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# 7. 输入输出

有几种方法可以显示程序的输出；数据可以以人类可读的形式打印出来，或者写入文件以供将来使用。本章将讨论一些可能性。

## 7.1. 更漂亮的输出格式

So far we’ve encountered two ways of writing values: expression statements and the `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()` method.

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()` functions.

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.

几个例子:

    >>> 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: by default it 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]`.)

还有另外一个方法，`str.zfill()` ，它会在数字字符串的左边填充零。它能识别正负号:

    >>> '12'.zfill(5)
    '00012'
    >>> '-3.14'.zfill(7)
    '-003.14'
    >>> '3.14159265359'.zfill(5)
    '3.14159265359'

`str.format()` 方法的基本用法如下所示:

    >>> 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()` method.

    >>> print '{0} and {1}'.format('spam', 'eggs')
    spam and eggs
    >>> print '{1} and {0}'.format('spam', 'eggs')
    eggs and spam

如果在 `str.format()` 方法中使用关键字参数，则使用参数的名称引用它们的值。:

    >>> print 'This {food} is {adjective}.'.format(
    ...       food='spam', adjective='absolutely horrible')
    This spam is absolutely horrible.

位置和关键字参数可以任意组合:

    >>> print 'The story of {0}, {1}, and {other}.'.format('Bill', 'Manfred',
    ...                                                    other='Georg')
    The story of Bill, Manfred, and Georg.

`'!s'` (apply `str()`) and `'!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

如果你有一个非常长的格式字符串，你不想把它拆开，那么你最好按名称而不是位置引用变量来进行格式化。这可以通过简单地传递字典和使用方括号 `'[]'` 访问键来完成:

    >>> 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

这也可以通过使用 ‘**’ 符号将 table 作为关键字参数传递。

    >>> 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

这在与内置函数 `vars()` 结合使用时非常有用，它会返回包含所有局部变量的字典。

关于使用 `str.format()` 进行字符串格式化的完整概述，请参阅 格式字符串语法 。

### 7.1.1. 旧的字符串格式化方法

`%` 操作符也可以用作字符串格式化。它将左边的参数解释为一个很像 `sprintf()` 风格 的格式字符串，应用到右边的参数，并返回一个由此格式化操作产生的字符串。例如:

    >>> import math
    >>> print 'The value of PI is approximately %5.3f.' % math.pi
    The value of PI is approximately 3.142.

More information can be found in the String Formatting Operations section.

## 7.2. 读写文件

`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>

第一个参数是包含文件名的字符串。第二个参数是另一个字符串，其中包含一些描述文件使用方式的字符。mode 可以是 `'r'` ，表示文件只能读取，`'w'` 表示只能写入（已存在的同名文件会被删除），还有 `'a'` 表示打开文件以追加内容；任何写入的数据会自动添加到文件的末尾。`'r+'` 表示打开文件进行读写。mode 参数是可选的；省略时默认为 `'r'`。

On Windows, `'b'` appended to the mode opens the file in binary mode, so there are also modes like `'rb'`, `'wb'`, and `'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.

### 7.2.1. 文件对象的方法

本节中剩下的例子将假定你已创建名为 `f` 的文件对象。

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()
    ''

要从文件中读取行，你可以循环遍历文件对象。这是内存高效，快速的，并简化代码:

    >>> for line in f:
            print line,

    This is the first line of the file.
    Second line of the file

如果你想以列表的形式读取文件中的所有行，你也可以使用 `list(f)` 或 `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()`, attempts to use the file object will automatically fail.

    >>> f.close()
    >>> f.read()
    Traceback (most recent call last):
      File "<stdin>", line 1, in <module>
    ValueError: I/O operation on closed file

It is good practice to use the `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` blocks:

    >>> with open('workfile', 'r') as f:
    ...     read_data = f.read()
    >>> f.closed
    True

文件对象有一些额外的方法，例如 `isatty()` 和 `truncate()` ，它们使用频率较低；有关文件对象的完整指南请参阅库参考。

### 7.2.2. 使用 `json` 保存结构化数据

字符串可以很轻松地写入文件并从文件中读取出来。数字可能会费点劲，因为 `read()` 方法只能返回字符串，这些字符串必须传递给类似 `int()` 的函数，它会接受类似 `'123'` 这样的字符串并返回其数字值 123。当你想保存诸如嵌套列表和字典这样更复杂的数据类型时，手动解析和序列化会变得复杂。

Python 允许你使用称为 JSON (JavaScript Object Notation) 的流行数据交换格式，而不是让用户不断的编写和调试代码以将复杂的数据类型保存到文件中。名为 `json` 的标准模块可以采用 Python 数据层次结构，并将它们转化为字符串表示形式；这个过程称为 serializing 。从字符串表示中重建数据称为 deserializing 。在序列化和反序列化之间，表示对象的字符串可能已存储在文件或数据中，或通过网络连接发送到某个远程机器。

注解

JSON格式通常被现代应用程序用于允许数据交换。许多程序员已经熟悉它，这使其成为互操作性的良好选择。

如果你有一个对象 `x` ，你可以用一行简单的代码来查看它的 JSON 字符串表示:

    >>> import json
    >>> json.dumps([1, 'simple', 'list'])
    '[1, "simple", "list"]'

Another variant of the `dumps()` function, called `dump()`, simply serializes the object to a file. So if `f` is a file object opened for writing, we can do this:

    json.dump(x, f)

To decode the object again, if `f` is a file object which has been opened for reading:

    x = json.load(f)

这种简单的序列化技术可以处理列表和字典，但是在JSON中序列化任意类的实例需要额外的努力。 `json` 模块的参考包含对此的解释。

参见

`pickle` - 封存模块

与 JSON 不同，pickle 是一种允许对任意复杂 Python 对象进行序列化的协议。因此，它为 Python 所特有，不能用于与其他语言编写的应用程序通信。默认情况下它也是不安全的：如果数据是由熟练的攻击者精心设计的，则反序列化来自不受信任来源的 pickle 数据可以执行任意代码。