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Using a shared compute engine, code can be run and displayed the same to multiple users in a Repl. [22] Repl environments have built-in source control via Git [23] on all Repls and users can switch branches, push files, and revert code. Replit allows for the pulling of code from a GitHub repository and linking Repls to GitHub repositories. [24]
In 1964, the expression READ-EVAL-PRINT cycle is used by L. Peter Deutsch and Edmund Berkeley for an implementation of Lisp on the PDP-1. [3] Just one month later, Project Mac published a report by Joseph Weizenbaum (the creator of ELIZA, the world's first chatbot) describing a REPL-based language, called OPL-1, implemented in his Fortran-SLIP language on the Compatible Time Sharing System (CTSS).
Visual Studio Code was first announced on April 29, 2015, by Microsoft at the 2015 Build conference. A preview build was released shortly thereafter. [13]On November 18, 2015, the project "Visual Studio Code — Open Source" (also known as "Code — OSS"), on which Visual Studio Code is based, was released under the open-source MIT License and made available on GitHub.
Visual Studio, with the Visual F# tools from Microsoft installed, can be used to create, run and debug F# projects. The Visual F# tools include a Visual Studio-hosted read–eval–print loop (REPL) interactive console that can execute F# code as it is written. Visual Studio for Mac also fully supports F# projects.
Deno and Node.js are both runtimes built on the V8 JavaScript engine developed by the Chromium Project, the engine used for Chromium and Google Chrome web browsers. They both have internal event loops and provide command-line interfaces for running scripts and a wide range of system utilities. Deno mainly deviates from Node.js in the following ...
Numba is used from Python, as a tool (enabled by adding a decorator to relevant Python code), a JIT compiler that translates a subset of Python and NumPy code into fast machine code. Pythran compiles a subset of Python 3 to C++ . [165] RPython can be compiled to C, and is used to build the PyPy interpreter of Python.
Node.js provides a way to create "add-ons" via a C-based API called N-API, which can be used to produce loadable (importable) .node modules from source code written in C/C++. [60] The modules can be directly loaded into memory and executed from within JS environment as simple CommonJS modules.
MicroPython was designed specifically to support the typical performance gap between microcontrollers and Python. [18] Python code is able to directly access and interact with hardware, with increased hardware possibilities that are not available using a normal Python application that is run on an operating system. [19]