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浅谈Python中re.match()和re.search()的使用及区别

作者:SpiderLiH

这篇文章主要介绍了浅谈Python中re.match()和re.search()的使用及区别,具有很好的参考价值,希望对大家有所帮助。一起跟随小编过来看看吧

1.re.match()

re.match()的概念是从头匹配一个符合规则的字符串,从起始位置开始匹配,匹配成功返回一个对象,未匹配成功返回None。

包含的参数如下:

pattern: 正则模型

string : 要匹配的字符串

falgs : 匹配模式

match() 方法一旦匹配成功,就是一个match object对象,而match object对象有以下方法:

group() 返回被 RE 匹配的字符串

start() 返回匹配开始的位置

end() 返回匹配结束的位置

span()返回一个元组包含匹配 (开始,结束) 的位置

案例:

import re
# re.match 返回一个Match Object 对象
# 对象提供了 group() 方法,来获取匹配的结果
result = re.match("hello","hello,world")
if result:
  print(result.group())
else:
  print("匹配失败!")

输出结果:

hello

2.re.search()

re.search()函数会在字符串内查找模式匹配,只要找到第一个匹配然后返回,如果字符串没有匹配,则返回None。

格式:re.search(pattern, string, flags=0)

要求:匹配出文章阅读的次数

import re

ret = re.search(r"\d+", "阅读次数为 9999")
print(ret.group())

输出结果:

9999

3.match()和search()的区别:

match()函数只检测RE是不是在string的开始位置匹配,

search()会扫描整个string查找匹配

match()只有在0位置匹配成功的话才有返回,如果不是开始位置匹配成功的话,match()就返回none

举例说明:

import re
print(re.match('super', 'superstition').span())

(0, 5)

print(re.match('super','insuperable'))

None

print(re.search('super','superstition').span())

(0, 5)

print(re.search('super','insuperable').span())

(2, 7)

补充知识: jupyter notebook_主函数文件如何调用类文件

使用jupyter notebook编写python程序,rw_visual.jpynb是写的主函数,random_walk.jpynb是类(如图)。在主函数中将类实例化后运行会报错,经网络查找解决了问题,缺少Ipynb_importer.py这样一个链接文件。

解决方法:

1、在同一路径下创建名为Ipynb_importer.py的文件:File-->download as-->Python(.py),该文件内容如下:

#!/usr/bin/env python
# coding: utf-8
# In[ ]:
 
import io, os,sys,types
from IPython import get_ipython
from nbformat import read
from IPython.core.interactiveshell import InteractiveShell
 
class NotebookFinder(object):
  """Module finder that locates Jupyter Notebooks"""
  def __init__(self):
    self.loaders = {}
 
  def find_module(self, fullname, path=None):
    nb_path = find_notebook(fullname, path)
    if not nb_path:
      return
 
    key = path
    if path:
      # lists aren't hashable
      key = os.path.sep.join(path)
 
    if key not in self.loaders:
      self.loaders[key] = NotebookLoader(path)
    return self.loaders[key]
 
def find_notebook(fullname, path=None):
  """find a notebook, given its fully qualified name and an optional path
  This turns "foo.bar" into "foo/bar.ipynb"
  and tries turning "Foo_Bar" into "Foo Bar" if Foo_Bar
  does not exist.
  """
  name = fullname.rsplit('.', 1)[-1]
  if not path:
    path = ['']
  for d in path:
    nb_path = os.path.join(d, name + ".ipynb")
    if os.path.isfile(nb_path):
      return nb_path
    # let import Notebook_Name find "Notebook Name.ipynb"
    nb_path = nb_path.replace("_", " ")
    if os.path.isfile(nb_path):
      return nb_path
 
class NotebookLoader(object):
  """Module Loader for Jupyter Notebooks"""
  def __init__(self, path=None):
    self.shell = InteractiveShell.instance()
    self.path = path
 
  def load_module(self, fullname):
    """import a notebook as a module"""
    path = find_notebook(fullname, self.path)
 
    print ("importing Jupyter notebook from %s" % path)
 
    # load the notebook object
    with io.open(path, 'r', encoding='utf-8') as f:
      nb = read(f, 4)
 
 
    # create the module and add it to sys.modules
    # if name in sys.modules:
    #  return sys.modules[name]
    mod = types.ModuleType(fullname)
    mod.__file__ = path
    mod.__loader__ = self
    mod.__dict__['get_ipython'] = get_ipython
    sys.modules[fullname] = mod
 
    # extra work to ensure that magics that would affect the user_ns
    # actually affect the notebook module's ns
    save_user_ns = self.shell.user_ns
    self.shell.user_ns = mod.__dict__
 
    try:
     for cell in nb.cells:
      if cell.cell_type == 'code':
        # transform the input to executable Python
        code = self.shell.input_transformer_manager.transform_cell(cell.source)
        # run the code in themodule
        exec(code, mod.__dict__)
    finally:
      self.shell.user_ns = save_user_ns
    return mod
sys.meta_path.append(NotebookFinder())

2、在主函数中import Ipynb_importer

import matplotlib.pyplot as plt
import Ipynb_importer
 
from random_walk import RandomWalk
 
rw = RandomWalk()
rw.fill_walk()
plt.scatter(rw.x_values, rw.y_values, s=15)
plt.show()

3、运行主函数,调用成功

ps:random_walk.jpynb文件内容如下:

from random import choice
 
class RandomWalk():
  def __init__(self, num_points=5000):
    self.num_points = num_points
    self.x_values = [0]
    self.y_values = [0]
    
  def fill_walk(self):
    while len(self.x_values) < self.num_points:
      x_direction = choice([1,-1])
      x_distance = choice([0,1,2,3,4])
      x_step = x_direction * x_distance
      
      y_direction = choice([1,-1])
      y_distance = choice([0,1,2,3,4])
      y_step = y_direction * y_distance
      
      if x_step == 0 and y_step == 0:
        continue
        
      next_x = self.x_values[-1] + x_step
      next_y = self.y_values[-1] + y_step
      
      self.x_values.append(next_x)
      self.y_values.append(next_y)

运行结果:

以上这篇浅谈Python中re.match()和re.search()的使用及区别就是小编分享给大家的全部内容了,希望能给大家一个参考,也希望大家多多支持脚本之家。

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