Free 0.6 hours is equal to how many days software for linux

C Minimal Perfect Hashing Library encapsulates the newest and more efficient algorithms in an easy-to-use, production-quality, fast API. The library was designed to work with big entries that cannot fit in the main memory. It has been used successfully for constructing minimal perfect hash functions for sets with more than 100 million of keys, and we intend to expand this number to the order of billion of keys.
Main features:
- Fast.
- Space-efficient with main memory usage carefully documented.
- The best modern algorithms are available (or at least scheduled for implementation :-)).
- Works with in-disk key sets through of using the adapter pattern.
- Serialization of hash functions.
- Portable C code (currently works on GNU/Linux and WIN32 and is reported to work in OpenBSD and Solaris).
- Object oriented implementation.
- Easily extensible.
- Well encapsulated API aiming binary compatibility through releases.
- Free Software.
A perfect hash function maps a static set of n keys into a set of m integer numbers without collisions, where m is greater than or equal to n. If m is equal to n, the function is called minimal.
Minimal perfect hash functions are widely used for memory efficient storage and fast retrieval of items from static sets, such as words in natural languages, reserved words in programming languages or interactive systems, universal resource locations (URLs) in Web search engines, or item sets in data mining techniques. Therefore, there are applications for minimal perfect hash functions in information retrieval systems, database systems, language translation systems, electronic commerce systems, compilers, operating systems, among others.
The use of minimal perfect hash functions is, until now, restricted to scenarios where the set of keys being hashed is small, because of the limitations of current algorithms. But in many cases, to deal with huge set of keys is crucial. So, this project gives to the free software community an API that will work with sets in the order of billion of keys.
Probably, the most interesting application for minimal perfect hash functions is its use as an indexing structure for databases. The most popular data structure used as an indexing structure in databases is the B+ tree. In fact, the B+ tree is very used for dynamic applications with frequent insertions and deletions of records. However, for applications with sporadic modifications and a huge number of queries the B+ tree is not the best option, because practical deployments of this structure are extremely complex, and perform poorly with very large sets of keys such as those required for the new frontiers database applications.
For example, in the information retrieval field, the work with huge collections is a daily task. The simple assignment of ids to web pages of a collection can be a challenging task. While traditional databases simply cannot handle more traffic once the working set of web page urls does not fit in main memory anymore, minimal perfect hash functions can easily scale to hundred of millions of entries, using stock hardware.
As there are lots of applications for minimal perfect hash functions, it is important to implement memory and time efficient algorithms for constructing such functions. The lack of similar libraries in the free software world has been the main motivation to create the C Minimal Perfect Hashing Library (gperf is a bit different, since it was conceived to create very fast perfect hash functions for small sets of keys and CMPH Library was conceived to create minimal perfect hash functions for very large sets of keys). C Minimal Perfect Hashing Library is a portable LGPLed library to generate and to work with very efficient minimal perfect hash functions.
Enhancements:
- This release adds an implementation of a classical minimal perfect hash algorithm called fch.
- This is used as a basis for a new algorithm that can create minimal perfect hashes for billions of keys with less than four bits per key, and is ready to use.
- Suggestions and bugfixes from users have been incorporated.

BetterAWstats is made to provide better statistics out of the data AWstats provides. The project is not a replacment of AWstats.
Main features:
- Multi-site data - If the path to the datafile has the files of several sites in it, all those sites can be viewed in BetterAWstats
- Rolling months - 12 months data chart & table now end in the selected month and show the previous 12 month instead of showing only the current year Jan-Dec.
- Rolling days - If the current month is not finished, the daily data shows the last days from the last month. The total amount of days shown is equal to the current months number of days.
- Pages & Hits have independent scale - In AWstats, the pages charts are scaled as a 1:1 to hits. So a website with 10 images on each page would show a one-pixel high pages-bar and a 10 pixel high hits-bar for one view of a page. If you have more images (in your layout etc), the pages ba becomes too small to show any information. BetterAWstats gives each bar its own scale, depending on the maximum value over the given timespan.
- Weekday data as average - In AWstats, data for each weekday (Mo, Tue...) would be summed up. So a month with 5 mondays would have more hits on Mondays than for its 4 Tuesdays. By building the average per weekday in BetterAWstats, you can see better how much more people come on Mondays to your site, independent how many Mondays that one month has. Also, beeing in the middle of the current month has less impact due to the fact that one Monday on the end of the month did not add any data to that month.
- Number of Visits per Weekday - Although this data is available, AWstats would not show it. BetterAWstats does!

Amarok is a wonderful media player and audio library management tool for Linux. Podcast Cleanup allows for extensions by third parties via a nice script system.

Amarok has some in-built support for subscribing to podcasts, however, at time of writing, there is no convenient way to manage deletion of downloaded podcast episodes en-masse.

Presently, the only way to delete downloaded podcast files from amarok is to traverse the podcast list, right clicking on each downloaded podcast episode, and selecting delete from the contect menu. This is quite cumbersome, particularly considering the fact that ever deletion provokes a confirmation dialog.

I listen to a lot of podcasts, and I wanted a better way to manage my downloaded podcast files, so I wrote a small script to delete downloaded podcast files.

The script can delete downloaded podcasts, either unconditionally, or just the listened podcasts, or listend-to podcasts which are older than some age (expressed in hours, days, weeks or months.

Its possible to specify cleanup criteria for startup, and at some regular time interval (after the initial check).

Its possible to request confirmation before deletion is done, and to request a notification when files have been cleaned up.

Search::Binary is a Perl module for generic binary search.

SYNOPSIS

use Seach::Binary;
$pos = binary_search($min, $max, $val, $read, $handle, [$size]);

binary_search implements a generic binary search algorithm returning the position of the first record whose index value is greater than or equal to $val. The search routine does not define any of the terms position, record or index value, but leaves their interpretation and implementation to the user supplied function &$read(). The only restriction is that positions must be integer scalars.

During the search the read function will be called with three arguments: the input parameters $handle and $val, and a position. If the position is not undef, the read function should read the first whole record starting at or after the position; otherwise, the read function should read the record immediately following the last record it read. The search algorithm will guarantee that the first call to the read function will not be with a position of undef. The read function needs to return a two element array consisting of the result of comparing $val with the index value of the read record and the position of the read record. The comparison value must be positive if $val is strictly greater than the index value of the read record, 0 if equal, and negative if strictly less. Furthermore, the returned position value must be greater than or equal to the position the read function was called with.

The input parameters $min and $max are positions and represents the extent of the search. Only records which begin at positions within this range (inclusive) will be searched. Moreover, $min must be the starting position of a record. If present $size is a difference between positions and determines when the algorithms switches to a sequential search. $val is an index value. The value of $handle is of no consequence to the binary search algorithm; it is merely passed as a convenience to the read function.

Math::MagicSquare is a Magic Square Checker and Designer.

SYNOPSIS

use Math::MagicSquare;

$a= Math::MagicSquare -> new ([num,...,num],
...,
[num,...,num]);
$a->print("string");
$a->printhtml();
$a->printimage();
$a->check();
$a->rotation();
$a->reflection();

The following methods are available:

new

Constructor arguments are a list of references to arrays of the same length.

$a = Math::MagicSquare -> new ([num,...,num],
...,
[num,...,num]);

check

This function can return 4 value

0: the Square is not Magic
1: the Square is a Semimagic Square (the sum of the rows and the columns is equal)
2: the Square is a Magic Square (the sum of the rows, the columns and the diagonals is equal)
3: the Square ia Panmagic Square (the sum of the rows, the columns, the diagonals and the broken diagonals is equal)

print

Prints the Square on STDOUT. If the method has additional parameters, these are printed before the Magic Square is printed.

printhtml

Prints the Square on STDOUT in an HTML format (exactly a inside a TABLE)

printimage

Prints the Square on STDOUT in png format.

rotation

Rotates the Magic Square of 90 degree clockwise

reflection

Reflect the Magic Square

Gmail Tray is a very simple Gmail notificaiton applet for the desktop system tray.

Why?

Because I needed one that will support "Gmail In Your Domain". And it took me less that 2 hours to get the first version working.