淺談Python中re.match()和re.search()的使用及區別
1.re.match()
re.match()的概念是從頭匹配一個符合規則的字串,從起始位置開始匹配,匹配成功返回一個物件,未匹配成功返回None。
包含的引數如下:
pattern: 正則模型
string : 要匹配的字串
falgs : 匹配模式
match() 方法一旦匹配成功,就是一個match object物件,而match object物件有以下方法:
group() 返回被 RE 匹配的字串
start() 返回匹配開始的位置
end() 返回匹配結束的位置
span()返回一個元組包含匹配 (開始,結束) 的位置
案例:
import re # re.match 返回一個Match Object 物件 # 物件提供了 group() 方法,來獲取匹配的結果 result = re.match("hello","hello,world") if result: print(result.group()) else: print("匹配失敗!")
輸出結果:
hello
2.re.search()
re.search()函式會在字串內查詢模式匹配,只要找到第一個匹配然後返回,如果字串沒有匹配,則返回None。
格式:re.search(pattern,string,flags=0)
要求:匹配出文章閱讀的次數
import re ret = re.search(r"\d+","閱讀次數為 9999") print(ret.group())
輸出結果:
9999
3.match()和search()的區別:
match()函式只檢測RE是不是在string的開始位置匹配,
search()會掃描整個string查詢匹配
match()只有在0位置匹配成功的話才有返回,如果不是開始位置匹配成功的話,match()就返回none
舉例說明:
import re
print(re.match('super','superstition').span())
(0,5)
print(re.match('super','insuperable'))
None
print(re.search('super',5)
print(re.search('super','insuperable').span())
(2,7)
補充知識: jupyter notebook_主函式檔案如何呼叫類檔案
使用jupyter notebook編寫python程式,rw_visual.jpynb是寫的主函式,random_walk.jpynb是類(如圖)。在主函式中將類例項化後執行會報錯,經網路查詢解決了問題,缺少Ipynb_importer.py
這樣一個連結檔案。解決方法:
1、在同一路徑下建立名為Ipynb_importer.py的檔案:File-->download as-->Python(.py),該檔案內容如下:
#!/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、在主函式中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、執行主函式,呼叫成功
ps:random_walk.jpynb檔案內容如下:
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([0,4]) 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)執行結果:
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