浅谈Python中re.match()和re.search()的使用及区别

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：