7. 输入和输出

There are several ways to present the output of a program; data can be printed in a human-readable form, or written to a file for future use. This chapter will discuss some of the possibilities.

7.1. 更漂亮的输出格式化

So far we’ve encountered two ways of writing values: expression statements print() function. (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 several ways to format output.

  • 要使用 格式化字符串文字 , begin a string with f or F before the opening quotation mark or triple quotation mark. Inside this string, you can write a Python expression between { and } characters that can refer to variables or literal values.

    >>> year = 2016
    >>> event = 'Referendum'
    >>> f'Results of the {year} {event}'
    'Results of the 2016 Referendum'
    										
  • str.format() method of strings requires more manual effort. You’ll still use { and } to mark where a variable will be substituted and can provide detailed formatting directives, but you’ll also need to provide the information to be formatted.

    >>> yes_votes = 42_572_654
    >>> no_votes = 43_132_495
    >>> percentage = yes_votes / (yes_votes + no_votes)
    >>> '{:-9} YES votes  {:2.2%}'.format(yes_votes, percentage)
    ' 42572654 YES votes  49.67%'
    										
  • Finally, you can do all the string handling yourself by using string slicing and concatenation operations to create any layout you can imagine. The string type has some methods that perform useful operations for padding strings to a given column width.

When you don’t need fancy output but just want a quick display of some variables for debugging purposes, you can convert any value to a string with the repr() or str() 函数。

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, in particular, have two distinct representations.

一些范例:

>>> s = 'Hello, world.'
>>> str(s)
'Hello, world.'
>>> repr(s)
"'Hello, world.'"
>>> str(1/7)
'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'))"
								

string module contains a Template class that offers yet another way to substitute values into strings, using placeholders like $x and replacing them with values from a dictionary, but offers much less control of the formatting.

7.1.1. Formatted String Literals

格式化字符串文字 (also called f-strings for short) let you include the value of Python expressions inside a string by prefixing the string with f or F and writing expressions as {expression} .

An optional format specifier can follow the expression. This allows greater control over how the value is formatted. The following example rounds pi to three places after the decimal:

>>> import math
>>> print(f'The value of pi is approximately {math.pi:.3f}.')
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 columns line up.

>>> table = {'Sjoerd': 4127, 'Jack': 4098, 'Dcab': 7678}
>>> for name, phone in table.items():
...     print(f'{name:10} ==> {phone:10d}')
...
Sjoerd     ==>       4127
Jack       ==>       4098
Dcab       ==>       7678
									

Other modifiers can be used to convert the value before it is formatted. '!a' applies ascii() , '!s' applies str() ,和 '!r' applies repr() :

>>> animals = 'eels'
>>> print(f'My hovercraft is full of {animals}.')
My hovercraft is full of eels.
>>> print(f'My hovercraft is full of {animals!r}.')
My hovercraft is full of 'eels'.
									

For a reference on these format specifications, see the reference guide for the 格式规范的迷你语言 .

7.1.2. 字符串 format() 方法

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 can be used to refer 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.
									

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.

As an example, the following lines produce a tidily-aligned set of columns giving integers and their squares and cubes:

>>> 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
									

For a complete overview of string formatting with str.format() ,见 格式字符串语法 .

7.1.3. Manual String Formatting

Here’s the same table of squares and cubes, formatted manually:

>>> for x in range(1, 11):
...     print(repr(x).rjust(2), repr(x*x).rjust(3), end=' ')
...     # Note use of 'end' 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
									

(Note that the one space between each column was added by the way print() works: it always adds spaces between its arguments.)

str.rjust() method of string objects 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'
									

7.1.4. 旧的字符串格式化

The % operator (modulo) can also be used for string formatting. Given 'string' % values , instances of % in string are replaced with zero or more elements of values . This operation is commonly known as string interpolation. 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 printf 样式字符串格式化 章节。

7.2. 读写文件

open() 返回 文件对象 ,且最常见用法是带 2 自变量: open(filename, mode) .

>>> f = open('workfile', 'w')
								

第一个自变量是包含文件名的字符串。第二个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' 当文件只被读取时, 'w' 对于只写 (采用相同名称的现有文件将被擦除),和 'a' 打开文件为追加;要写入文件的任何数据被自动添加到末尾。 'r+' 打开文件为读写两者。 mode 自变量是可选的; 'r' 将被假定若省略。

通常,文件被打开按 文本模式 ,意味着,可以按特定编码进行编码读写文件字符串。若编码未指定,默认从属平台 (见 open() ). 'b' 追加到打开文件的模式按 二进制模式 :现在以字节对象形式读写数据。此模式应用于未包含文本的所有文件。

当以文本模式读取时,默认转换特定平台行尾 ( \n 在 Unix, \r\n 在 Windows) 到仅仅 \n 。当以文本模式写入时,默认转换出现的 \n 回特定平台行尾。这种对文件数据的幕后修改适用于文本文件,但会破坏二进制数据像在 JPEG or EXE 文件。要非常小心使用二进制模式,当读写这种文件时。

是很好实践使用 with 关键词当处理文件对象时。优点是文件在其套件完成之后被正确关闭,即使在某个时间点有引发异常。使用 with 也短得多比编写等效 try - finally 块:

>>> with open('workfile') as f:
...     read_data = f.read()
>>> # We can check that the file has been automatically closed.
>>> f.closed
True
								

若不使用 with 关键词,那么应该调用 f.close() 来关闭文件并立即释放由它使用的任何系统资源。

警告

调用 f.write() 不使用 with 关键词或调用 f.close() might 导致自变量对于 f.write() 未被完全写入磁盘,即使程序成功退出。

在文件对象关闭之后,通过 with 语句或通过调用 f.close() ,试图使用文件对象将自动失败。

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

7.2.1. 文件对象方法

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 (in text mode) or bytes object (in binary mode). 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 characters (in text mode) or size bytes (in binary mode) 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, end='')
...
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 the number of characters written.

>>> f.write('This is a test\n')
15
									

Other types of objects need to be converted – either to a string (in text mode) or a bytes object (in binary mode) – before writing them:

>>> value = ('the answer', 42)
>>> s = str(value)  # convert the tuple to string
>>> f.write(s)
18
									

f.tell() returns an integer giving the file object’s current position in the file represented as number of bytes from the beginning of the file when in binary mode and an opaque number when in text mode.

To change the file object’s position, use f.seek(offset, whence) . The position is computed from adding offset to a reference point; the reference point is selected by the whence argument. A whence 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. whence can be omitted and defaults to 0, using the beginning of the file as the reference point.

>>> f = open('workfile', 'rb+')
>>> f.write(b'0123456789abcdef')
16
>>> f.seek(5)      # Go to the 6th byte in the file
5
>>> f.read(1)
b'5'
>>> f.seek(-3, 2)  # Go to the 3rd byte before the end
13
>>> f.read(1)
b'd'
									

In text files (those opened without a b in the mode string), only seeks relative to the beginning of the file are allowed (the exception being seeking to the very file end with seek(0, 2) ) and the only valid offset values are those returned from the f.tell() , or zero. Any other offset value produces undefined behaviour.

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.

7.2.2. 保存结构化数据采用 json

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:

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

另一变体的 dumps() 函数,称为 dump() ,将对象简单序列化成 文本文件 。因此若 f 文本文件 object opened for writing, we can do this:

json.dump(x, f)
									

To decode the object again, if f 文本文件 object 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.