Introduction¶
The “Python library” contains several different kinds of components.
It contains data types that would normally be considered part of the “core” of a language, such as numbers and lists. For these types, the Python language core defines the form of literals and places some constraints on their semantics, but does not fully define the semantics. (On the other hand, the language core does define syntactic properties like the spelling and priorities of operators.)
The library also contains built-in functions and exceptions — objects that can be used by all Python code without the need of an import statement. Some of these are defined by the core language, but many are not essential for the core semantics and are only described here.
The bulk of the library, however, consists of a collection of modules. There are many ways to dissect this collection. Some modules are written in C and built in to the Python interpreter; others are written in Python and imported in source form. Some modules provide interfaces that are highly specific to Python, like printing a stack trace; some provide interfaces that are specific to particular operating systems, such as access to specific hardware; others provide interfaces that are specific to a particular application domain, like the World Wide Web. Some modules are available in all versions and ports of Python; others are only available when the underlying system supports or requires them; yet others are available only when a particular configuration option was chosen at the time when Python was compiled and installed.
This manual is organized “from the inside out:” it first describes the built-in functions, data types and exceptions, and finally the modules, grouped in chapters of related modules.
This means that if you start reading this manual from the start, and skip to the next chapter when you get bored, you will get a reasonable overview of the available modules and application areas that are supported by the Python library. Of course, you don’t have to read it like a novel — you can also browse the table of contents (in front of the manual), or look for a specific function, module or term in the index (in the back). And finally, if you enjoy learning about random subjects, you choose a random page number (see module random ) and read a section or two. Regardless of the order in which you read the sections of this manual, it helps to start with chapter Built-in Functions , as the remainder of the manual assumes familiarity with this material.
Let the show begin!
Notes on availability¶
An “Availability: Unix” note means that this function is commonly found on Unix systems. It does not make any claims about its existence on a specific operating system.
If not separately noted, all functions that claim “Availability: Unix” are supported on macOS, which builds on a Unix core.
If an availability note contains both a minimum Kernel version and a minimum libc version, then both conditions must hold. For example a feature with note Availability: Linux >= 3.17 with glibc >= 2.27 requires both Linux 3.17 or newer and glibc 2.27 or newer.
WebAssembly platforms¶
The WebAssembly platforms wasm32-emscripten (Emscripten) and wasm32-wasi (WASI) provide a subset of POSIX APIs. WebAssembly runtimes and browsers are sandboxed and have limited access to the host and external resources. Any Python standard library module that uses processes, threading, networking, signals, or other forms of inter-process communication (IPC), is either not available or may not work as on other Unix-like systems. File I/O, file system, and Unix permission-related functions are restricted, too. Emscripten does not permit blocking I/O. Other blocking operations like sleep() block the browser event loop.
The properties and behavior of Python on WebAssembly platforms depend on the Emscripten-SDK or WASI-SDK version, WASM runtimes (browser, NodeJS, wasmtime), and Python build time flags. WebAssembly, Emscripten, and WASI are evolving standards; some features like networking may be supported in the future.
For Python in the browser, users should consider Pyodide or PyScript. PyScript is built on top of Pyodide, which itself is built on top of CPython and Emscripten. Pyodide provides access to browsers’ JavaScript and DOM APIs as well as limited networking capabilities with JavaScript’s XMLHttpRequest and Fetch APIs.
Process-related APIs are not available or always fail with an error. That includes APIs that spawn new processes ( fork() , execve() ), wait for processes ( waitpid() ), send signals ( kill() ), or otherwise interact with processes. The subprocess is importable but does not work.
The socket module is available, but is limited and behaves differently from other platforms. On Emscripten, sockets are always non-blocking and require additional JavaScript code and helpers on the server to proxy TCP through WebSockets; see Emscripten Networking for more information. WASI snapshot preview 1 only permits sockets from an existing file descriptor.
Some functions are stubs that either don’t do anything and always return hardcoded values.
Functions related to file descriptors, file permissions, file ownership, and links are limited and don’t support some operations. For example, WASI does not permit symlinks with absolute file names.
Что такое библиотеки в python
Normally, a library is a collection of books or is a room or place where many books are stored to be used later. Similarly, in the programming world, a library is a collection of precompiled codes that can be used later on in a program for some specific well-defined operations. Other than pre-compiled codes, a library may contain documentation, configuration data, message templates, classes, and values, etc.
A Python library is a collection of related modules. It contains bundles of code that can be used repeatedly in different programs. It makes Python Programming simpler and convenient for the programmer. As we don’t need to write the same code again and again for different programs. Python libraries play a very vital role in fields of Machine Learning, Data Science, Data Visualization, etc.
Working of Python Library
As is stated above, a Python library is simply a collection of codes or modules of codes that we can use in a program for specific operations. We use libraries so that we don’t need to write the code again in our program that is already available. But how it works. Actually, in the MS Windows environment, the library files have a DLL extension (Dynamic Load Libraries). When we link a library with our program and run that program, the linker automatically searches for that library. It extracts the functionalities of that library and interprets the program accordingly. That’s how we use the methods of a library in our program. We will see further, how we bring in the libraries in our Python programs.
Python standard library
The Python Standard Library contains the exact syntax, semantics, and tokens of Python. It contains built-in modules that provide access to basic system functionality like I/O and some other core modules. Most of the Python Libraries are written in the C programming language. The Python standard library consists of more than 200 core modules. All these work together to make Python a high-level programming language. Python Standard Library plays a very important role. Without it, the programmers can’t have access to the functionalities of Python. But other than this, there are several other libraries in Python that make a programmer’s life easier. Let’s have a look at some of the commonly used libraries:
- TensorFlow: This library was developed by Google in collaboration with the Brain Team. It is an open-source library used for high-level computations. It is also used in machine learning and deep learning algorithms. It contains a large number of tensor operations. Researchers also use this Python library to solve complex computations in Mathematics and Physics.
- Matplotlib: This library is responsible for plotting numerical data. And that’s why it is used in data analysis. It is also an open-source library and plots high-defined figures like pie charts, histograms, scatterplots, graphs, etc.
- Pandas: Pandas are an important library for data scientists. It is an open-source machine learning library that provides flexible high-level data structures and a variety of analysis tools. It eases data analysis, data manipulation, and cleaning of data. Pandas support operations like Sorting, Re-indexing, Iteration, Concatenation, Conversion of data, Visualizations, Aggregations, etc.
- Numpy: The name “Numpy” stands for “Numerical Python”. It is the commonly used library. It is a popular machine learning library that supports large matrices and multi-dimensional data. It consists of in-built mathematical functions for easy computations. Even libraries like TensorFlow use Numpy internally to perform several operations on tensors. Array Interface is one of the key features of this library.
- SciPy: The name “SciPy” stands for “Scientific Python”. It is an open-source library used for high-level scientific computations. This library is built over an extension of Numpy. It works with Numpy to handle complex computations. While Numpy allows sorting and indexing of array data, the numerical data code is stored in SciPy. It is also widely used by application developers and engineers.
- Scrapy: It is an open-source library that is used for extracting data from websites. It provides very fast web crawling and high-level screen scraping. It can also be used for data mining and automated testing of data.
- Scikit-learn: It is a famous Python library to work with complex data. Scikit-learn is an open-source library that supports machine learning. It supports variously supervised and unsupervised algorithms like linear regression, classification, clustering, etc. This library works in association with Numpy and SciPy.
- PyGame: This library provides an easy interface to the Standard Directmedia Library (SDL) platform-independent graphics, audio, and input libraries. It is used for developing video games using computer graphics and audio libraries along with Python programming language.
- PyTorch: PyTorch is the largest machine learning library that optimizes tensor computations. It has rich APIs to perform tensor computations with strong GPU acceleration. It also helps to solve application issues related to neural networks.
- PyBrain: The name “PyBrain” stands for Python Based Reinforcement Learning, Artificial Intelligence, and Neural Networks library. It is an open-source library built for beginners in the field of Machine Learning. It provides fast and easy-to-use algorithms for machine learning tasks. It is so flexible and easily understandable and that’s why is really helpful for developers that are new in research fields.
There are many more libraries in Python. We can use a suitable library for our purposes. Hence, Python libraries play a very crucial role and are very helpful to the developers.
Use of Libraries in Python Program
As we write large-size programs in Python, we want to maintain the code’s modularity. For the easy maintenance of the code, we split the code into different parts and we can use that code later ever we need it. In Python, modules play that part. Instead of using the same code in different programs and making the code complex, we define mostly used functions in modules and we can just simply import them in a program wherever there is a requirement. We don’t need to write that code but still, we can use its functionality by importing its module. Multiple interrelated modules are stored in a library. And whenever we need to use a module, we import it from its library. In Python, it’s a very simple job to do due to its easy syntax. We just need to use import.
Python Libraries Explained for Information
Numpy package comes with a wide collection of numerical functions that. While the python language reference describes the exact syntax and semantics of the python language, this library reference manual describes the standard library that is distributed with python.
Python Libraries Explained, Python libraries are called modules. Full list of libraries mentioned below.
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Библиотеки Python: Что это такое и как этим пользоваться?
Вас интересуют библиотеки Python? Для чего подходит библиотека Numpy, Python Django, TensorFlow Python и другие. Всё про библиотеки Python!
Обновлено: January 18, 2023
Когда мы говорим про библиотеку, то представляем себе дымчатый запах старых книг и уютную атмосферу внутри огромного помещения. Если бы библиотеки Python были в реальном мире, то мы бы увидели упорядоченные полки с модулями, которые вы могли бы брать и использовать в вашем коде. Именно поэтому, библиотеки Python принято считать источниками различного полезного функционала. Ведь разработчики чаще всего стараются избегать излишней траты времени на написание собственного кода, когда есть уже написанный и проверенный фрагмент кода из библиотеки.
В данном руководстве мы расскажем про самые популярные Python библиотеки, которые используют программисты для импорта и добавления модулей в свой код. Если вы один из тех, кто любит выполнять работу эффективно, то вы обязательно должны узнать, что именно эти библиотеки могут предложить!
Используя их, вы сможете писать код более эффективно и экономить время для других важных вещей. Однако давайте не будем спешить. Для начала нам стоит узнать, что на самом деле из себя представляет библиотека Python.
Содержание
Важные Концепты Для Обучения
Перед тем как начать разбор различных библиотек Python, давайте рассмотрим некоторые базовые концепты. Например, глубокое обучение (deep learning) — это процесс машинного обучения. Вы же знаете как люди учаться на своих ошибках? Это же применимо для компьютеров. Глубокое обучение нацелено на то, чтобы научить машину учиться на примерах.
Другим интересующим нас термином станет нейронная сеть, которая напоминает человеческий мозг. Каким образом? Что же, нейронные сети являются комбинацией алгоритмов, которые нацелены на подражание способности человека определять различные модели или примеры. Следовательно, эта концепция берёт биологию человека и применяет ее в мире программирования для распознавания изображений и речи (обычно только одного из вариантов).
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Что Такое Дополненная Реальность: Разбираемся в Работе AR
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Мечтаете стать преподавателем? Узнайте, как стать учителем со степенью и даже без неё, а также быть частью сообщества учителей.
Python или C++: что лучше? Давайте узнаем!
После прочтения этой статьи у вас сложится полное понимание того, какой язык программирования вам лучше выбрать Python или C++.
Что Такое Библиотеки Python?
Для начала вы должны понять, что библиотеки Python не очень сильно отличаются от обычных библиотек, где вы можете найти и взять интересующую вас книгу. Они схожи тем, что являются коллекциями источников информации.
Тем не менее, вместо книг, вы получаете модули, которые вы можете применить для вашего процесса программирования. Все профессиональные разработчики пользуются преимуществами модулей. Если существует простой способ сделать что-то, то почему бы не воспользоваться этим?
Как только вы начнёте искать Python библиотеки, то вы будете удивлены обилием огромного количества доступных оригинальных и сторонних модулей. Именно по этой причине, вам может быть сложно выбрать те, которые вам нужны в какой-то определённый момент. Если вы программист, который работает во многих сферах, то выбрать какую-то определённую библиотеку для вас будет той ещё головной болью.
Вы уже должны знать, что Python является очень гибким языком. Это настоящая находка в мире программирования, так как он может быть использованы в сфере науки о данных, веб-разработке и даже машинном обучении. Если вы новичок в программировании, то вы можете попробовать пройти некоторые онлайн-курсы, чтобы понять насколько этот язык полезен.
В общем и целом различные библиотеки Python включают в себя различные модули для определённых областей применения. Должны ли мы начать наше знакомство с TensorFlow, PyTorch, Numpy, Sklearn и другими популярными библиотеками?
Кстати, если вы испытываете проблемы с поиском работы в качестве программиста на Python, то мы можем порекомендовать вам прочитать немного информации про вопросы собеседования, которые часто задают работодатели. Если вы не сможете ответить на них, то вы вряд-ли будете подходить для этой работы. Кроме того, один из этих вопросов собеседования касается библиотеки Python. Поэтому можете прочитать данное руководство, а уже потом вернуться к этой части.
API и Python: Лучшие Библиотеки
API — является аббревиатурой для программного интерфейса приложения. Он позволяет открыть окно для взаимодействия между приложениями через машинное общение. Python имеет фреймворки, которые ускоряют процесс создания API. Поэтому наша миссия — кратко обсудить наиболее распространенные библиотеки Python из данного списка: