object represents a VCALENDAR object as defined in the iCalendar protocol (RFC 2445, MIME type "text/calendar"), as implemented in many popular calendaring programs such as Apples iCal.
Each Data::ICal object is a collection of "entries", which are objects of a subclass of Data::ICal::Entry. The types of entries defined by iCalendar (which refers to them as "components") include events, to-do items, journal entries, free/busy time indicators, and time zone descriptors; in addition, events and to-do items can contain alarm entries. (Currently, Data::ICal only implements to-do items and events.)
Data::ICal is a subclass of Data::ICal::Entry; see its manpage for more methods applicable to Data::ICal.
<<lessSYNOPSIS
use Data::ICal;
my $calendar = Data::ICal->new();
my $vtodo = Data::ICal::Entry::Todo->new();
$vtodo->add_properties(
# ... see Data::ICal::Entry::Todo documentation
);
# ... or
$calendar = Data::ICal->new(filename => foo.ics); # parse existing file
$calendar = Data::ICal->new(data => BEGIN:VCALENDAR...); # parse existing file
$calendar->add_entry($vtodo);
print $calendar->as_string;
# Or, if youre printing to something you want google to read:
print $calendar->as_string(fold => 0);
A Data::ICal object represents a VCALENDAR object as defined in the iCalendar protocol (RFC 2445, MIME type "text/calendar"), as implemented in many popular calendaring programs such as Apples iCal.
Each Data::ICal object is a collection of "entries", which are objects of a subclass of Data::ICal::Entry. The types of entries defined by iCalendar (which refers to them as "components") include events, to-do items, journal entries, free/busy time indicators, and time zone descriptors; in addition, events and to-do items can contain alarm entries. (Currently, Data::ICal only implements to-do items and events.)
Data::ICal is a subclass of Data::ICal::Entry; see its manpage for more methods applicable to Data::ICal.
Download (0.10MB)
Added: 2006-12-01 License: Perl Artistic License Price:
1059 downloads
Data::Diff 0.01
Data::Diff is a data structure comparison module. more>>
Data::Diff is a data structure comparison module.
SYNOPSIS
use Data::Diff qw(diff);
# simple procedural interface to raw difference output
$out = diff( $a, $b );
# OO usage
$diff = Data::Diff->new( $a, $b );
$new = $diff->apply();
$changes = $diff->diff_a();
Data::Diff computes the differences between two abirtray complex data structures.
METHODS
Creation
new Data::Diff( $a, $b, $options )
Creates and retruns a new Data::Diff object with the differences between $a and $b.
Access
apply( $options )
Returns the result of applying one side over the other.
raw()
Returns the internal data structure that describes the differences at all levels within.
Functions
Diff( $a, $b, $options )
Compares the two arguments $a and $b and returns the raw comparison between the two.
EXPORT
Nothing by default but you can choose to export the non-OO function Diff().
<<lessSYNOPSIS
use Data::Diff qw(diff);
# simple procedural interface to raw difference output
$out = diff( $a, $b );
# OO usage
$diff = Data::Diff->new( $a, $b );
$new = $diff->apply();
$changes = $diff->diff_a();
Data::Diff computes the differences between two abirtray complex data structures.
METHODS
Creation
new Data::Diff( $a, $b, $options )
Creates and retruns a new Data::Diff object with the differences between $a and $b.
Access
apply( $options )
Returns the result of applying one side over the other.
raw()
Returns the internal data structure that describes the differences at all levels within.
Functions
Diff( $a, $b, $options )
Compares the two arguments $a and $b and returns the raw comparison between the two.
EXPORT
Nothing by default but you can choose to export the non-OO function Diff().
Download (0.006MB)
Added: 2007-07-13 License: Perl Artistic License Price:
833 downloads
File::Data 1.12
File::Data is a Perl module as a interface to file data. more>>
File::Data is a Perl module as a interface to file data.
Wraps all the accessing of a file into a convenient set of calls for reading and writing data, including a simple regex interface.
Note that the file needs to exist prior to using this module!
See new()
SYNOPSIS
use strict;
use File::Data;
my $o_dat = File::Data->new(./t/example);
$o_dat->write("complete file contentsn");
$o_dat->prepend("first linen"); # line 0
$o_dat->append("original second (last) linen");
$o_dat->insert(2, "new second linen"); # inc. zero!
$o_dat->replace(line, LINE);
print $o_dat->READ;
Or, perhaps more seriously :-}
my $o_sgm = File::Data->new(./sgmlfile);
print "new SGML data: ".$o_sgm->REPLACE(
s*((?s).*)s* ,
qq| key="val" |,
) if $o_sgm;
See METHODS and EXAMPLES.
IMPORTANT
lowercase method calls return the object itself, so you can chain calls.
my $o_obj = $o_dat->read; # ! READ; # !<<less
Wraps all the accessing of a file into a convenient set of calls for reading and writing data, including a simple regex interface.
Note that the file needs to exist prior to using this module!
See new()
SYNOPSIS
use strict;
use File::Data;
my $o_dat = File::Data->new(./t/example);
$o_dat->write("complete file contentsn");
$o_dat->prepend("first linen"); # line 0
$o_dat->append("original second (last) linen");
$o_dat->insert(2, "new second linen"); # inc. zero!
$o_dat->replace(line, LINE);
print $o_dat->READ;
Or, perhaps more seriously :-}
my $o_sgm = File::Data->new(./sgmlfile);
print "new SGML data: ".$o_sgm->REPLACE(
s*((?s).*)s* ,
qq| key="val" |,
) if $o_sgm;
See METHODS and EXAMPLES.
IMPORTANT
lowercase method calls return the object itself, so you can chain calls.
my $o_obj = $o_dat->read; # ! READ; # !<<less
Download (0.013MB)
Added: 2007-04-26 License: Perl Artistic License Price:
914 downloads
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.
<<lessSYNOPSIS
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.
Download (0.006MB)
Added: 2006-10-31 License: Perl Artistic License Price:
1088 downloads
Sunrise Data Dictionary 1.00
Sunrise Data Dictionary is a library for hashtable storage of arbitrary data objects. more>>
Sunrise Data Dictionary is a library for hashtable storage of arbitrary data objects with built-in reference counting and guaranteed order iteration for the C programming language.
Sunrise Data Dictionary library can participate in external reference counting systems or use its own built-in reference counting. It comes with a variety of hash functions and allows the use of runtime supplied hash functions via callback mechanism. The source code is well documented.
The Sunrise Data Dictionary was specifically designed for use within the Afelio and Callweaver telephony servers, the implementation focuses on performance and scalability.
Enhancements:
- This is the initial release of the full API (all header files) and a developer snapshot of the implementation.
<<lessSunrise Data Dictionary library can participate in external reference counting systems or use its own built-in reference counting. It comes with a variety of hash functions and allows the use of runtime supplied hash functions via callback mechanism. The source code is well documented.
The Sunrise Data Dictionary was specifically designed for use within the Afelio and Callweaver telephony servers, the implementation focuses on performance and scalability.
Enhancements:
- This is the initial release of the full API (all header files) and a developer snapshot of the implementation.
Download (0.17MB)
Added: 2007-07-16 License: MIT/X Consortium License Price:
832 downloads
Secleted [ 0 ] software to compare
Copyright Notice:
Software piracy is theft, Using crack, password, serial numbers, registration codes, key generators is illegal and prevent future software development. The above aqua data search only lists software in full, demo and trial versions for free download. Download links are directly from our mirror sites or publisher sites, torrent files or links from rapidshare.com, yousendit.com or megaupload.com are not allowed