PyQt is a set of Python v2 and v3 bindings for Digia's Qt application framework and runs on all platforms supported by Qt including Windows, MacOS/X and Linux. PyQt5 supports Qt v5. PyQt4 supports Qt v4 and will build against Qt v5. The bindings are implemented as a set of Python modules and contain over 620 classes.
Like Qt, PyQt is available on all platforms under a variety of licenses including the GNU GPL v3 and a commercial license. Unlike Qt, PyQt is not available under the LGPL. You can purchase the commercial version of PyQt here.
PyQt does not include a copy of Qt. You must obtain a correctly licensed copy of Qt yourself. However, a binary Windows installers of the GPL version of both PyQt5 and PyQt4 are provided and this includes a copy of the LGPL version of Qt.
SymPy is a Python library for symbolic mathematics. It aims to become a full-featured computer algebra system (CAS) while keeping the code as simple as possible in order to be comprehensible and easily extensible. SymPy is written entirely in Python and does not require any external libraries.
We focus on scientific/engineering software development using RAD abilities of Python language, accompanied with free scientific libraries such as NumPy and SciPy. Our mainstream research activity is numerical optimization, including nonsmooth optimization and solving systems of nonlinear equations. OpenOpt framework - universal numerical optimization package with several own solvers (e.g. ralg) and connections to tens of other, graphical output of convergence and many other goodies FuncDesigner - tool to rapidly build functions over variables/arrays and get their derivatives via automatic differentiation. Also, you can perform integration, interpolation, solve systems of linear/nonlinear/ODE equations and numerical optimization problems coded in FuncDesigner by OpenOpt (see some examples in its doc), uncertainty analysis and interval analysis DerApproximator - tool to get (or check user-supplied) derivatives via finite-difference approximation SpaceFuncs - tool for 2D, 3D, N-dimensional geometric modeling with possibilities of parametrized calculations, numerical optimization and solving systems of geometrical equations
Python(x,y) is a free scientific and engineering development software for numerical computations, data analysis and data visualization based on Python programming language, Qt graphical user interfaces, Eclipse integrated development environment and Spyder interactive scientific development environment.
SciPy (pronounced "Sigh Pie") is open-source software for mathematics, science, and engineering. It is also the name of a very popular conference on scientific programming with Python. The SciPy library depends on NumPy, which provides convenient and fast N-dimensional array manipulation. The SciPy library is built to work with NumPy arrays, and provides many user-friendly and efficient numerical routines such as routines for numerical integration and optimization. Together, they run on all popular operating systems, are quick to install, and are free of charge. NumPy and SciPy are easy to use, but powerful enough to be depended upon by some of the world's leading scientists and engineers. If you need to manipulate numbers on a computer and display or publish the results, give SciPy a try!