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Anaconda is a distribution of the Python and R programming languages for scientific computing (data science, machine learning applications, large-scale data processing, predictive analytics, etc.), that aims to simplify package management and deployment. The distribution includes data-science packages suitable for Windows, Linux, and macOS.
Conda is an open-source, [2] cross-platform, [3] language-agnostic package manager and environment management system. It was originally developed to solve package management challenges faced by Python data scientists, and today is a popular package manager for Python and R. [4][5] At first, Anaconda Python distribution was developed by Anaconda ...
Spyder is an open-source cross-platform integrated development environment (IDE) for scientific programming in the Python language. Spyder integrates with a number of prominent packages in the scientific Python stack, including NumPy, SciPy, Matplotlib, pandas, IPython, SymPy and Cython, as well as other open-source software. [ 4 ][ 5 ] It is ...
Python is a multi-paradigm programming language. Object-oriented programming and structured programming are fully supported, and many of their features support functional programming and aspect-oriented programming (including metaprogramming [ 70 ] and metaobjects). [ 71 ] Many other paradigms are supported via extensions, including design by ...
LibTIFF is a library for reading and writing Tag Image File Format (abbreviated TIFF) files. The set also contains command line tools for processing TIFFs. It is distributed in source code and can be found as binary builds for all kinds of platforms. The LibTIFF software was originally written by Sam Leffler while working for Silicon Graphics.
Python 2.6 was released to coincide with Python 3.0, and included some features from that release, as well as a "warnings" mode that highlighted the use of features that were removed in Python 3.0. [ 27 ] [ 10 ] Similarly, Python 2.7 coincided with and included features from Python 3.1, [ 28 ] which was released on June 26, 2009.
IronPython is implemented on top of the Dynamic Language Runtime (DLR), a library running on top of the Common Language Infrastructure that provides dynamic typing and dynamic method dispatch, among other things, for dynamic languages. [4] The DLR is part of the .NET Framework 4.0 and is also a part of Mono since version 2.4 from 2009. [5]
CUDA. In computing, CUDA (originally Compute Unified Device Architecture) is a proprietary [ 1 ] parallel computing platform and application programming interface (API) that allows software to use certain types of graphics processing units (GPUs) for accelerated general-purpose processing, an approach called general-purpose computing on GPUs ...