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 reret = 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,typesfrom IPython import get_ipythonfrom nbformat import readfrom 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 modsys.meta_path.append(NotebookFinder())

2、在主函数中import Ipynb_importer

import matplotlib.pyplot as pltimport 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。