先说下：所谓的大文件并不是压缩文件有多大，几十兆的文件而是解压后几百兆。其中就遇到解压不成功的情况.、读小文件时成功，大文件时失败等
def unzip_to_txt_plus(zipfilename):
zfile = zipfile.ZipFile(zipfilename, 'r')
for filename in zfile.namelist():
data = zfile.read(filename)
# data = data.decode('gbk').encode('utf-8')
data = data.decode('gbk', 'ignore').encode('utf-8')
file = open(filename, 'w+b')
file.write(data)
file.close()
if __name__ == '__main__':
zipfilename = "E:\\share\\python_excel\\zip_to_database\\20171025.zip"
unzip_to_txt_plus(zipfilename)
注意参数：‘ignore' ，因为默认是严格编码，如果不加这个参数就会报错。
因为该函数已经把文件编成utf-8 所以后面读取文件时成功，下面贴出读取大文件代码(忽略数据库相关)
# - coding: utf-8 -
import csv
import linecache
import xlrd
import MySQLdb
def txt_todatabase(filename, linenum):
# with open(filename, "r", encoding="gbk") as csvfile:
# Read = csv.reader(csvfile)
# count =0
# for i in Read:
# # print(i)
# count += 1
# # print('hello')
# print(count)
count = linecache.getline(filename, linenum)
print(count)
# with open("new20171028.csv", "w", newline="") as datacsv:
# # dialect为打开csv文件的方式，默认是excel，delimiter="\t"参数指写入的时候的分隔符
# csvwriter = csv.writer(datacsv, dialect=("excel"))
# # csv文件插入一行数据，把下面列表中的每一项放入一个单元格（可以用循环插入多行）
# csvwriter.writerow(["A", "B", "C", "D"])
def bigtxt_read(filename):
with open(filename, 'r', encoding='utf-8') as data:
count =0
while 1:
count += 1
line = data.readline()
if 1000000 == count:
print(line)
if not line:
break
print(count)
if __name__ == '__main__':
filename = '20171025.txt'
txt_todatabase(filename, 1000000)
bigtxt_read(filename)
经过对比，发现两个速度基本一样快。两百万行的数据是没压力的。
