Historically, Python uses the ANSI APIs for interacting with the Windows operating system, often via C Runtime functions. However, these have been long discouraged in favor of the UTF-16 APIs. Within the operating system, all text is represented as UTF-...| Python Enhancement Proposals (PEPs)
Source code: Lib/tracemalloc.py The tracemalloc module is a debug tool to trace memory blocks allocated by Python. It provides the following information: Traceback where an object was allocated, St...| Python documentation
Source code: Lib/genericpath.py, Lib/posixpath.py(for POSIX) and Lib/ntpath.py(for Windows). This module implements some useful functions on pathnames. To read or write files see open(), and for ac...| Python documentation
Python supports multiple ways to format text strings. These include %-formatting 1, str.format() 2, and string.Template 3. Each of these methods have their advantages, but in addition have disadvantages that make them cumbersome to use in practice. This...| Python Enhancement Proposals (PEPs)
PEP 484 introduced type hints, a.k.a. type annotations. While its main focus was function annotations, it also introduced the notion of type comments to annotate variables:| Python Enhancement Proposals (PEPs)
The CPython interpreter scans the command line and the environment for various settings. CPython implementation detail: Other implementations’ command line schemes may differ. See Alternate Impleme...| Python documentation
The growth of Internet and general connectivity has triggered the proportionate need for responsive and scalable code. This proposal aims to answer that need by making writing explicitly asynchronous, concurrent Python code easier and more Pythonic.| Python Enhancement Proposals (PEPs)
This module provides access to some variables used or maintained by the interpreter and to functions that interact strongly with the interpreter. It is always available. Unless explicitly noted oth...| Python documentation
PEP 492 introduced support for native coroutines and async/await syntax to Python 3.5. It is proposed here to extend Python’s asynchronous capabilities by adding support for asynchronous generators.| Python Enhancement Proposals (PEPs)
The following sections describe the standard types that are built into the interpreter. The principal built-in types are numerics, sequences, mappings, classes, instances and exceptions. Some colle...| Python documentation
>>>, The default Python prompt of the interactive shell. Often seen for code examples which can be executed interactively in the interpreter.,,..., Can refer to:- The default Python prompt of the i...| Python documentation
Source code: Lib/pathlib/ This module offers classes representing filesystem paths with semantics appropriate for different operating systems. Path classes are divided between pure paths, which pro...| Python documentation
Source code: Lib/string.py String constants: The constants defined in this module are: Custom String Formatting: The built-in string class provides the ability to do complex variable substitutions ...| Python documentation
Source code: Lib/os.py This module provides a portable way of using operating system dependent functionality. If you just want to read or write a file see open(), if you want to manipulate paths, s...| Python documentation
PEP 3107 introduced syntax for function annotations, but the semantics were deliberately left undefined. There has now been enough 3rd party usage for static type analysis that the community would benefit from a standard vocabulary and baseline tools w...| Python Enhancement Proposals (PEPs)
Source code: Lib/datetime.py The datetime module supplies classes for manipulating dates and times. While date and time arithmetic is supported, the focus of the implementation is on efficient attr...| Python documentation
The Python interpreter has a number of functions and types built into it that are always available. They are listed here in alphabetical order.,,,, Built-in Functions,,, A, abs(), aiter(), all(), a...| Python documentation
Objects, values and types: Objects are Python’s abstraction for data. All data in a Python program is represented by objects or by relations between objects. (In a sense, and in conformance to Von ...| Python documentation
