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Anaconda, Inc. compiles and builds the packages available in the Anaconda repository itself, and provides binaries for Windows 32/64 bit, Linux 64 bit and MacOS 64-bit (Intel, Apple Silicon). Anything available on PyPI may be installed into a Conda environment using pip, and Conda will keep track of what it has installed and what pip has installed.
An output of pip install virtualenv. Pip's command-line interface allows the install of Python software packages by issuing a command: pip install some-package-name. Users can also remove the package by issuing a command: pip uninstall some-package-name. pip has a feature to manage full lists of packages and corresponding version numbers ...
Jupyter Notebook, an IDE that supports markdown, Python, Julia, R and several other languages. Komodo IDE an IDE PHOTOS Python, Perl, PHP and Ruby. NetBeans, is written in Java and runs everywhere where a JVM is installed. Ninja-IDE, free software, written in Python and Qt, Ninja name stands for Ninja-IDE Is Not Just Another IDE
A Jupyter Notebook document is a JSON file, following a versioned schema, usually ending with the ".ipynb" extension. The main parts of the Jupyter Notebooks are: Metadata, Notebook format and list of cells. Metadata is a data Dictionary of definitions to set up and display the notebook. Notebook Format is a version number of the software.
64-bit versions of Windows cannot run 16-bit software. However, most 32-bit applications will work well. 64-bit users are forced to install a virtual machine of a 16- or 32-bit operating system to run 16-bit applications or use one of the alternatives for NTVDM. [40]
SciPy (pronounced / ˈ s aɪ p aɪ / "sigh pie" [2]) is a free and open-source Python library used for scientific computing and technical computing. [3]SciPy contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and engineering.
TensorFlow is available on 64-bit Linux, macOS, Windows, and mobile computing platforms including Android and iOS. [citation needed] Its flexible architecture allows for easy deployment of computation across a variety of platforms (CPUs, GPUs, TPUs), and from desktops to clusters of servers to mobile and edge devices.
Originally developed as an internal tool for a CTF team, [4] the developers later formed Vector 35 Inc. to turn Binary Ninja into a commercial product. Development began in 2015, and the first public version was released in July 2016.