{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "w 是以写的方式打开文件 write\n", "a 是以追加的方式打开文件 append\n", "r 是读的方式打开文件 read" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "poem = '\\n让我们一起学习AI python\\n'\n", "f = open('./test/poem.txt', 'a')\n", "f.write(poem)\n", "f.close()" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "让我们一起学习AI python\n", "\n", "让我们一起学习AI python\n", "\n" ] } ], "source": [ "f = open('./test/poem.txt', 'r')\n", "data = f.read()\n", "print(data)\n", "f.close()" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "让我们一起学习AI python\n", "\n", "让我们一起学习AI python\n", "\n" ] } ], "source": [ "with open('./test/poem.txt', 'r') as f:\n", " data = f.read()\n", " print(data)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "readline方法每次读出一行内容,所以读取时占用的内存小,比较适合大文件" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "\n", "让我们一起学习AI python\n", "\n", "\n", "\n", "让我们一起学习AI python\n", "\n" ] } ], "source": [ "f = open('./test/poem.txt', 'r')\n", "line = f.readline()\n", "while line:\n", " print(line)\n", " line = f.readline()\n", "f.close()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "readlines方法读取整个文件所有行,保存在一个列表变量中,每行对于列表的一个元素,但是读取大文件会比较占内存" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "\n", "让我们一起学习AI python\n", "\n", "\n", "\n", "让我们一起学习AI python\n", "\n" ] } ], "source": [ "f = open('./test/poem.txt', 'r')\n", "lines = f.readlines()\n", "for line in lines:\n", " print(line)\n", "f.close()" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "collapsed": true }, "outputs": [], "source": [ "poem = '\\n让我们一起学习AI python\\n'\n", "f = open('./test/poem.txt', 'w', encoding='utf-8')\n", "f.write(poem)\n", "f.close()" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "\n", "让我们一起学习AI python\n", "\n" ] } ], "source": [ "f = open('./test/poem.txt', 'r', encoding='utf-8')\n", "line = f.readline()\n", "while line:\n", " print(line)\n", " line = f.readline()\n", "f.close()" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.3" } }, "nbformat": 4, "nbformat_minor": 2 }