git-flow Python Edition is a a pure Python implementation of git-flow. All sub-commands share a common back-end to ensure features behave the same, whatever branch-type they are working on. New workflow behavior can also be added easily by simply sub-classing existing ones. It also includes a comprehensive unit test suite, decent man pages, and HTML docs.
WTMParse is a script originally intended for use in forensic examinations which parses WTMP files from Unix-like operating systems and generates a CSS-styled HTML report containing the login terminal, username, log start date, and login time/date in a table. It's good for postmortem forensic examinations or as a way of getting "last"-like information when you don't have the ability to boot the machine in question but can grab the wtmp.
Meson aims to be the most usable and fast build system. It provides a simple yet powerful mostly declarative language for describing your build. It has native support for modern tools and frameworks, such as Qt5, code coverage, unit tests, precompiled headers, and others. It utilizes a host of optimization techniques to compile your code faster on both full and incremental builds.
Django-live-profiler is a low-overhead data access and code profiler for Django-based applications. Profiling Web applications on a development environment often produces misleading results due to different patterns in the data, different patterns in user behavior, and differences in infrastructure. All existing DB access profiling solutions for Django seem to focus on a single request, but in the real world certain queries might be negligible in a single request while still putting a considerable strain the database across all requests. Django-live-profiler aims to solve these issues by collecting database usage data from a live application.
The Pegasus Workflow Management System encompasses a set of technologies which help workflow-based applications execute in a number of different environments, including desktops, campus clusters, grids, and clouds. It bridges the scientific domain and the execution environment by automatically mapping high-level workflow descriptions onto distributed resources. It automatically locates the necessary input data and computational resources necessary for workflow execution. It enables scientists to construct workflows in abstract terms without worrying about the details of the underlying execution environment or the particulars of the low-level specifications required by the middleware (Condor, Globus, or Amazon EC2). It bridges the current cyberinfrastructure by effectively coordinating multiple distributed resources.
Libcolumbus is a small error tolerant search engine designed to deal with noisy data and typos. It will power the searches in the next generation of Ubuntu's HUD system as well as other searches. It has a fast implementation of the Levenshtein distance algorithm, which allows it to correct errors such as added and dropped letters (e.g. 'bar' -> 'bard'), changed letters ('ctr' -> 'car') and translations ('acr' -> 'car'). It also allows the user to customize the error values. Libcolumbus is designed to be small, efficient and easy to embed. It is programmed in C++ but also provides C and Python APIs.