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()
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 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 type has 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, 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'))"
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), 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 >>> 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 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.
'!a'
(apply
ascii()
),
'!s'
(apply
str()
) 和
'!r'
(apply
repr()
) can be used to convert the value before it is formatted:
>>> contents = 'eels' >>> print('My hovercraft is full of {}.'.format(contents)) My hovercraft is full of eels. >>> print('My hovercraft is full of {!r}.'.format(contents)) My hovercraft is full of 'eels'.
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 printf 样式字符串格式化 章节。
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 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。
通常，打开文件是按
文本模式
，意味着从文件读取字符串和将字符串写入文件，编码是按特定编码。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。优点是文件在套件完成后会正确关闭，即使某些时候有引发异常。使用
with
也短得多比编写等效
try
-
finally
块：
>>> with open('workfile') as f: ... read_data = f.read() >>> f.closed True
若不使用
with
关键词，那么应调用
f.close()
to close the file and immediately free up any system resources used by it. If you don’t explicitly close a file, Python’s garbage collector will eventually destroy the object and close the open file for you, but the file may stay open for a while. Another risk is that different Python implementations will do this clean-up at different times.
在关闭文件对象后，通过
with
语句或通过调用
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 <module> ValueError: I/O operation on closed file
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
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, 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, 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', '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.
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 >>> json.dumps([1, 'simple', 'list']) '[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
是
文本文件
object opened for writing, we can do this:
json.dump(x, f)
To decode the object again, if
f
是
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.