Search Results for "tk-4" - Page 2
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Showing 46 open source projects for "tk-4"
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Design and development of visual programming interface to allow specification, loading, execution and termination of specified simulation runs. It should be capable of allowing secure remote control flow setup, execution / termination of simulation jobs
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Cloud Target is a front-end to the python scripts that google uses to create, run and upload projects to its App Server system. This .NET application is based on the OSX front-end provided by Google in the SDK.
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Simple Distributed Job Management Tools facilitates parallel, distributed execution of simple commands, on a network of UNIX-like machines. Components include a job dependency/exclusivity language and load-balanced remote execution facility.
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Python DB driver for Java JDBC. Allows CPython programs to use a java JDBC driver to connect with a database server. It's API is Python DB compliant. ZJdbcDA (a zope database adapter) is also included.
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iROS is a meta-operating system for technology-rich "interactive rooms". The core components (Event Heap, DataHeap, iCrafter) provide communication, data storage, and service management for an iRoom.
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A Console-based BitTorrent Client with built-in scheduler for handling multiple sessions. It is designed to manage sessions in queue easily without heavy-weight GUI. External module can search for new torrents in trackers and submit it automatically.
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phpMyLibrary is a PHP MySQL Library automation application. The program consist of cataloging, circulation, and the webpac module. The programs also has an import export feature. The program strictly follow the USMARC standard for adding materials.
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This library provides a network abstraction layer for heterogenous large scale modular systems. It supports clearly specified interface definitions for communication between modules, while maximizing module indendence and adaptability.
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Dispyte is an expendable, fault tolerant task scheduler which distributes computationally expensive tasks across a heterogeneous network.
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Cheshire3 is a fast Z39.50, SRW, XML search engine, written in Python for extensability and using C libraries for speed. Next generation of the Cheshire system (http://cheshire.berkeley.edu) and designed around a distributable, object oriented model.
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The Job Jar is a simple batch queuing system for Unix. Its main distinguishing feature is that there is no central daemon. Instead, an arbitrary set of workers cooperatively claim jobs from a central directory. A job is any Unix executable file.
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distX is a script which can be used to distribute CPU intensive tasks to a cluster of machines. For example, distX has been used for distributed encoding of ogg vorbis files.
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The purpose of this program is to prove that given a finite number of Monkeys and a finite amount of time one monkey will be able to make more money off the stock market than any human being. Checkout our web site for an uncorrupted download.
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OpenLC is a set tools designed to facilitate benchmarking and stress testing of a wide variety of information servers (WEB, Email, FTP, LDAP, ...). A XML-RPC API is offered for developers interested in creating clients that query the services provid
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DPytHOS is a means for administrators of large networks to both monitor and manage the servers under their control. DPytHOS is implemented in python and uses a generic database back-end (with MySQL supported and MS-SQL 2000 supported via XML)
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This package provides Python bindings to the OpenPBS C API. All functions of the OpenPBS C library can be accessed in Python through the use of this package. We provide extensive documentation on the usage and lots of examples.
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Named after a well know product from Microsoft, SandStorm is a framework for creating modular middle-end web products.
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Pluster is a cluster management software developed with python. It is easy to install and maintain. Pluster Provides cluster performance monitoring and remote OS installing. It's future will be an agent-based management system.
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StreamMine is a distributed event processing (streaming) infrastructure. You can create low-latency, fault-tolerant stream processing functionality with any stream-oriented operators that can be implemented in Python.
