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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]
Programmed input–output (also programmable input/output, programmed input/output, programmed I/O, PIO) is a method of data transmission, via input/output (I/O), between a central processing unit (CPU) and a peripheral device, [1] such as a Parallel ATA storage device. Each data item transfer is initiated by an instruction in the program ...
Perform I/O Operations in Parallel; Description from POSIX standard; Inside I/O Completion Ports by Mark Russinovich; Description from .NET Framework Developer's Guide; Asynchronous I/O and The Asynchronous Disk I/O Explorer; IO::AIO is a Perl module offering an asynchronous interface for most I/O operations; ACE Proactor
Since 7 October 2024, Python 3.13 is the latest stable release, and it and, for few more months, 3.12 are the only releases with active support including for bug fixes (as opposed to just for security) and Python 3.9, [55] is the oldest supported version of Python (albeit in the 'security support' phase), due to Python 3.8 reaching end-of-life.
In computing, vectored I/O, also known as scatter/gather I/O, is a method of input and output by which a single procedure call sequentially reads data from multiple buffers and writes it to a single data stream (gather), or reads data from a data stream and writes it to multiple buffers (scatter), as defined in a vector of buffers.
An alternative method is via instruction-based I/O which requires that a CPU have specialized instructions for I/O. [1] Both input and output devices have a data processing rate that can vary greatly. [2] With some devices able to exchange data at very high speeds direct access to memory (DMA) without the continuous aid of a CPU is required. [2]
Parallel I/O, in the context of a computer, means the performance of multiple input/output operations at the same time, for instance simultaneously outputs to storage devices and display devices. [1] It is a fundamental feature of operating systems .
Introduced in Python 2.2 as an optional feature and finalized in version 2.3, generators are Python's mechanism for lazy evaluation of a function that would otherwise return a space-prohibitive or computationally intensive list. This is an example to lazily generate the prime numbers: