The Python Papers Anthology
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TMSTAF The Extended Use of STAF on Test Automation
Get PDFAs software packages becomes increasingly large and complex, the time required for testing them, throughout the development lifecycle, has also increased. Because testing activities consume the majority of software Quality Assurance (QA) resources, a test platform was needed to speed up test cycles without any decrease in test result accuracy. The use of Python 2.6 scripting language to create a faster, automated testing platform is reported here. Trend Micro Software Testing Automation Framework (TMSTAF) was developed using Python 2.6, based on Software Testing Automation Framework (STAF), to improve automated testing. We found that TMSTAF not only decreased testing time, it provided faster process integration, test feedback, and improved overall software quality. Using the TMSTAF automation environment for development and execution is simple to set up. Test cases can be created for use in both manual and automated tasks, converted to automated scripts, and implemented with structural and flexible mechanisms. Automation script pre-runs and debugging make troubleshooting more efficiently; TMSTAF test report data can be used to identify quality issues quickly. TMSTAF can be seamlessly integrated into the build release process, making it a smart option for software QA engineers
Designing and Testing PyZMQ Applications
Get PDFPyZMQ is a powerful and easy-to-use network layer. While ZeroMQ and PyZMQ are quite well documented and good introductory tutorials exist, no best-practice guide on how to design and especially to test larger or more complex PyZMQ applications could be found. This article shows a possible way to design, document and test real-world applications. The approach presented in this article was used for the development of a distributed simulation framework and proved to work quite well in this scenario
FUSEing Python for Development of Storage Efficient Filesystem
Get PDFFilesystem is a core component of a functional operating system. Traditional Filesystem development has been confined to the kernel space. A customized, purpose-built, and user-driven Filesystem development involves extensive knowledge of kernel internals, tools and processes. Alternatively, user-space Filesystems are preferred over the kernel space Filesystem, for ease of development, portability and developing prototypes Filesystems, particularly for intuitive abstraction of non-file objects. This paper proposes usage of FUSE kernel module to develop a functional Filesystem in user-space, titled seFS. Apart from offering convenience of user-space development, FUSE allows on-par features and functionality of a kernel space Filesystem. We demonstrate development of a Filesystem in Python on Ubuntu 11.04 system with Python-Fuse bindings. seFS Filesystem abstracts a SQLite database to store files data and metadata. By developing a Filesystem with Python-FUSE, we quickly solved the problem of efficient data management with online de-duplication and data compression. We discuss the internals of FUSE, its operation and implementation in this paper
An Artificial Life Simulation Library Based on Genetic Algorithm, 3-Character Genetic Code and Biological Hierarchy
Get PDFGenetic algorithm (GA) is inspired by biological evolution of genetic organisms by optimizing the genotypic combinations encoded within each individual with the help of evolutionary operators, suggesting that GA may be a suitable model for studying real-life evolutionary processes. This paper describes the design of a Python library for artificial life simulation, Digital Organism Simulation Environment (DOSE), based on GA and biological hierarchy starting from genetic sequence to population. A 3-character instruction set that does not take any operand is introduced as genetic code for digital organism. This mimics the 3-nucleotide codon structure in naturally occurring DNA. In addition, the context of a 3-dimensional world composing of ecological cells is introduced to simulate a physical ecosystem. Using DOSE, an experiment to examine the changes in genetic sequences with respect to mutation rates is presented
Ragaraja 1.0: The Genome Interpreter of Digital Organism Simulation Environment (DOSE)
Get PDFThis manuscript documents the implementation of Ragaraja interpreter version 1.0, the 3-character genetic code interpreter in Digital Organisms Simulation Environment (DOSE). These codes are licensed under Python Software Foundation License version 2
High-Speed Data Shredding using Python
Get PDFIn recent years, backup and restore is a common topic in data storage. However, theres hardly anybody mention about safe data deletion. Common data destruction methodology requires the wipe operation to fill the disk with zeros, then with random data, and then with zeros again. Three passes are normally sufficient for ordinary home users. On the down side, such algorithms will take many hours to delete a 2TB hard disk. Although current Linux utility tools gives most users more than enough security and data protections, we had developed a cross-platform standalone application that could expunge all confidential data stored in flash drive or hard disk. The data shredding software is written in Python, and it could overwrite existing data using user-defined wipe algorithm. This software project also explores the technical approaches to digital data destruction using various methodologies defined in different standards, which includes a selection of military-grade procedures proposed by information security specialists. The application operates with no limitations to the capacity of the storage media connected to the computer system, it can rapidly and securely erase any magnetic mediums, optical disks or solid-state memories found in the computer or embedded system. Not only does the software comply with the IEEE T10/T13 specifications, it also binds to the number of connectivity limited by the SAS/SATA buses
A Python Wrapper Code Generator for Dynamic Libraries
Get PDFWe introduce a new Python code generator for conveniently and transparently wrapping native dynamic libraries. The presented code generator is used in several projects for scientific collaboration and can be adapted to other projects fairly easily
Python for Education: The Exact Cover Problem
Get PDFPython implementation of Algorithm X by Knuth is presented.Algorithm X finds all solutions to the exact cover problem.The exemplary results for pentominoes, Latin squares and Sudokuare given
Evaluation of aspect-oriented frameworks in Python for extending a project with provenance documentation features
Get PDFIn this paper we describe two sides of a real life use case of introducing an aspect-oriented framework into an industrial-grade project. This paper is divided into two parts: the selection process for an AOP framework in the Python programming language, and its use for modularized non-invasive recording of provenance data in a distributed data management tool. Criteria for the choice of such a framework are discussed and the background of provenance documentation is laid out