用正則匹配生成固定格式的隨機文本python

• 生成文本
• • 導入python包
  • 生成隨機數字--年齡
  • 生成隨機英文名
  • 生成隨機城市名
• 正則匹配
• • 構造重復字符串

生成文本

導入python包

import random import string import numpy as np import pandas as pd

生成隨機數字–年齡

age=[] for i in range(10, 100):num = random.randint(10,100)age.append(num) #age

生成隨機英文名

name=[] for i in range(100):name_str = ''.join(random.sample(string.ascii_letters, random.randint(3, 5)))name.append(name_str.capitalize()) #name

生成隨機城市名

city=[] for i in range(100):city_str=''.join(random.sample(string.ascii_letters, random.randint(5,7)))city.append(city_str.upper()) #city #age

age默認為2位數；

name默認為首字母大寫的3-5個英文字母；

city默認為5-7個大寫英文字母；

正則匹配

當你要匹配 一個/多個/任意個 數字/字母/非數字/非字母/某幾個字符/任意字符，想要 貪婪/非貪婪 匹配，想要捕獲匹配出來的 第一個/所有 內容的時候，python正則表達式小抄：

構造重復字符串

# data_raw Hi, I'm [Bob] and I from {SZ}, I'm (18) years old. Hello, I am [RPI], I'm (20) years old and I come from {GZ}. I born in {YuLin}. I'm (24), just call me [ATA]. I don't want to tell you my name, but I from {ShangHai}. Hey My name is [CZW], I live in {HangZhou}, what's your name? Hi, I'm [Tom] and I from {RY}, I'm (78) years old. Hello, I am [ABG], I'm (40) years old and I come from {HU}. I born in {Liuzhou}. I'm (24), just call me [HYU]. I don't want to tell you my name, but I from {Nanchang}. Hey My name is [YUN], I live in {WUHAN}, what's your name? Hi, I'm [Lily] and I from {BJ}, I'm (6) years old. Hello, I am [Yin], I'm (23) years old and I come from {guigang}. ## 構造重復字符串 with open('data_raw.txt') as f:essay=f.read()import re sen=essay.strip().split('\n') train_text=[] for i in range(len(age)):for row in sen:str1=rowages = re.sub(r'\(.*?\)','(%s)'%(random.choice(age)), str1)names = re.sub(r'\[.*?\]',f'[{random.choice(name)}]', str1)cities = re.sub(r'\{.*?\}','{%s}'%(random.choice(city)), str1)train_text.append(str1)#train_text random.shuffle(train_text)

如此，便可自己構造數據來進行NLP處理。

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