Скачать или смотреть Python is the Language-Like Interface of an Abstract Machine

In this video, Zach begins by asking, “What is a machine?” and then walks through explanations of machine interfaces, layers of abstraction, and the language-like quality of programming languages. Finally, at the end of the video, Zach addresses the difference between two major parts of the official Python documentation (the Language Reference and Library Reference).

In summary:

A machine is a device that converts energy into useful work. A user manipulates a machine in order to actualize its potential, and in order to manipulate the machine, the user needs an interface.

An interface is a functional representation of the potential of a machine, and a machine with greater potential tends to come with a more complex interface.

A computer is a machine that is designed to process logical operations. At its bottommost level - the hardware - a computer offers incomprehensibly vast potential. Computer hardware would require an impractically large and complex interface if that interface were built physically (like an airplane cockpit).

We solve this complexity problem using layers of abstraction (i.e. by building abstract machines on top of lower-level machines). Each abstract machine offers an additional interface through which it can be manipulated by higher-level machines. More abstract machines have less potential than lower-level machines, but the potential that they retain is easier for users to actualize.

The Python programming language is a language-like interface to the Python abstract machine.

The Python interface is language-like because language is abstraction-agnostic. In other words, language is equally as effective at any level of abstraction as long as it refers to real things.

Because these interfaces - programming languages - are language-like, they have a syntax. You can learn about the Python syntax by reviewing the official Python Language Reference.

Like a Swiss army knife, the standard Python installation includes many different tools. The official Python Library Reference explains how to use each specific tool.
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