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15 Python modules

Popularity：661 ℃/2024-09-06 10:27:41

This is the 15th in a series of Python tutorials; for more, visit my Python collection!

A module is actually a file (ending in .py). The advantage of using modules is that they are easy to maintain and reuse code.

To create a module, simply write a new text file and save it with a .py extension.

1 Introducing Modules

1.1 Importing the entire module

import mymodule
mymodule.some_function()

1.2 Importing a specific function or class

from mymodule import some_function
some_function()

1.3 Importing all content

from mymodule import *
some_function() # Call the function directly without prefixing the module

1.4 Use of aliases

import mymodule as mm
mm.some_function()

2 Common Modules

Python's standard library is very large and provides a large number of built-in modules to support a variety of programming tasks. Here's a list of some common modules and their main uses:

2.1 Standard library module

2.1.1 os

Operating system related functions such as reading environment variables, changing directories, etc.

import os
print(()) # Get the current working directory

2.1.2 sys

Some system-specific variables and functions, such as getting command line arguments, exiting the program, etc.

import sys
print() # Get command line arguments

2.1.3 math

Math functions such as square roots, logarithms, etc.

import math
print((16)) # Calculate square root

2.1.4 random

Generate random numbers.

import random
print((1, 100)) # Generate a random integer between 1 and 100

2.1.5 datetime

Date and time operations.

from datetime import datetime
print(()) # Get the current date and time.

2.1.6 re

Regular expression support.

import re
pattern = r'\d+'
result = (pattern, '123 abc 456')
print(result) # Output all strings that match a number

2.1.7 json

JSON encoding and decoding.

import json
data = {'name': 'John', 'age': 30}
json_str = (data)
print(json_str) # Convert the dictionary to a JSON string.

2.1.8 collections

Advanced container types such asdefaultdict, Counter, deque etc.

from collections import defaultdict
d = defaultdict(int)
d['a'] += 1
print(d['a']) # exports: 1

2.1.9 itertools

Iteration tool that provides efficient loop iterators.

import itertools
for x in (start=1).
    print(x)
    if x > 10.
        break # Count indefinitely until 10 is exceeded

2.1.10 functools

Higher-order function tools such as decorators, biased functions, etc.

from functools import lru_cache
@lru_cache(maxsize=None)
def fib(n):
    if n < 2:
        return n
    return fib(n-1) + fib(n-2)
print(fib(10))  # Calculate the Fibonacci series number10classifier for principles, items, clauses, tasks, research projects etc

2.1.11 pathlib

Modern interface for handling paths.

from pathlib import Path
p = Path('/etc') / 'passwd'
print(p) # Output: /etc/passwd

12. argparse

Parses command line arguments and options.

import argparse
parser = ()
parser.add_argument("--input", help="input file")
args = parser.parse_args()
print()

2.2 Third-party modules

In addition to the standard library, there are many third-party modules that can be installed and used, for example:

  • NumPy - Numerical calculations.
  • Pandas - Data analysis.
  • Matplotlib - Data visualization.
  • Requests - Sends an HTTP request.
  • Flask - Web development framework.
  • SQLAlchemy - Database abstraction layer.
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