这篇文章主要介绍“怎么通过Python实现批量数据提取”，在日常操作中，相信很多人在怎么通过Python实现批量数据提取问题上存在疑惑，小编查阅了各式资料，整理出简单好用的操作方法，希望对大家解答”怎么通过Python实现批量数据提取”的疑惑有所帮助！接下来，请跟着小编一起来学习吧！
配置需求
ImageMagick
tesseract-OCR
Python3.7
from PIL import Image as PI
import io
import os
import pyocr.builders
from cnocr import CnOcr
import xlwt
分析上图发现票据金额为“贰拾万元整”，数据金额为大写中文，因此在导入Excel之前我们需要将金额票据的数据转换成数字的格式，基于此，我们需要首先完成大写汉字和数字的转换。
def chineseNumber2Int(strNum: str): result = 0 temp = 1 # 存放一个单位的数字如：十万 count = 0 # 判断是否有chArr cnArr = ['壹', '贰', '叁', '肆', '伍', '陆', '柒', '捌', '玖'] chArr = ['拾', '佰', '仟', '万', '亿'] for i in range(len(strNum)): b = True c = strNum[i] for j in range(len(cnArr)): if c == cnArr[j]: if count != 0: result += temp count = 0 temp = j + 1 b = False break if b: for j in range(len(chArr)): if c == chArr[j]: if j == 0: temp *= 10 elif j == 1: temp *= 100 elif j == 2: temp *= 1000 elif j == 3: temp *= 10000 elif j == 4: temp *= 100000000 count += 1 if i == len(strNum) - 1: result += temp return result通过上述代码即可实现大写字母与数字的转换，例如输入“贰拾万元整”即可导出“200000”，再将其转换成数字后即可极大地简化表格的操作，也可以在完成表格操作的同时有利于数据归档。
接下来，我们需要分析发票的内部内容，分析下图可知，我们需要获取以下几个数据内容：“出票日期”、“汇票到账日期”、“票据号码”、“收款人”、“票据金额”、“出票人”，可以通过画图软件获取精准定位。
如图，小黑点即鼠标所在地，画图软件左下角即他的坐标。
提取出票日期
def text1(new_img): #提取出票日期 left = 80 top = 143 right = 162 bottom = 162 image_text1 = new_img.crop((left, top, right, bottom)) #展示图片 #image_text1.show() txt1 = tool.image_to_string(image_text1) print(txt1) return str(txt1)提取金额
def text2(new_img): #提取金额 left = 224 top = 355 right = 585 bottom = 380 image_text2 = new_img.crop((left, top, right, bottom)) #展示图片 #image_text2.show() image_text2.save("img/tmp.png") temp = ocr.ocr("img/tmp.png") temp="".join(temp[0]) txt2=chineseNumber2Int(temp) print(txt2) return txt2提取出票人
def text3(new_img): #提取出票人 left = 177 top = 207 right = 506 bottom = 231 image_text3 = new_img.crop((left, top, right, bottom)) #展示图片 #image_text3.show() image_text3.save("img/tmp.png") temp = ocr.ocr("img/tmp.png") txt3="".join(temp[0]) print(txt3) return txt3提取付款行
def text4(new_img): #提取付款行 left = 177 top = 274 right = 492 bottom = 311 image_text4 = new_img.crop((left, top, right, bottom)) #展示图片 #image_text4.show() image_text4.save("img/tmp.png") temp = ocr.ocr("img/tmp.png") txt4="".join(temp[0]) print(txt4) return txt4提取汇票到账日期
def text5(new_img): #提取汇票到日期 left = 92 top = 166 right = 176 bottom = 184 image_text5 = new_img.crop((left, top, right, bottom)) #展示图片 #image_text5.show() txt5 = tool.image_to_string(image_text5) print(txt5) return txt5提取票据单据
def text6(new_img): #提取票据号码 left = 598 top = 166 right = 870 bottom = 182 image_text6 = new_img.crop((left, top, right, bottom)) #展示图片 #image_text6.show() txt6 = tool.image_to_string(image_text6) print(txt6) return txt6在将数据全部提取完成之后，即进入设置环节，我们需要首先将所有账单文件进行提取，获取他们的文件名和路径。
ocr=CnOcr()tool = pyocr.get_available_tools()[0]filePath='img'img_name=[]for i,j,name in os.walk(filePath): img_name=name在获取完整后，即可进行数据导入Excel的操作。
count=1book = xlwt.Workbook(encoding='utf-8',style_compression=0)sheet = book.add_sheet('test',cell_overwrite_ok=True)for i in img_name: img_url = filePath+"/"+i with open(img_url, 'rb') as f: a = f.read() new_img = PI.open(io.BytesIO(a)) ## 写入csv col = ('年份','出票日期','金额','出票人','付款行全称','汇票到日期','备注') for j in range(0,7): sheet.write(0,j,col[j]) book.save('1.csv') shijian=text1(new_img) sheet.write(count,0,shijian[0:4]) sheet.write(count,1,shijian[5:]) sheet.write(count,2,text2(new_img)) sheet.write(count,3,text3(new_img)) sheet.write(count,4,text4(new_img)) sheet.write(count,5,text5(new_img)) sheet.write(count,6,text6(new_img)) count = count + 1至此，完整流程结束。
附上源码全部
from wand.image import Imagefrom PIL import Image as PIimport pyocrimport ioimport reimport osimport shutilimport pyocr.buildersfrom cnocr import CnOcrimport requestsimport xlrdimport xlwtfrom openpyxl import load_workbook def chineseNumber2Int(strNum: str): result = 0 temp = 1 # 存放一个单位的数字如：十万 count = 0 # 判断是否有chArr cnArr = ['壹', '贰', '叁', '肆', '伍', '陆', '柒', '捌', '玖'] chArr = ['拾', '佰', '仟', '万', '亿'] for i in range(len(strNum)): b = True c = strNum[i] for j in range(len(cnArr)): if c == cnArr[j]: if count != 0: result += temp count = 0 temp = j + 1 b = False break if b: for j in range(len(chArr)): if c == chArr[j]: if j == 0: temp *= 10 elif j == 1: temp *= 100 elif j == 2: temp *= 1000 elif j == 3: temp *= 10000 elif j == 4: temp *= 100000000 count += 1 if i == len(strNum) - 1: result += temp return result def text1(new_img): #提取出票日期 left = 80 top = 143 right = 162 bottom = 162 image_text1 = new_img.crop((left, top, right, bottom)) #展示图片 #image_text1.show() txt1 = tool.image_to_string(image_text1) print(txt1) return str(txt1)def text2(new_img): #提取金额 left = 224 top = 355 right = 585 bottom = 380 image_text2 = new_img.crop((left, top, right, bottom)) #展示图片 #image_text2.show() image_text2.save("img/tmp.png") temp = ocr.ocr("img/tmp.png") temp="".join(temp[0]) txt2=chineseNumber2Int(temp) print(txt2) return txt2 def text3(new_img): #提取出票人 left = 177 top = 207 right = 506 bottom = 231 image_text3 = new_img.crop((left, top, right, bottom)) #展示图片 #image_text3.show() image_text3.save("img/tmp.png") temp = ocr.ocr("img/tmp.png") txt3="".join(temp[0]) print(txt3) return txt3def text4(new_img): #提取付款行 left = 177 top = 274 right = 492 bottom = 311 image_text4 = new_img.crop((left, top, right, bottom)) #展示图片 #image_text4.show() image_text4.save("img/tmp.png") temp = ocr.ocr("img/tmp.png") txt4="".join(temp[0]) print(txt4) return txt4def text5(new_img): #提取汇票到日期 left = 92 top = 166 right = 176 bottom = 184 image_text5 = new_img.crop((left, top, right, bottom)) #展示图片 #image_text5.show() txt5 = tool.image_to_string(image_text5) print(txt5) return txt5def text6(new_img): #提取票据号码 left = 598 top = 166 right = 870 bottom = 182 image_text6 = new_img.crop((left, top, right, bottom)) #展示图片 #image_text6.show() txt6 = tool.image_to_string(image_text6) print(txt6) return txt6 ocr=CnOcr() tool = pyocr.get_available_tools()[0] filePath='img'img_name=[]for i,j,name in os.walk(filePath): img_name=namecount=1 book = xlwt.Workbook(encoding='utf-8',style_compression=0)sheet = book.add_sheet('test',cell_overwrite_ok=True) for i in img_name: img_url = filePath+"/"+i with open(img_url, 'rb') as f: a = f.read() new_img = PI.open(io.BytesIO(a)) ## 写入csv col = ('年份','出票日期','金额','出票人','付款行全称','汇票到日期','备注') for j in range(0,7): sheet.write(0,j,col[j]) book.save('1.csv') shijian=text1(new_img) sheet.write(count,0,shijian[0:4]) sheet.write(count,1,shijian[5:]) sheet.write(count,2,text2(new_img)) sheet.write(count,3,text3(new_img)) sheet.write(count,4,text4(new_img)) sheet.write(count,5,text5(new_img)) sheet.write(count,6,text6(new_img)) count = count + 1到此，关于“怎么通过Python实现批量数据提取”的学习就结束了，希望能够解决大家的疑惑。理论与实践的搭配能更好的帮助大家学习，快去试试吧！若想继续学习更多相关知识，请继续关注编程网网站，小编会继续努力为大家带来更多实用的文章！
