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Alexei Podvalsky

awissu

Involved Projects and Packages
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Gambas is a free development environment based on a Basic interpreter
with object extensions, like Visual Basic(tm) (but it is NOT a clone!).
With Gambas, you can quickly design your program GUI, access MySQL or
PostgreSQL databases, control KDE applications with DCOP, translate
your program into many languages, create network applications easily,
build RPMs of your apps automatically, and so on... You have to install
the necessary components

Gambas is still in development, but already useful for smaller projects.
The IDE itself is written in Gambas-BASIC. The source can be used reviewed
as an example application in the /usr/share/gambas/examples directory.
Documentation is also in that directory.

Maintainer

This project contains packages required to use or setup peer to peer networks as well as other tools to share files.

Maintainer

GNUnet is peer-to-peer framework focusing on security. The first and primary application for GNUnet is anonymous file-sharing. GNUnet is currently developed by a worldwide group of independent free software developers.

GNUnet is a part of the GNU project (http://www.gnu.org/).

Maintainer

GNUnet-fuse allows you to mount directories published on GNUnet.

Maintainer

Using libextractor, you can extract metadata from files of arbitrary
types. Supported file formats include HTML, PDF, DVI, PS, MP3, OGG,
WAV, JPEG, GIF, PNG, TIFF, RPM, ZIP, TAR, ELF, REAL, RIFF (AVI), MPEG,
QT, and ASF. Also, various additional MIME types are detected.

Helper libraries perform the extraction. It is extendable by linking
against external extractors for additional file types.

The goal is to provide developers of indexing tools with a universal
library to obtain simple keywords to match against queries.
libextractor contains a shell command "extract" that, similar to the
well-known "file" command, can extract metadata from a file and print
the results to stdout.

Maintainer
Maintainer

jpegoptim is a utility for optimizing JPEG files. It provides lossless
optimization (based on optimizing the Huffman tables) and "lossy" optimization
based on setting a maximum quality factor.

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