Open Source Python Libraries for Mac

Originally developed by Google for internal use, TensorFlow is an open source platform for machine learning. Available across all common operating systems (desktop, server and mobile), TensorFlow provides stable APIs for Python and C as well as APIs that are not guaranteed to be backwards compatible or are 3rd party for a variety of other languages. The platform can be easily deployed on multiple CPUs, GPUs and Google's proprietary chip, the tensor processing unit (TPU). TensorFlow expresses its computations as dataflow graphs, with each node in the graph representing an operation. Nodes take tensors—multidimensional arrays—as input and produce tensors as output. The framework allows for these algorithms to be run in C++ for better performance, while the multiple levels of APIs let the user determine how high or low they wish the level of abstraction to be in the models produced. Tensorflow can also be used for research and production with TensorFlow Extended.

A collection of open source libraries and tools that provide solutions for common problems in processing Arabic text, especially in web applications. text normalization, phrase segmentation, text indexing, stop word lists, common spelling mistakes.

That project aims at providing a clean API and a simple implementation, as a C++ library, of an Airline-related Inventory Management system. That library uses the Standard Airline IT C++ object model (http://sf.net/projects/stdair).

That project aims at providing a clean API, and the corresponding C++ implementation, for the basis of Airline IT Business Object Model (BOM), ie, to be used by several other Open Source projects, such as RMOL, Air-Sched, Travel-CCM, OpenTREP, etc.

A mature cross-platform C++ library for use as a default application framework. Features include: * Threading & synchronization * Socket programming: SSL, NanoMsg & ZMQ * File I/O utilities: zlib, ini, yaml * Native Database access: MySQL, SQLite, BerkleyDB, Postgre, REDIS and ODBC * Built-in mini XML parser; optional EXPAT, LIBXML and MSXML support * Network protocol stack: HTTP, FTP, SMTP, POP3, SOAP, XMLRPC * Scripting languages: Perl, Python, JavaScript, VBScript, Java, Lua, TCL, Squirrel * Cloud Computing: AWS * Encryption: OpenSSL * Platforms: Linux/Posix, Windows, Arduino * Over 500+ highly reusable classes. 4000+ fully documented functions. Follow the 'Wiki' link above to explore everything about the framework.

Web gallery based on pre-generated metadata, typically according to directory structure, not database or an administration. Development moved to: http://github.com/martinkozak/fsgal.

Simple and rapid Application builder, built on top of Flask. includes detailed security, auto form generation, google charts and much more. Demo on: http://flaskappbuilder.pythonanywhere.com/

That project aims at delivering a reference implementation of a library, estimating and serving average prices paid for air travel products. It is not intended for use by an actual airline, but rather by simulators or other airline-related modules of

Modern software systems and application are commonly written in multiple languages, include scripting engines, and are frequently build on multiple specialized frameworks and middleware for a considerable diversity of runtime environments. The latest influencing update in development paradigm is the application of multicore processors. This projects is aimed to unify the required trace and logging output and integrate into debugging environments. The target is to provide general development, test, and production support of software environments based on multiple programming languages for distributed multicore environments.