mirror of https://github.com/python/cpython
420 lines
16 KiB
ReStructuredText
420 lines
16 KiB
ReStructuredText
.. _tut-io:
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****************
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Input and Output
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****************
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There are several ways to present the output of a program; data can be printed
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in a human-readable form, or written to a file for future use. This chapter will
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discuss some of the possibilities.
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.. _tut-formatting:
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Fancier Output Formatting
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=========================
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So far we've encountered two ways of writing values: *expression statements* and
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the :keyword:`print` statement. (A third way is using the :meth:`write` method
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of file objects; the standard output file can be referenced as ``sys.stdout``.
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See the Library Reference for more information on this.)
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Often you'll want more control over the formatting of your output than simply
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printing space-separated values. There are two ways to format your output; the
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first way is to do all the string handling yourself; using string slicing and
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concatenation operations you can create any layout you can imagine. The
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string types have some methods that perform useful operations for padding
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strings to a given column width; these will be discussed shortly. The second
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way is to use the :meth:`str.format` method.
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The :mod:`string` module contains a :class:`~string.Template` class which offers
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yet another way to substitute values into strings.
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One question remains, of course: how do you convert values to strings? Luckily,
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Python has ways to convert any value to a string: pass it to the :func:`repr`
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or :func:`str` functions.
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The :func:`str` function is meant to return representations of values which are
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fairly human-readable, while :func:`repr` is meant to generate representations
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which can be read by the interpreter (or will force a :exc:`SyntaxError` if
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there is no equivalent syntax). For objects which don't have a particular
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representation for human consumption, :func:`str` will return the same value as
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:func:`repr`. Many values, such as numbers or structures like lists and
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dictionaries, have the same representation using either function. Strings and
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floating point numbers, in particular, have two distinct representations.
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Some examples::
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>>> s = 'Hello, world.'
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>>> str(s)
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'Hello, world.'
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>>> repr(s)
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"'Hello, world.'"
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>>> str(1.0/7.0)
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'0.142857142857'
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>>> repr(1.0/7.0)
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'0.14285714285714285'
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>>> x = 10 * 3.25
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>>> y = 200 * 200
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>>> s = 'The value of x is ' + repr(x) + ', and y is ' + repr(y) + '...'
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>>> print s
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The value of x is 32.5, and y is 40000...
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>>> # The repr() of a string adds string quotes and backslashes:
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... hello = 'hello, world\n'
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>>> hellos = repr(hello)
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>>> print hellos
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'hello, world\n'
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>>> # The argument to repr() may be any Python object:
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... repr((x, y, ('spam', 'eggs')))
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"(32.5, 40000, ('spam', 'eggs'))"
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Here are two ways to write a table of squares and cubes::
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>>> for x in range(1, 11):
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... print repr(x).rjust(2), repr(x*x).rjust(3),
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... # Note trailing comma on previous line
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... print repr(x*x*x).rjust(4)
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...
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1 1 1
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2 4 8
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3 9 27
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4 16 64
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5 25 125
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6 36 216
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7 49 343
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8 64 512
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9 81 729
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10 100 1000
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>>> for x in range(1,11):
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... print '{0:2d} {1:3d} {2:4d}'.format(x, x*x, x*x*x)
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...
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1 1 1
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2 4 8
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3 9 27
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4 16 64
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5 25 125
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6 36 216
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7 49 343
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8 64 512
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9 81 729
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10 100 1000
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(Note that in the first example, one space between each column was added by the
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way :keyword:`print` works: it always adds spaces between its arguments.)
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This example demonstrates the :meth:`str.rjust` method of string
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objects, which right-justifies a string in a field of a given width by padding
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it with spaces on the left. There are similar methods :meth:`str.ljust` and
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:meth:`str.center`. These methods do not write anything, they just return a
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new string. If the input string is too long, they don't truncate it, but
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return it unchanged; this will mess up your column lay-out but that's usually
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better than the alternative, which would be lying about a value. (If you
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really want truncation you can always add a slice operation, as in
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``x.ljust(n)[:n]``.)
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There is another method, :meth:`str.zfill`, which pads a numeric string on the
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left with zeros. It understands about plus and minus signs::
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>>> '12'.zfill(5)
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'00012'
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>>> '-3.14'.zfill(7)
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'-003.14'
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>>> '3.14159265359'.zfill(5)
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'3.14159265359'
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Basic usage of the :meth:`str.format` method looks like this::
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>>> print 'We are the {} who say "{}!"'.format('knights', 'Ni')
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We are the knights who say "Ni!"
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The brackets and characters within them (called format fields) are replaced with
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the objects passed into the :meth:`str.format` method. A number in the
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brackets refers to the position of the object passed into the
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:meth:`str.format` method. ::
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>>> print '{0} and {1}'.format('spam', 'eggs')
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spam and eggs
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>>> print '{1} and {0}'.format('spam', 'eggs')
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eggs and spam
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If keyword arguments are used in the :meth:`str.format` method, their values
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are referred to by using the name of the argument. ::
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>>> print 'This {food} is {adjective}.'.format(
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... food='spam', adjective='absolutely horrible')
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This spam is absolutely horrible.
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Positional and keyword arguments can be arbitrarily combined::
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>>> print 'The story of {0}, {1}, and {other}.'.format('Bill', 'Manfred',
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... other='Georg')
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The story of Bill, Manfred, and Georg.
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``'!s'`` (apply :func:`str`) and ``'!r'`` (apply :func:`repr`) can be used to
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convert the value before it is formatted. ::
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>>> import math
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>>> print 'The value of PI is approximately {}.'.format(math.pi)
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The value of PI is approximately 3.14159265359.
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>>> print 'The value of PI is approximately {!r}.'.format(math.pi)
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The value of PI is approximately 3.141592653589793.
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An optional ``':'`` and format specifier can follow the field name. This allows
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greater control over how the value is formatted. The following example
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rounds Pi to three places after the decimal.
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>>> import math
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>>> print 'The value of PI is approximately {0:.3f}.'.format(math.pi)
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The value of PI is approximately 3.142.
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Passing an integer after the ``':'`` will cause that field to be a minimum
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number of characters wide. This is useful for making tables pretty. ::
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>>> table = {'Sjoerd': 4127, 'Jack': 4098, 'Dcab': 7678}
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>>> for name, phone in table.items():
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... print '{0:10} ==> {1:10d}'.format(name, phone)
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...
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Jack ==> 4098
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Dcab ==> 7678
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Sjoerd ==> 4127
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If you have a really long format string that you don't want to split up, it
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would be nice if you could reference the variables to be formatted by name
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instead of by position. This can be done by simply passing the dict and using
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square brackets ``'[]'`` to access the keys ::
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>>> table = {'Sjoerd': 4127, 'Jack': 4098, 'Dcab': 8637678}
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>>> print ('Jack: {0[Jack]:d}; Sjoerd: {0[Sjoerd]:d}; '
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... 'Dcab: {0[Dcab]:d}'.format(table))
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Jack: 4098; Sjoerd: 4127; Dcab: 8637678
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This could also be done by passing the table as keyword arguments with the '**'
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notation. ::
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>>> table = {'Sjoerd': 4127, 'Jack': 4098, 'Dcab': 8637678}
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>>> print 'Jack: {Jack:d}; Sjoerd: {Sjoerd:d}; Dcab: {Dcab:d}'.format(**table)
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Jack: 4098; Sjoerd: 4127; Dcab: 8637678
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This is particularly useful in combination with the built-in function
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:func:`vars`, which returns a dictionary containing all local variables.
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For a complete overview of string formatting with :meth:`str.format`, see
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:ref:`formatstrings`.
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Old string formatting
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---------------------
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The ``%`` operator can also be used for string formatting. It interprets the
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left argument much like a :c:func:`sprintf`\ -style format string to be applied
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to the right argument, and returns the string resulting from this formatting
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operation. For example::
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>>> import math
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>>> print 'The value of PI is approximately %5.3f.' % math.pi
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The value of PI is approximately 3.142.
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Since :meth:`str.format` is quite new, a lot of Python code still uses the ``%``
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operator. However, because this old style of formatting will eventually be
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removed from the language, :meth:`str.format` should generally be used.
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More information can be found in the :ref:`string-formatting` section.
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.. _tut-files:
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Reading and Writing Files
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=========================
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.. index::
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builtin: open
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object: file
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:func:`open` returns a file object, and is most commonly used with two
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arguments: ``open(filename, mode)``.
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::
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>>> f = open('/tmp/workfile', 'w')
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>>> print f
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<open file '/tmp/workfile', mode 'w' at 80a0960>
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The first argument is a string containing the filename. The second argument is
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another string containing a few characters describing the way in which the file
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will be used. *mode* can be ``'r'`` when the file will only be read, ``'w'``
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for only writing (an existing file with the same name will be erased), and
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``'a'`` opens the file for appending; any data written to the file is
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automatically added to the end. ``'r+'`` opens the file for both reading and
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writing. The *mode* argument is optional; ``'r'`` will be assumed if it's
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omitted.
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On Windows, ``'b'`` appended to the mode opens the file in binary mode, so there
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are also modes like ``'rb'``, ``'wb'``, and ``'r+b'``. Python on Windows makes
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a distinction between text and binary files; the end-of-line characters in text
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files are automatically altered slightly when data is read or written. This
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behind-the-scenes modification to file data is fine for ASCII text files, but
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it'll corrupt binary data like that in :file:`JPEG` or :file:`EXE` files. Be
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very careful to use binary mode when reading and writing such files. On Unix,
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it doesn't hurt to append a ``'b'`` to the mode, so you can use it
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platform-independently for all binary files.
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.. _tut-filemethods:
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Methods of File Objects
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-----------------------
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The rest of the examples in this section will assume that a file object called
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``f`` has already been created.
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To read a file's contents, call ``f.read(size)``, which reads some quantity of
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data and returns it as a string. *size* is an optional numeric argument. When
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*size* is omitted or negative, the entire contents of the file will be read and
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returned; it's your problem if the file is twice as large as your machine's
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memory. Otherwise, at most *size* bytes are read and returned. If the end of
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the file has been reached, ``f.read()`` will return an empty string (``""``).
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::
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>>> f.read()
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'This is the entire file.\n'
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>>> f.read()
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''
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``f.readline()`` reads a single line from the file; a newline character (``\n``)
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is left at the end of the string, and is only omitted on the last line of the
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file if the file doesn't end in a newline. This makes the return value
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unambiguous; if ``f.readline()`` returns an empty string, the end of the file
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has been reached, while a blank line is represented by ``'\n'``, a string
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containing only a single newline. ::
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>>> f.readline()
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'This is the first line of the file.\n'
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>>> f.readline()
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'Second line of the file\n'
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>>> f.readline()
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''
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``f.readlines()`` returns a list containing all the lines of data in the file.
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If given an optional parameter *sizehint*, it reads that many bytes from the
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file and enough more to complete a line, and returns the lines from that. This
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is often used to allow efficient reading of a large file by lines, but without
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having to load the entire file in memory. Only complete lines will be returned.
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::
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>>> f.readlines()
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['This is the first line of the file.\n', 'Second line of the file\n']
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An alternative approach to reading lines is to loop over the file object. This is
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memory efficient, fast, and leads to simpler code::
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>>> for line in f:
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print line,
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This is the first line of the file.
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Second line of the file
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The alternative approach is simpler but does not provide as fine-grained
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control. Since the two approaches manage line buffering differently, they
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should not be mixed.
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``f.write(string)`` writes the contents of *string* to the file, returning
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``None``. ::
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>>> f.write('This is a test\n')
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To write something other than a string, it needs to be converted to a string
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first::
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>>> value = ('the answer', 42)
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>>> s = str(value)
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>>> f.write(s)
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``f.tell()`` returns an integer giving the file object's current position in the
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file, measured in bytes from the beginning of the file. To change the file
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object's position, use ``f.seek(offset, from_what)``. The position is computed
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from adding *offset* to a reference point; the reference point is selected by
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the *from_what* argument. A *from_what* value of 0 measures from the beginning
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of the file, 1 uses the current file position, and 2 uses the end of the file as
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the reference point. *from_what* can be omitted and defaults to 0, using the
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beginning of the file as the reference point. ::
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>>> f = open('/tmp/workfile', 'r+')
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>>> f.write('0123456789abcdef')
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>>> f.seek(5) # Go to the 6th byte in the file
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>>> f.read(1)
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'5'
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>>> f.seek(-3, 2) # Go to the 3rd byte before the end
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>>> f.read(1)
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'd'
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When you're done with a file, call ``f.close()`` to close it and free up any
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system resources taken up by the open file. After calling ``f.close()``,
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attempts to use the file object will automatically fail. ::
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>>> f.close()
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>>> f.read()
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Traceback (most recent call last):
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File "<stdin>", line 1, in ?
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ValueError: I/O operation on closed file
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It is good practice to use the :keyword:`with` keyword when dealing with file
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objects. This has the advantage that the file is properly closed after its
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suite finishes, even if an exception is raised on the way. It is also much
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shorter than writing equivalent :keyword:`try`\ -\ :keyword:`finally` blocks::
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>>> with open('/tmp/workfile', 'r') as f:
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... read_data = f.read()
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>>> f.closed
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True
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File objects have some additional methods, such as :meth:`~file.isatty` and
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:meth:`~file.truncate` which are less frequently used; consult the Library
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Reference for a complete guide to file objects.
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.. _tut-pickle:
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The :mod:`pickle` Module
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------------------------
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.. index:: module: pickle
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Strings can easily be written to and read from a file. Numbers take a bit more
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effort, since the :meth:`read` method only returns strings, which will have to
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be passed to a function like :func:`int`, which takes a string like ``'123'``
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and returns its numeric value 123. However, when you want to save more complex
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data types like lists, dictionaries, or class instances, things get a lot more
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complicated.
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Rather than have users be constantly writing and debugging code to save
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complicated data types, Python provides a standard module called :mod:`pickle`.
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This is an amazing module that can take almost any Python object (even some
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forms of Python code!), and convert it to a string representation; this process
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is called :dfn:`pickling`. Reconstructing the object from the string
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representation is called :dfn:`unpickling`. Between pickling and unpickling,
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the string representing the object may have been stored in a file or data, or
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sent over a network connection to some distant machine.
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If you have an object ``x``, and a file object ``f`` that's been opened for
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writing, the simplest way to pickle the object takes only one line of code::
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pickle.dump(x, f)
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To unpickle the object again, if ``f`` is a file object which has been opened
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for reading::
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x = pickle.load(f)
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(There are other variants of this, used when pickling many objects or when you
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don't want to write the pickled data to a file; consult the complete
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documentation for :mod:`pickle` in the Python Library Reference.)
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:mod:`pickle` is the standard way to make Python objects which can be stored and
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reused by other programs or by a future invocation of the same program; the
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technical term for this is a :dfn:`persistent` object. Because :mod:`pickle` is
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so widely used, many authors who write Python extensions take care to ensure
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that new data types such as matrices can be properly pickled and unpickled.
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