Table of Contents
argparse
shutil
glob
pprint
statistics
calendar
Home Backend Development Python Tutorial It's so useful! Share these built-in Python modules!

It's so useful! Share these built-in Python modules!

May 25, 2023 am 09:58 AM
python Built-in module

Its so useful! Share these built-in Python modules!

argparse

Python当中的argparse模块主要用于命令行的参数解析,可以帮助用户轻松地编写命令行接口,我们先来看一个例子。

import argparse
# 解析参数
parser = argparse.ArgumentParser()
parser.add_argument("name")
args = parser.parse_args()
# 打印结果
print(f'Hello {args.name}!')
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然后我们在终端当中运行以下的代码:

python python_package.py 俊欣
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就会出现以下的结果。

Hello 俊欣!
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要是我们忘记带上参数了,会自动出现如下的提示:

usage: python_package.py [-h] name
python_package.py: error: the following arguments are required: name
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当然我们也可以通过如下的命令行来查看需要添加什么样的参数。

python python_package.py -h
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出来的结果如下所示:

usage: python_package.py [-h] name
positional arguments:
name
optional arguments:
-h, --helpshow this help message and exit
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当然我们并不知道这个name的参数到底指的是什么,因为我们可以更改一下我们写的程序。

import argparse
# 解析参数
parser = argparse.ArgumentParser()
parser.add_argument("name", help="Enter your name")
args = parser.parse_args()
print(f'Hello {args.name}!')
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这样的话,我们再来运行一下如下的命令行:

python python_package.py -h
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output

usage: python_package.py [-h] name
positional arguments:
nameEnter your name
optional arguments:
-h, --helpshow this help message and exit
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有时候我们想要输入的不止一个参数,我们可以这样来做,

import argparse
# 解析参数
parser = argparse.ArgumentParser()
parser.add_argument("name", help="Enter your name")
parser.add_argument("age", help='Enter your age', type=int)
args = parser.parse_args()
born_year = 2022 - args.age
print(f'Hello {args.name}! You were borned in {born_year}.')
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我们通过终端输入如下的程序。

python python_package.py 俊欣 24
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output

Hello 俊欣! You were borned in 1998.
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shutil

shutil模块提供了大量的文件高级操作。特别是针对文件的拷贝、删除、移动、压缩和解压缩等操作,我们先来看一个例子:

import shutil
print(shutil.which("python"))
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output

路径......
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上面返回的是Python可执行程序的路径,文件移动的代码是shutil.move(src, dst)。

shutil.move("源路径", "目标路径")
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除此之外我们主要会用到的还有:

  • shutil.copyfile(src, dst): 复制文件
  • shutil.copytree(olddir, newdir, True/False):复制整个文件夹目录
  • shutil.rmtree(src): 递归删除一整个目录以及目录文件夹下的所有内容

glob

glob模块主要是用来查找符合特定规则的目录和文件,并将查找出来的结果返回到一个列表当中来。它还可以和正则通配符一起来使用,例如:

def choose_numbered_files(root="."):
return glob.glob(f"{root}/[0-9].*")
choose_numbered_files("images")
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返回的是在images路径下的带有数字的文件,结果如下:

['images\1.gif',
 'images\1.png',
 'images\2.gif',
 'images\2.png',
 'images\3.png',]
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上面用到的glob.glob()返回的是符合匹配条件的所有文件的路径,而glob.iglob()返回的是一个迭代对象,需要循环遍历获取每个元素之后得到符合匹配条件的所有文件的路径。

pprint

pprint模块提供了“美化打印”任意Python数据结构的功能,方便使用者阅读,要是用普通的print来打印的话,如下:

nested = [list("abcs"), list("sdff"), [1, 45, 4, 6, 7, 8], list(range(12))]
print(nested)
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output

[['a', 'b', 'c', 's'], ['s', 'd', 'f', 'f'], [1, 45, 4, 6, 7, 8], [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]]
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而用pprint模块来打印的话,如下:

from pprint import pprint
pprint(nested)
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output

[['a', 'b', 'c', 's'],
 ['s', 'd', 'f', 'f'],
 [1, 45, 4, 6, 7, 8],
 [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]]
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我们还能够对键值对类型的数据进行格式化的输出,代码如下:

import json
import pprint
from urllib.request import urlopen
with urlopen('https://pypi.org/pypi/sampleproject/json') as resp:
project_info = json.load(resp)['info']
pprint.pprint(project_info)
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output

{'author': 'A. Random Developer',
 'author_email': 'author@example.com',
 'bugtrack_url': None,
 'classifiers': [.......],
 'description': [.......],
 'description_content_type': 'text/markdown',
 'docs_url': None,
 'download_url': '',
 'downloads': {.........},
 'home_page': 'https://github.com/pypa/sampleproject',
 'keywords': 'sample setuptools development',
 'license': '',
 'maintainer': '',
 'maintainer_email': '',
 'name': 'sampleproject',
 'package_url': 'https://pypi.org/project/sampleproject/',
 'platform': '',
 'project_url': 'https://pypi.org/project/sampleproject/',
 'project_urls': ..........,
 'requires_dist': [..........],
 'requires_python': '>=3.5, <4',
 'summary': 'A sample Python project',
 'version': '2.0.0',
 'yanked': False,
 'yanked_reason': None}
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statistics

Python当中的statistics模块提供了更加完善的数据统计操作,例如对中位数的计算就提供了median_low()、median_high()两种方法,分别来计算数据的低中位数(偶数个样本时取中间两个数的较小者),代码如下:

statistics.median_low([1,3,5,7])
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output

3
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和高中位数(偶数个样本时取中间两个数的较大者),代码如下:

statistics.median_high([1,3,5,7])
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output

5
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除此之外,例如平均数、众数、标准差、方差等等都能够计算,例如:

x1 = statistics.mode([1,1,2,3,4,3,3,3,3])
print(x1)
x2 = statistics.mode(["a","b","c","d","d","a","a",])
print(x2)
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output

3
a
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calendar

Python当中的日历模块提供了对日期的一系列操作方法,并且可以生成日历,代码如下:

import calendar
print(calendar.calendar(2022))
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output

2022
January February March
Mo Tu We Th Fr Sa SuMo Tu We Th Fr Sa SuMo Tu We Th Fr Sa Su
12123456123456
 3456789 789 10 11 12 13 789 10 11 12 13
10 11 12 13 14 15 1614 15 16 17 18 19 2014 15 16 17 18 19 20
17 18 19 20 21 22 2321 22 23 24 25 26 2721 22 23 24 25 26 27
24 25 26 27 28 29 302828 29 30 31
31
 AprilMay June
Mo Tu We Th Fr Sa SuMo Tu We Th Fr Sa SuMo Tu We Th Fr Sa Su
 123 1 12345
 456789 10 2345678 6789 10 11 12
11 12 13 14 15 16 17 9 10 11 12 13 14 1513 14 15 16 17 18 19
18 19 20 21 22 23 2416 17 18 19 20 21 2220 21 22 23 24 25 26
25 26 27 28 29 30 23 24 25 26 27 28 2927 28 29 30
30 31
......
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当然我们也可以打印出某一个月份的日历,代码如下:

import calendar
print(calendar.month(2022, 3))
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output

March 2022
Mo Tu We Th Fr Sa Su
123456
 789 10 11 12 13
14 15 16 17 18 19 20
21 22 23 24 25 26 27
28 29 30 31
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calendar.isleap(year)是闰年则返回True,否则返回False,例如:

import calendar
print(calendar.isleap(2022))
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output

False
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