Python3 Standard Library Overview

The Python standard library is very large, covering a wide range of components. Using the standard library allows you to easily complete various tasks.

Below are some modules in the Python3 standard library:

os module: The os module provides many functions for interacting with the operating system, such as creating, moving, and deleting files and directories, and accessing environment variables.
sys module: The sys module provides functions related to the Python interpreter and system, such as interpreter version and path, and information related to stdin, stdout, and stderr.
time module: The time module provides functions for handling time, such as getting the current time, formatting dates and times, timing, etc.
datetime module: The datetime module provides more advanced date and time handling functions, such as handling time zones, calculating time differences, calculating date differences, etc.
random module: The random module provides functions for generating random numbers, such as generating random integers, floats, sequences, etc.
math module: The math module provides mathematical functions, such as trigonometric functions, logarithmic functions, exponential functions, constants, etc.
re module: The re module provides regular expression processing functions, which can be used for text search, replacement, splitting, etc.
json module: The json module provides JSON encoding and decoding functions, which can convert Python objects to JSON format and parse Python objects from JSON format.
urllib module: The urllib module provides functions for accessing web pages and handling URLs, including downloading files, sending POST requests, handling cookies, etc.

Operating System Interface

The os module provides many functions related to the operating system, such as file and directory operations.

Example

import os

# Get the current working directory
current_dir = os.getcwd()
print("Current working directory:", current_dir)

# List files in the directory
files = os.listdir(current_dir)
print("Files in the directory:", files)

It is recommended to use the import os style rather than from os import *, to ensure that the os.open() which varies by operating system does not override the built-in function open().

When using large modules like os, the built-in dir() and help() functions are very useful:

>>> import os
>>> dir(os)
<returns a list of all module functions>
>>> help(os)
<returns an extensive manual page created from the module's docstrings>

For daily file and directory management tasks, the shutil module provides an easy-to-use high-level interface:

>>> import shutil
>>> shutil.copyfile('data.db', 'archive.db')
>>> shutil.move('/build/executables', 'installdir')

File Wildcards

The glob module provides a function for generating file lists from directory wildcard searches:

Example

>>> import glob
>>> glob.glob('*.py')
['primes.py', 'random.py', 'quote.py']

Command Line Arguments

Common utility scripts often invoke command line arguments. These command line arguments are stored as a linked list in the argv variable of the sys module. For example, executing “python demo.py one two three” in the command line produces the following output:

Example

>>> import sys
>>> print(sys.argv)
['demo.py', 'one', 'two', 'three']

Error Output Redirection and Program Termination

sys also has stdin, stdout, and stderr attributes. Even when stdout is redirected, the latter can be used to display warnings and error messages.

Example

>>> sys.stderr.write('Warning, log file not found starting a new one\n')
Warning, log file not found starting a new one

Most scripts use sys.exit() for directed termination.

String Regular Matching

The re module provides regular expression tools for advanced string processing. For complex matching and processing, regular expressions provide concise and optimized solutions:

Example

>>> import re
>>> re.findall(r'\bf[a-z]*', 'which foot or hand fell fastest')
['foot', 'fell', 'fastest']
>>> re.sub(r'(\b[a-z]+) \1', r'\1', 'cat in the the hat')
'cat in the hat'

If only simple functionality is needed, you should first consider string methods, as they are very simple, easy to read, and debug:

>>> 'tea for too'.replace('too', 'two')
'tea for two'

Mathematics

The math module provides access to the underlying C function library for floating-point operations:

Example

>>> import math
>>> math.cos(math.pi / 4)
0.70710678118654757
>>> math.log(1024, 2)
10.0

random provides tools for generating random numbers.

Example

>>> import random
>>> random.choice(['apple', 'pear', 'banana'])
'apple'
>>> random.sample(range(100), 10)   # sampling without replacement
[30, 83, 16, 4, 8, 81, 41, 50, 18, 33]
>>> random.random()    # random float
0.17970987693706186
>>> random.randrange(6)    # random integer chosen from range(6)
4

Internet Access

There are several modules for accessing the internet and handling network communication protocols. The two simplest are urllib.request for handling data received from URLs and smtplib for sending emails:

Example

>>> from urllib.request import urlopen
>>> for line in urlopen('http://tycho.usno.navy.mil/cgi-bin/timer.pl'):
...     line = line.decode('utf-8')  # Decoding the binary data to text.
...     if 'EST' in line or 'EDT' in line:  # look for Eastern Time
...         print(line)

<BR>Nov. 25, 09:43:32 PM EST

>>> import smtplib
>>> server = smtplib.SMTP('localhost')
>>> server.sendmail('[email protected]', '[email protected]',
... """To: [email protected]
... From: [email protected]
...
... Beware the Ides of March.
... """)
>>> server.quit()

Note that the second example requires a mail server running locally.

Date and Time

The datetime module provides both simple and complex methods for date and time handling.

While supporting date and time algorithms, the implementation focuses on more efficient processing and formatted output.

Example

import datetime

# Get the current date and time
current_datetime = datetime.datetime.now()
print(current_datetime)

# Get the current date
current_date = datetime.date.today()
print(current_date)

# Format the date
formatted_datetime = current_datetime.strftime("%Y-%m-%d %H:%M:%S")
print(formatted_datetime)  # Output: 2023-07-17 15:30:45

The output is:

2023-07-17 18:37:56.036914
2023-07-17
2023-07-17 18:37:56

This module also supports timezone handling:

>>> # Import the date class from the datetime module
>>> from datetime import date
>>> now = date.today()    # Current date
>>> now
datetime.date(2023, 7, 17)
>>> now.strftime("%m-%d-%y. %d %b %Y is a %A on the %d day of %B.")
'07-17-23. 17 Jul 2023 is a Monday on the 17 day of July.'

>>> # Create a date object representing a birthday
>>> birthday = date(1964, 7, 31)
>>> age = now - birthday   # Calculate the time difference between two dates
>>> age.days             # The days attribute of the variable age, representing the number of days in the time difference
21535

Data Compression

The following modules directly support common data packaging and compression formats: zlib, gzip, bz2, zipfile, and tarfile.

>>> import zlib
>>> s = b'witch which has which witches wrist watch'
>>> len(s)
41
>>> t = zlib.compress(s)
>>> len(t)
37
>>> zlib.decompress(t)
b'witch which has which witches wrist watch'
>>> zlib.crc32(s)
226805979

Performance Measurement

Some users are interested in understanding the performance differences between different methods of solving the same problem. Python provides a measurement tool that provides direct answers to these questions.

For example, using tuple packing and unpacking to swap elements seems more attractive than using the traditional method. timeit proves that modern methods are faster.

>>> from timeit import Timer
>>> Timer('t=a; a=b; b=t', 'a=1; b=2').timeit()
0.57535828626024577
>>> Timer('a,b = b,a', 'a=1; b=2').timeit()
0.54962537085770791

Compared to the fine granularity of timeit, the profile and pstats modules provide time measurement tools for larger code blocks.

Testing Modules

One method of developing high-quality software is to develop test code for each function and test frequently during the development process.

The doctest module provides a tool that scans modules and executes tests based on docstrings embedded in the program.

Test construction is as simple as cutting and pasting its output into the docstring.

Through user-provided examples, it strengthens documentation and allows the doctest module to confirm whether the code’s results are consistent with the documentation:

def average(values):
    """Computes the arithmetic mean of a list of numbers.

    >>> print(average([20, 30, 70]))
    40.0
    """
    return sum(values) / len(values)

import doctest
doctest.testmod()   # Automatically verify embedded tests

The unittest module is not as easy to use as doctest, but it can provide a more comprehensive set of tests in a separate file:

import unittest

class TestStatisticalFunctions(unittest.TestCase):

    def test_average(self):
        self.assertEqual(average([20, 30, 70]), 40.0)
        self.assertEqual(round(average([1, 5, 7]), 1), 4.3)
        self.assertRaises(ZeroDivisionError, average, [])
        self.assertRaises(TypeError, average, 20, 30, 70)

unittest.main() # Calling from the command line invokes all tests

The above is just a part of the modules in the Python3 standard library. Many more modules can be found in the complete standard library documentation: https://docs.python.org/zh-cn/3/library/index.html