有几种办法呈现程序输出；数据可以按人类可读形式打印，或写入文件以供未来使用。本章节将讨论一些可能性。
So far we’ve encountered two ways of writing values: expression statements 和 print statement. (A third way is using the write() method of file objects; the standard output file can be referenced as sys.stdout . See the Library Reference for more information on this.)
Often you’ll want more control over the formatting of your output than simply printing space-separated values. There are two ways to format your output; the first way is to do all the string handling yourself; using string slicing and concatenation operations you can create any layout you can imagine. The string types have some methods that perform useful operations for padding strings to a given column width; these will be discussed shortly. The second way is to use the str.format() 方法。
The string module contains a Template class which offers yet another way to substitute values into strings.
One question remains, of course: how do you convert values to strings? Luckily, Python has ways to convert any value to a string: pass it to the repr() or str() 函数。
The str() function is meant to return representations of values which are fairly human-readable, while repr() is meant to generate representations which can be read by the interpreter (or will force a SyntaxError if there is no equivalent syntax). For objects which don’t have a particular representation for human consumption, str() will return the same value as repr() . Many values, such as numbers or structures like lists and dictionaries, have the same representation using either function. Strings and floating point numbers, in particular, have two distinct representations.
一些范例：
>>> s = 'Hello, world.' >>> str(s) 'Hello, world.' >>> repr(s) "'Hello, world.'" >>> str(1.0/7.0) '0.142857142857' >>> repr(1.0/7.0) '0.14285714285714285' >>> x = 10 * 3.25 >>> y = 200 * 200 >>> s = 'The value of x is ' + repr(x) + ', and y is ' + repr(y) + '...' >>> print s The value of x is 32.5, and y is 40000... >>> # The repr() of a string adds string quotes and backslashes: ... hello = 'hello, world\n' >>> hellos = repr(hello) >>> print hellos 'hello, world\n' >>> # The argument to repr() may be any Python object: ... repr((x, y, ('spam', 'eggs'))) "(32.5, 40000, ('spam', 'eggs'))"
Here are two ways to write a table of squares and cubes:
>>> for x in range(1, 11): ... print repr(x).rjust(2), repr(x*x).rjust(3), ... # Note trailing comma on previous line ... print repr(x*x*x).rjust(4) ... 1 1 1 2 4 8 3 9 27 4 16 64 5 25 125 6 36 216 7 49 343 8 64 512 9 81 729 10 100 1000 >>> for x in range(1,11): ... print '{0:2d} {1:3d} {2:4d}'.format(x, x*x, x*x*x) ... 1 1 1 2 4 8 3 9 27 4 16 64 5 25 125 6 36 216 7 49 343 8 64 512 9 81 729 10 100 1000
(Note that in the first example, one space between each column was added by the way print works: it always adds spaces between its arguments.)
This example demonstrates the str.rjust() method of string objects, which right-justifies a string in a field of a given width by padding it with spaces on the left. There are similar methods str.ljust() and str.center() . These methods do not write anything, they just return a new string. If the input string is too long, they don’t truncate it, but return it unchanged; this will mess up your column lay-out but that’s usually better than the alternative, which would be lying about a value. (If you really want truncation you can always add a slice operation, as in x.ljust(n)[:n] )。
There is another method, str.zfill() , which pads a numeric string on the left with zeros. It understands about plus and minus signs:
>>> '12'.zfill(5) '00012' >>> '-3.14'.zfill(7) '-003.14' >>> '3.14159265359'.zfill(5) '3.14159265359'
基本用法的 str.format() 方法看起来像这样:
>>> print 'We are the {} who say "{}!"'.format('knights', 'Ni') We are the knights who say "Ni!"
The brackets and characters within them (called format fields) are replaced with the objects passed into the str.format() method. A number in the brackets refers to the position of the object passed into the str.format() 方法。
>>> print '{0} and {1}'.format('spam', 'eggs') spam and eggs >>> print '{1} and {0}'.format('spam', 'eggs') eggs and spam
If keyword arguments are used in the str.format() method, their values are referred to by using the name of the argument.
>>> print 'This {food} is {adjective}.'.format( ... food='spam', adjective='absolutely horrible') This spam is absolutely horrible.
Positional and keyword arguments can be arbitrarily combined:
>>> print 'The story of {0}, {1}, and {other}.'.format('Bill', 'Manfred', ... other='Georg') The story of Bill, Manfred, and Georg.
'!s' (apply str() ) 和 '!r' (apply repr() ) can be used to convert the value before it is formatted.
>>> import math >>> print 'The value of PI is approximately {}.'.format(math.pi) The value of PI is approximately 3.14159265359. >>> print 'The value of PI is approximately {!r}.'.format(math.pi) The value of PI is approximately 3.141592653589793.
An optional ':' and format specifier can follow the field name. This allows greater control over how the value is formatted. The following example rounds Pi to three places after the decimal.
>>> import math >>> print 'The value of PI is approximately {0:.3f}.'.format(math.pi) The value of PI is approximately 3.142.
Passing an integer after the ':' will cause that field to be a minimum number of characters wide. This is useful for making tables pretty.
>>> table = {'Sjoerd': 4127, 'Jack': 4098, 'Dcab': 7678} >>> for name, phone in table.items(): ... print '{0:10} ==> {1:10d}'.format(name, phone) ... Jack ==> 4098 Dcab ==> 7678 Sjoerd ==> 4127
If you have a really long format string that you don’t want to split up, it would be nice if you could reference the variables to be formatted by name instead of by position. This can be done by simply passing the dict and using square brackets '[]' to access the keys
>>> table = {'Sjoerd': 4127, 'Jack': 4098, 'Dcab': 8637678} >>> print ('Jack: {0[Jack]:d}; Sjoerd: {0[Sjoerd]:d}; ' ... 'Dcab: {0[Dcab]:d}'.format(table)) Jack: 4098; Sjoerd: 4127; Dcab: 8637678
This could also be done by passing the table as keyword arguments with the ‘**’ notation.
>>> table = {'Sjoerd': 4127, 'Jack': 4098, 'Dcab': 8637678} >>> print 'Jack: {Jack:d}; Sjoerd: {Sjoerd:d}; Dcab: {Dcab:d}'.format(**table) Jack: 4098; Sjoerd: 4127; Dcab: 8637678
This is particularly useful in combination with the built-in function vars() , which returns a dictionary containing all local variables.
For a complete overview of string formatting with str.format() ，见 格式字符串语法 .
The % operator can also be used for string formatting. It interprets the left argument much like a sprintf() -style format string to be applied to the right argument, and returns the string resulting from this formatting operation. For example:
>>> import math >>> print 'The value of PI is approximately %5.3f.' % math.pi The value of PI is approximately 3.142.
可以找到更多信息在 字符串格式化操作 章节。
open() returns a file object, and is most commonly used with two arguments: open(filename, mode) .
>>> f = open('workfile', 'w') >>> print f <open file 'workfile', mode 'w' at 80a0960>
第 1 自变量是包含文件名的字符串。第 2 自变量是包含描述文件使用方式的一些字符的另一字符串。 mode 可以是 'r' 当只读文件时， 'w' 为只写 (将擦除具有相同名称的现有文件)，和 'a' 打开文件以供追加；将要写入文件的任何数据自动添加到末尾。 'r+' 打开文件以供读取和写入两者。 mode 自变量是可选的； 'r' 会被假定若省略。
在 Windows， 'b' appended to the mode opens the file in binary mode, so there are also modes like 'rb' , 'wb' ，和 'r+b' . Python on Windows makes a distinction between text and binary files; the end-of-line characters in text files are automatically altered slightly when data is read or written. This behind-the-scenes modification to file data is fine for ASCII text files, but it’ll corrupt binary data like that in JPEG or EXE files. Be very careful to use binary mode when reading and writing such files. On Unix, it doesn’t hurt to append a 'b' to the mode, so you can use it platform-independently for all binary files.
The rest of the examples in this section will assume that a file object called f has already been created.
To read a file’s contents, call f.read(size) , which reads some quantity of data and returns it as a string. size is an optional numeric argument. When size is omitted or negative, the entire contents of the file will be read and returned; it’s your problem if the file is twice as large as your machine’s memory. Otherwise, at most size bytes are read and returned. If the end of the file has been reached, f.read() will return an empty string ( "" ).
>>> f.read() 'This is the entire file.\n' >>> f.read() ''
f.readline() reads a single line from the file; a newline character ( \n ) is left at the end of the string, and is only omitted on the last line of the file if the file doesn’t end in a newline. This makes the return value unambiguous; if f.readline() returns an empty string, the end of the file has been reached, while a blank line is represented by '\n' , a string containing only a single newline.
>>> f.readline() 'This is the first line of the file.\n' >>> f.readline() 'Second line of the file\n' >>> f.readline() ''
For reading lines from a file, you can loop over the file object. This is memory efficient, fast, and leads to simple code:
>>> for line in f: print line, This is the first line of the file. Second line of the file
If you want to read all the lines of a file in a list you can also use list(f) or f.readlines() .
f.write(string) writes the contents of string to the file, returning None .
>>> f.write('This is a test\n')
To write something other than a string, it needs to be converted to a string first:
>>> value = ('the answer', 42) >>> s = str(value) >>> f.write(s)
f.tell() returns an integer giving the file object’s current position in the file, measured in bytes from the beginning of the file. To change the file object’s position, use f.seek(offset, from_what) . The position is computed from adding offset to a reference point; the reference point is selected by the from_what argument. A from_what value of 0 measures from the beginning of the file, 1 uses the current file position, and 2 uses the end of the file as the reference point. from_what can be omitted and defaults to 0, using the beginning of the file as the reference point.
>>> f = open('workfile', 'r+') >>> f.write('0123456789abcdef') >>> f.seek(5) # Go to the 6th byte in the file >>> f.read(1) '5' >>> f.seek(-3, 2) # Go to the 3rd byte before the end >>> f.read(1) 'd'
When you’re done with a file, call f.close() to close it and free up any system resources taken up by the open file. After calling f.close() ，试图使用文件对象会自动失败。
>>> f.close() >>> f.read() Traceback (most recent call last): File "<stdin>", line 1, in ? ValueError: I/O operation on closed file Traceback (most recent call last): File "<stdin>", line 1, in ? ValueError: I/O operation on closed file
是很好实践使用 with keyword when dealing with file objects. This has the advantage that the file is properly closed after its suite finishes, even if an exception is raised on the way. It is also much shorter than writing equivalent try - finally 块：
>>> with open('workfile', 'r') as f: ... read_data = f.read() >>> f.closed True
File objects have some additional methods, such as isatty() and truncate() which are less frequently used; consult the Library Reference for a complete guide to file objects.
Strings can easily be written to and read from a file. Numbers take a bit more effort, since the read() method only returns strings, which will have to be passed to a function like int() , which takes a string like '123' and returns its numeric value 123. When you want to save more complex data types like nested lists and dictionaries, parsing and serializing by hand becomes complicated.
Rather than having users constantly writing and debugging code to save complicated data types to files, Python allows you to use the popular data interchange format called JSON (JavaScript 对象表示法) . The standard module called json can take Python data hierarchies, and convert them to string representations; this process is called serializing . Reconstructing the data from the string representation is called deserializing . Between serializing and deserializing, the string representing the object may have been stored in a file or data, or sent over a network connection to some distant machine.
注意
The JSON format is commonly used by modern applications to allow for data exchange. Many programmers are already familiar with it, which makes it a good choice for interoperability.
If you have an object x , you can view its JSON string representation with a simple line of code:
>>> json.dumps([1, 'simple', 'list']) '[1, "simple", "list"]'
另一变体的 dumps() 函数，称为 dump() , simply serializes the object to a file. So if f 是 文件对象 opened for writing, we can do this:
json.dump(x, f)
To decode the object again, if f 是 文件对象 which has been opened for reading:
x = json.load(f)
This simple serialization technique can handle lists and dictionaries, but serializing arbitrary class instances in JSON requires a bit of extra effort. The reference for the json module contains an explanation of this.
另请参阅
pickle - 腌制模块
Contrary to JSON , pickle is a protocol which allows the serialization of arbitrarily complex Python objects. As such, it is specific to Python and cannot be used to communicate with applications written in other languages. It is also insecure by default: deserializing pickle data coming from an untrusted source can execute arbitrary code, if the data was crafted by a skilled attacker.
