14 projects tagged "Python Modules"
Berkeley DB XML is a native XML database engine for use within your product. Made available as a C++ library with language bindings for Java, Perl, Python, PHP, and Tcl, it integrates directly into your application (it is not a standalone database server). It provides XQuery access into a database of document containers. XML documents are stored and indexed in their native format using Berkeley DB as the transactional database engine.
ACDK is a development framework with a similar target of Microsoft's .NET or Sun's ONE platform, but it uses C++ as a core implementation language. It implements the standard library packages, including acdk::lang, acdk::lang::reflect, acdk::util, acdk::io, acdk::text (including regexpr), acdk::net, acdk::sql, acdk::xml, and more. Flexible allocator/garbage collection, threading, and Unicode are implemented in the core of ACDK. Extensions make C++ objects available for reflection, serialization, aspect-oriented class attributes, and [D]ynamic [M] ethod [I]nvocation. This DMI acts as an universal object oriented call interface to connect C++ with scripting languages (Java, Perl, Tcl, Python, Lisp, Visual Basic, and VBScript) and standard component technologies (CORBA and COM).
Opticks Extras is a set of official extensions for the Opticks application. The Spectral Processing extension adds multi-spectral and hyper-spectral processing capability to Opticks. The IDL Scripting extension integrates an IDL interpreter directly into the Opticks application. The Python Scripting Extension integrates a Python interpreter directly into the Opticks application.
py-xmlrpc is an extremely fast implementation of the xmlrpc spec for Python (written in C). It supports both blocking and non-blocking clients and servers on Windows and POSIX platforms. Version 0.8.1 is 100% compliant with the xmlrpc validator found at http://validator.xmlrpc.com.
The Maximum Entropy Toolkit provides a set of tools and library for constructing maximum entropy (maxent) models in either Python or C++. It features conditional maximum entropy models, L-BFGS and GIS parameter estimation, Gaussian Prior smoothing, a C++ API, a Python extension module, a command line utility, and good documentation.
The eGenix mxODBC Zope Database Adapter (Zope DA) allows you to easily connect your Zope installation to just about any database backend. Unlike Zope's ZODBC Zope DA, the mxODBC Zope DA works on Windows, Linux, and Solaris using the same interface. It implements thread-safe connection pooling and multiple physical connects per logical Zope connection. You can safely run Z SQL Methods in parallel, achieving much better performance than ZODBC Zope DA or similar database adapters under heavy load. This makes it ideal for deployment in clusters and hosting environments where stability and high performance are a priority.