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A library can be used by multiple, independent consumers (programs and other libraries). This differs from resources defined in a program which can usually only be used by that program. When a consumer uses a library resource, it gains the value of the library without having to implement it itself. Libraries encourage code reuse in a modular ...
To use such libraries from another language, usually of higher-level, such as Java, Common Lisp, Scheme, Python, or Lua, a binding to the library must be created in that language, possibly requiring recompiling the language's code, depending on the amount of modification needed. [2]
This is the philosophy that is used in the C and C++ standard libraries. By contrast, Guido van Rossum, designer of Python, has embraced a much more inclusive vision of the standard library. Python attempts to offer an easy-to-code, object-oriented, high-level language. [citation needed] In the Python tutorial, he writes:
Python (programming language) scientific libraries (36 P) Pages in category "Python (programming language) libraries" The following 43 pages are in this category, out of 43 total.
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.
While code is the most common resource selected for reuse, other assets generated during the development cycle may offer opportunities for reuse: software components, test suites, designs, documentation, and so on. [7] The software library is a good example of code reuse. Programmers may decide to create internal abstractions so that certain ...
The term assembly (as in .NET languages like C#, F# or Visual Basic .NET) or package (as in Dart, Go or Java) is sometimes used instead of module.In other implementations, these are distinct concepts; in Python a package is a collection of modules, while in Java 9 the introduction of the new module concept (a collection of packages with enhanced access control) was implemented.
The Natural Language Toolkit, or more commonly NLTK, is a suite of libraries and programs for symbolic and statistical natural language processing (NLP) for English written in the Python programming language. It supports classification, tokenization, stemming, tagging, parsing, and semantic reasoning functionalities. [4]