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Interpreter
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Python default prompt - »> - The default Python prompt of the interactive shell. Often seen for code examples which can be executed interactively in the Python interpreter.“ (POG 2022)
- Snippet from Wikipedia: Interpreter (computing)
In computing, an interpreter is software that executes source code without first compiling it to machine code. An interpreted runtime environment differs from one that processes CPU-native executable code which requires translating source code before executing it. An interpreter may translate the source code to an intermediate format, such as bytecode. A hybrid environment may translate the bytecode to machine code via just-in-time compilation, as in the case of .NET and Java, instead of interpreting the bytecode directly.
Before the widespread adoption of interpreters, the execution of computer programs often relied on compilers, which translate and compile source code into machine code. Early runtime environments for Lisp and BASIC could parse source code directly. Thereafter, runtime environments were developed for languages (such as Perl, Raku, Python, MATLAB, and Ruby), which translated source code into an intermediate format before executing to enhance runtime performance.
Code that runs in an interpreter can be run on any platform that has a compatible interpreter. The same code can be distributed to any such platform, instead of an executable having to be built for each platform. Although each programming language is usually associated with a particular runtime environment, a language can be used in different environments. Interpreters have been constructed for languages traditionally associated with compilation, such as ALGOL, Fortran, COBOL, C and C++.
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Variables, Data Types, Control Structures, Loops, Functions, Modules, Packages, File Handling, Errors and Exceptions, Classes and Objects, Inheritance, Polymorphism, Encapsulation, Abstraction, Lists, Dictionaries, Tuples, Sets, String Manipulation, Regular Expressions, Comprehensions, Lambda Functions, Map, Filter, and Reduce, Decorators, Generators, Context Managers, Concurrency with Threads, Asynchronous Programming, Multiprocessing, Networking, Database Interaction, Debugging, Testing and Unit Testing, Virtual Environments, Package Management, Data Analysis, Data Visualization, Web Scraping, Web Development with Flask/Django, API Interaction, GUI Programming, Game Development, Security and Cryptography, Blockchain Programming, Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Robotics, Scientific Computing, Data Engineering, Cloud Computing, DevOps Tools, Performance Optimization, Design Patterns, Type Hints, Version Control with Git, Documentation, Internationalization and Localization, Accessibility, Configurations and Environments, Continuous Integration/Continuous Deployment, Algorithm Design, Problem Solving, Code Readability, Software Architecture, Refactoring, Integration with Other Languages, Microservices Architecture, Serverless Computing, Big Data Analysis, Internet of Things (IoT), Geospatial Analysis, Quantum Computing, Bioinformatics, Ethical Hacking, Artificial Intelligence, Augmented Reality and Virtual Reality, Blockchain Applications, Chatbots, Voice Assistants, Edge Computing, Graph Algorithms, Social Network Analysis, Time Series Analysis, Image Processing, Audio Processing, Video Processing, 3D Programming, Parallel Computing, Event-Driven Programming, Reactive Programming.
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