Files Operation in Python

# 基本的文件读写操作#-------------------------------------------------------------------------------------output = open(r'D:\text', 'w')       # 创建输出文件用于写操作input  = open('D:\text', 'r')        # 创建输入文件用于读操作, 第二个参数是默认值，可省略aString = input.read()               # 读取整个文件到一个字符串aString = input.read(N)              # 读取接下来的N个字符(字节)到一个字符串aString = input.readline()           # 读取下一行到一个字符串aList   = input.realines()           # 读取整个文件到一个字符串列表output.write(aString)                # 写入一个字符串(字节串)到文件output.writelines(aList)             # 将列表内所有字符串写入文件output.close()                       # 手动关闭output.flush()                       # 将输出缓冲区刷新到磁盘, 但不关闭文件anyFile.seek(N)                      # 修改文件指针指向偏移量N的位置for line in open('data'): use line   # 使用文件迭代器逐行读取open('f.txt', encoding = 'latin-1')  # Python 3.x Unicode文本文件(str字符串)open('f.bin', 'rb')                  # Python 3.x 字节文件(bytes字符串)codecs.open('f.txt', encoding = '')  # Python 2.x Unicode文本文件(Unicode字符串)open('f.bin', 'rb')                  # Python 2.x 字节文件(str字符串)#-------------------------------------------------------------------------------------#********************* some tips *************************# 1. 文件迭代器是最好的读取行工具# 2. 从文件读取的内容是字符串而不是对象# 3. 默认情况下文件时缓冲的并且可查找(允许从指定位置读写文件)# 4. close通常是可选的, 文件在进行收集(collection)之后会自动关闭#*********************************************************# 基本文件操作实践>>> myfile = open('myfile.txt', 'w')>>> myfile.write('Hello, Andy.\n')  13>>> myfile.close()>>> myfile = open('myfile.txt') # 'r'是默认的打开模式>>> myfile.readline()'Hello, Andy.\n'>>> myfile.readline()''>>> myfile.close()>>> text = open('myfile.txt').read() # 读取整个文件到一个字符串>>> text'Hello, Andy.\n'>>> for line in open('myfile.txt'): #使用文件迭代器...     print(line, end='')...Hello, Andy.>>># Storing Python Objects>>> X, Y, Z = 43, 44, 45 # Using unpacking>>> S = 'spam'>>> D = {'a':97, 'b':98}>>> L = ['Tom', 'Jerry', 'Andy']>>> f = open('data', 'w')>>> f.write('%s,%s,%s\n' % (X, Y, Z))9>>> f.write(S + '\n')5>>> f.write(str(D) + '$' + str(L) + '\n')44>>> f.close()>>> f = open('data')>>> f.read()"43,44,45\nspam\n{'a': 97, 'b': 98}$['Tom', 'Jerry', 'Andy']\n">>> f.close()>>> f = open('data')>>> line = f.readline()>>> line'43,44,45\n'>>> nums = line.split(',')>>> nums['43', '44', '45\n']>>> listNums = [int(x) for x in nums]>>> listNums[43, 44, 45]>>> X, Y, Z = listNums  # Assignment by seq unpacking>>> line = f.readline()>>> line'spam\n'>>> S = line.rstrip() # Remove end-of-line>>> S'spam'>>> line = f.readlime()>>> line"{'a': 97, 'b': 98}$['Tom', 'Jerry', 'Andy']\n">>> parts = line.split('$')>>> parts["{'a': 97, 'b': 98}", "['Tom', 'Jerry', 'Andy']\n"]>>> D = eval(parts[0])  # extract any object from a string, repr do the converse>>> D{'a':97, 'b':98}>>> L = eval(parts[1])>>> L['Tom', 'Jerry', 'Andy']# **************************************************************# Storing Native Python Objects: Using pickle>>> D = {'a':97, 'b':98}>>> f = open('data-pickle', 'wb')>>> import pickle>>> pickle.dump(D, f)   # Pickle any object to file>>> f.close()>>> f = open('data-pickle', 'rb')>>> D = pickle.load(f)  # Load any object from file>>> D{'a':97, 'b':98}>>> f.close()# **************************************************************# Storing Native Python Objects: Using shelve>>> D = {'a':97, 'b':98}>>> L = ['Tom', 'Jerry', 'Andy']>>> import shelve>>> db = shelve.open('data-shelve')>>> db['dict'] = D  # The key here must be strings and shoude be unique >>> db['list'] = L>>> db.close()      # 3 files will be created (data-shelve.bak, data-shelve.dat, data-shelve.dir)>>> db = shelve.open('data-shelve')>>> for key in db:...     print(key, '=>', db[key])...list => ['Tom', 'Jerry', 'Andy']dict => {'a': 97, 'b': 98}>>> db.close()# Update db (data-shelve)>>> db = shelve.open('data-shelve')# without writeback=true, so D['dict']['c'] = 99 will not work# https://docs.python.org/2/library/shelve.html#example >>> D = db['dict']  # Extract the copy>>> D['c'] = 99     # mutates the copy>>> db['dict'] = D  # Store the copy right back >>> db.close()>>> db = shelve.open('data-shelve')>>> db['dict']{'a': 97, 'c':99, 'b': 98}