Python built in modules examples

Lareina 89 Published: 08/12/2024

Python built in modules examples

I'm happy to provide an answer in English!

Python is a versatile language that provides numerous built-in modules for performing various tasks, including data analysis, file manipulation, networking, and more. Here are some examples of the versatility of Python's built-in modules:

math module: This module contains mathematical functions like sin(), cos(), tan(), exp(), log(), etc. It also includes functions for calculating trigonometric identities, exponential and logarithmic values.

Example: import math; print(math.sin(3.14))

random module: This module provides functionality to generate random numbers, which is useful in simulations or data analysis. You can specify the range of the random number using the randint() function.

Example: import random; print(random.randint(1, 100))

statistics module: This module provides statistical functions like mean(), median(), mode(), and std() for calculating various statistics.

Example: from statistics import mean; scores = [90, 85, 92, 88]; print(mean(scores))

re module: This module is used to perform regular expression operations, which are useful in data processing and text manipulation.

Example: import re; string = 'Hello world!'; print(re.search('world', string).group())

datetime module: This module provides functions for working with dates and times. You can use it to parse dates, calculate time differences, or generate random timestamps.

Example: from datetime import date, timedelta; start_date = date.today(); end_date = start_date + timedelta(days=30); print(end_date)

csv module: This module provides functionality for reading and writing comma-separated values (CSV) files, which is useful in data analysis or processing.

Example: import csv; with open('data.csv', 'w') as file: writer = csv.writer(file); writer.writerow(['name', 'age']);

os module: This module provides functions for interacting with the operating system, such as working with files and directories, setting environment variables, or spawning new processes.

Example: import os; print(os.getcwd())

sys module: This module provides functions for interacting with the Python interpreter itself, such as getting information about modules, tracing program flow, or terminating the program.

Example: import sys; print(sys.version)

time module: This module provides functions for working with time and dates, including calculating time differences, generating random timestamps, or measuring execution times.

Example: import time; start_time = time.time(); print(time.sleep(2)); end_time = time.time(); print(end_time - start_time)

shutil module: This module provides functions for file and directory operations, such as copying files, deleting directories, or creating temporary directories.

Example: import shutil; shutil.copy('file1.txt', 'file2.txt')

These are just a few examples of the many built-in modules that Python provides. By leveraging these modules, you can write efficient, readable, and maintainable code for your projects.

Python built in modules list

I'd be happy to provide you with a comprehensive list of Python's built-in modules!

Python comes with many built-in modules that can help you achieve a wide range of tasks. These modules are part of the Python Standard Library and are available for use without having to install anything extra.

Here is an alphabetical list of some of the most commonly used Python built-in modules:

argparse: Used to create command-line interfaces. array: Provides support for arrays, which are similar to lists but with more control over the type of elements and memory usage. asyncio: Supports asynchronous I/O, allowing you to write single-threaded code that can handle multiple concurrent tasks. base64: Encodes and decodes binary data using Base64 encoding scheme. binascii: Provides functions for converting between strings and sequences of bytes. binomial: A module for generating binomial coefficients and computing probability distributions. bisect: Performs sorting and searching operations on arrays or lists. calendar: Used to create calendars and manipulate dates. cmath: Contains mathematical functions for complex numbers, trigonometry, and hyperbolic functions. collections: Provides various specialized container datatypes, such as deque, defaultdict, Counter, and OrderedDict. concurrent.futures: A high-level interface for asynchronously executing callables. contextlib: Provides context management protocol implementation. cookbook: Contains examples of how to use Python's standard library modules. copy: Makes a copy of one or more list, tuple, or dictionary items. csv: Supports reading and writing CSV (comma-separated values) files. datetime: Used for manipulating dates and times. diff_match_patch: A class used to create differencing, patching and merging functionality. dis: Provides support for disassembling Python bytecode into equivalent assembly code. distutils: The core package for distributing Python packages. doctest: Used for testing the documentation of a function using examples. email: Supports parsing, composing, and sending emails. encodings: Contains various encoding functions for converting text between different character sets. functools: Provides support for higher-order functions, including partial application. glob: Used to work with files based on shell-like patterns. heapq: A min-heap queue implemented as a list. hmac: Provides support for keyed-hashing algorithms (e.g., HMAC). html: Contains classes and functions for parsing and generating HTML documents. http: Used to create HTTP clients and servers. idlelib: Used by IDLE, Python's integrated development environment. imaplib: Supports accessing IMAP (Internet Message Access Protocol) mailboxes. inspect: Provides information about live objects, such as functions and modules. io: Contains classes for working with input/output operations. json: Used to create JSON (JavaScript Object Notation) parsers and generators. keyword: The set of reserved words in the Python language. lib2to3: The main package for the 2to3 conversion tool. logging: Provides support for logging events, with various levels of verbosity. mailbox: Supports working with email messages. math: Contains mathematical functions, such as trigonometry and hyperbolic functions. mimetools: Provides tools for working with MIME (Multipurpose Internet Mail Extensions) types. nntplib: Used to create NNTP (Network News Transfer Protocol) clients. numbers: Provides support for various numeric types, including integers, floats, and complex numbers. operator: Maps names of standard operators to their corresponding functions. optparse: The original command-line option parser in Python. os: Used to create operating system interfaces (e.g., for working with files). pstats: Provides support for profiling Python programs, which helps you identify performance bottlenecks. py_compile: Compiles and runs a given source file, possibly creating bytecode. ptyprocess: Provides tools for controlling pseudo-terminals. quart: Asynchronous web framework. re: Supports regular expressions (regex) operations. reprlib: Used to create representations of Python objects as strings. runpy: Run modules or scripts from the command line, like a simple batch file. site: Contains functions for manipulating the module search path and checking if a module is already imported. smtpd: Supports creating SMTP (Simple Mail Transfer Protocol) servers. snddevice: Used to create device drivers for playing or recording audio. socket: Provides support for working with network sockets, which allow programs to communicate over networks. sqlite3: Provides a SQL database engine in Python. statistics: Used to calculate statistical measures (e.g., mean, median, mode). stringprep: Contains functions for preparing strings to be used as IDs or labels. struct: Used to convert between strings of bytes and Python sequences. sys: Contains the main program-level functions that interact with the operating system.

These are just a few of the many built-in modules available in Python. Each module has its own unique set of functionalities, making it easier for you to write efficient, maintainable code.

Please let me know if you have any other questions or if there's anything else I can help you with!