Open Source Python Software Development Software

LASS : Library of Assembled Shared Source. Library of C++ code for scientific purposes.

BTK contains C++ and Python libraries that implement speech processing and microphone array techniques such as speech feature extraction, speech enhancement, speaker tracking, beamforming, dereverberation and echo cancellation algorithms. The Millennium ASR provides C++ and python libraries for automatic speech recognition. The Millennium ASR implements a weighted finite state transducer (WFST) decoder, training and adaptation methods. These toolkits are meant for facilitating research and development of automatic distant speech recognition.

BiBler is a software for managing references to scientific articles using BibTeX. BiBler runs with a windows GUI or can be used as a Python library

GluCat is a generic library of C++ templates that implement universal Clifford algebras over the field of real numbers. The PyClical extension module for Python gives users an easy Python scripting interface for calculations in Clifford algebras. The name PyClical is an homage to Pertti Lounesto's CLICAL.

Pretty Damn Quick (PDQ) analytically solves queueing network models of computer and manufacturing systems, data networks, etc., written in conventional programming languages. Generic or customized reports of predicted performance measures are output.

PyLogAnalyzer is a tool that receives an input log in black and white, a configuration INI file, which contains the list of rules to process the input, and an output file where to save the results. These rules permit to detect an input line according to a regular expression (regex) or line number range, filter it, pass it, colorise in foreground and background, columnise the groups of the regex and enable or disable the rule. The final goal of this tool is to ameliorate reading long and difficult b/w logs, speed up the analysis and enhance day to day wearying activities. As common application, you can colorise adb logcat logs taking the example files and using them (and also, filter unnecessary lines). You can INSTALL it from PyPI: $ python -m pip install pyloganalyser

https://sourceforge.net/p/contools/contools/ci/master/tree/README.md https://sourceforge.net/p/contools/contools/ci/master/tree/README_EN.txt https://sourceforge.net/p/contools/contools/ci/master/tree/README_EN.deps.txt https://sourceforge.net/p/contools/contools/ci/master/tree/changelog.txt

THIS PROJECT MIGRATED TO https://gitlab.com/mwetoolkit/mwetoolkit3/ The Multiword Expressions toolkit aids in the automatic identification and extraction of multiword units in running text. These include idioms (kick the bucket), noun compounds (cable car), phrasal verbs (take off, give up), etc. Even though it focuses on multiword expresisons, the framework is quite complete and can also be useful in any corpus-based study in computational linguistics. The mwetoolkit can be applied to virtually any text collection, language, and MWE type. It is a command-line tool written mostly in Python. Its development started in 2010 as a PhD thesis but the project keeps active (see the SVN logs). Up-to-date documentation and details about the tool can be found on the mwetoolkit website: http://mwetoolkit.sourceforge.net/