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511 lines
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ReStructuredText
511 lines
19 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 :func:`print` function. (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 several ways to format output.
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* To use :ref:`formatted string literals <tut-f-strings>`, begin a string
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with ``f`` or ``F`` before the opening quotation mark or triple quotation mark.
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Inside this string, you can write a Python expression between ``{`` and ``}``
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characters that can refer to variables or literal values.
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::
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>>> year = 2016
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>>> event = 'Referendum'
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>>> f'Results of the {year} {event}'
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'Results of the 2016 Referendum'
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* The :meth:`str.format` method of strings requires more manual
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effort. You'll still use ``{`` and ``}`` to mark where a variable
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will be substituted and can provide detailed formatting directives,
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but you'll also need to provide the information to be formatted.
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::
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>>> yes_votes = 42_572_654
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>>> no_votes = 43_132_495
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>>> percentage = yes_votes / (yes_votes + no_votes)
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>>> '{:-9} YES votes {:2.2%}'.format(yes_votes, percentage)
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' 42572654 YES votes 49.67%'
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* Finally, you can do all the string handling yourself by using string slicing and
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concatenation operations to create any layout you can imagine. The
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string type has some methods that perform useful operations for padding
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strings to a given column width.
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When you don't need fancy output but just want a quick display of some
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variables for debugging purposes, you can convert any value to a string with
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the :func:`repr` 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, in
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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(1/7)
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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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The :mod:`string` module contains a :class:`~string.Template` class that offers
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yet another way to substitute values into strings, using placeholders like
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``$x`` and replacing them with values from a dictionary, but offers much less
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control of the formatting.
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.. _tut-f-strings:
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Formatted String Literals
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-------------------------
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:ref:`Formatted string literals <f-strings>` (also called f-strings for
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short) let you include the value of Python expressions inside a string by
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prefixing the string with ``f`` or ``F`` and writing expressions as
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``{expression}``.
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An optional format specifier can follow the expression. This allows greater
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control over how the value is formatted. The following example rounds pi to
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three places after the decimal::
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>>> import math
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>>> print(f'The value of pi is approximately {math.pi:.3f}.')
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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 columns line up. ::
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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(f'{name:10} ==> {phone:10d}')
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...
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Sjoerd ==> 4127
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Jack ==> 4098
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Dcab ==> 7678
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Other modifiers can be used to convert the value before it is formatted.
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``'!a'`` applies :func:`ascii`, ``'!s'`` applies :func:`str`, and ``'!r'``
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applies :func:`repr`::
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>>> animals = 'eels'
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>>> print(f'My hovercraft is full of {animals}.')
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My hovercraft is full of eels.
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>>> print(f'My hovercraft is full of {animals!r}.')
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My hovercraft is full of 'eels'.
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For a reference on these format specifications, see
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the reference guide for the :ref:`formatspec`.
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.. _tut-string-format:
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The String format() Method
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--------------------------
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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 can be used to refer 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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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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As an example, the following lines produce a tidily-aligned
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set of columns giving integers and their squares and cubes::
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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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For a complete overview of string formatting with :meth:`str.format`, see
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:ref:`formatstrings`.
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Manual String Formatting
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------------------------
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Here's the same table of squares and cubes, formatted manually::
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>>> for x in range(1, 11):
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... print(repr(x).rjust(2), repr(x*x).rjust(3), end=' ')
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... # Note use of 'end' 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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(Note that the one space between each column was added by the
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way :func:`print` works: it always adds spaces between its arguments.)
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The :meth:`str.rjust` method of string objects right-justifies a string in a
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field of a given width by padding it with spaces on the left. There are
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similar methods :meth:`str.ljust` and :meth:`str.center`. These methods do
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not write anything, they just return a new string. If the input string is too
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long, they don't truncate it, but return it unchanged; this will mess up your
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column lay-out but that's usually better than the alternative, which would be
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lying about a value. (If you really want truncation you can always add a
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slice operation, as in ``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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Old string formatting
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---------------------
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The % operator (modulo) can also be used for string formatting. Given ``'string'
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% values``, instances of ``%`` in ``string`` are replaced with zero or more
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elements of ``values``. This operation is commonly known as string
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interpolation. 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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More information can be found in the :ref:`old-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 :term:`file object`, and is most commonly used with
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two arguments: ``open(filename, mode)``.
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::
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>>> f = open('workfile', 'w')
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.. XXX str(f) is <io.TextIOWrapper object at 0x82e8dc4>
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>>> print(f)
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<open file '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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Normally, files are opened in :dfn:`text mode`, that means, you read and write
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strings from and to the file, which are encoded in a specific encoding. If
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encoding is not specified, the default is platform dependent (see
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:func:`open`). ``'b'`` appended to the mode opens the file in
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:dfn:`binary mode`: now the data is read and written in the form of bytes
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objects. This mode should be used for all files that don't contain text.
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In text mode, the default when reading is to convert platform-specific line
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endings (``\n`` on Unix, ``\r\n`` on Windows) to just ``\n``. When writing in
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text mode, the default is to convert occurrences of ``\n`` back to
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platform-specific line endings. This behind-the-scenes modification
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to file data is fine for text files, but will corrupt binary data like that in
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:file:`JPEG` or :file:`EXE` files. Be very careful to use binary mode when
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reading and writing such files.
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It is good practice to use the :keyword:`with` keyword when dealing
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with file objects. The advantage is that the file is properly closed
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after its suite finishes, even if an exception is raised at some
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point. Using :keyword:`!with` is also much shorter than writing
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equivalent :keyword:`try`\ -\ :keyword:`finally` blocks::
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>>> with open('workfile') as f:
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... read_data = f.read()
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>>> # We can check that the file has been automatically closed.
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>>> f.closed
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True
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If you're not using the :keyword:`with` keyword, then you should call
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``f.close()`` to close the file and immediately free up any system
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resources used by it.
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.. warning::
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Calling ``f.write()`` without using the :keyword:`!with` keyword or calling
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``f.close()`` **might** result in the arguments
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of ``f.write()`` not being completely written to the disk, even if the
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program exits successfully.
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..
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See also https://bugs.python.org/issue17852
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After a file object is closed, either by a :keyword:`with` statement
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or by calling ``f.close()``, attempts to use the file object will
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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 <module>
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ValueError: I/O operation on closed file.
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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 (in text mode) or bytes object (in binary mode).
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*size* is an optional numeric argument. When *size* is omitted or negative, the
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entire contents of the file will be read and returned; it's your problem if the
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file is twice as large as your machine's memory. Otherwise, at most *size*
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characters (in text mode) or *size* bytes (in binary mode) are read and returned.
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If the end of the file has been reached, ``f.read()`` will return an empty
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string (``''``). ::
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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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For reading lines from a file, you can loop over the file object. This is memory
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efficient, fast, and leads to simple code::
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>>> for line in f:
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... print(line, end='')
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...
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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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If you want to read all the lines of a file in a list you can also use
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``list(f)`` or ``f.readlines()``.
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``f.write(string)`` writes the contents of *string* to the file, returning
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the number of characters written. ::
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>>> f.write('This is a test\n')
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15
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Other types of objects need to be converted -- either to a string (in text mode)
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or a bytes object (in binary mode) -- before writing them::
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>>> value = ('the answer', 42)
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>>> s = str(value) # convert the tuple to string
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>>> f.write(s)
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18
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``f.tell()`` returns an integer giving the file object's current position in the file
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represented as number of bytes from the beginning of the file when in binary mode and
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an opaque number when in text mode.
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To change the file object's position, use ``f.seek(offset, whence)``. 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 *whence* argument. A *whence* 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. *whence* 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('workfile', 'rb+')
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>>> f.write(b'0123456789abcdef')
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16
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>>> f.seek(5) # Go to the 6th byte in the file
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5
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>>> f.read(1)
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b'5'
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>>> f.seek(-3, 2) # Go to the 3rd byte before the end
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13
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>>> f.read(1)
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b'd'
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In text files (those opened without a ``b`` in the mode string), only seeks
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relative to the beginning of the file are allowed (the exception being seeking
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to the very file end with ``seek(0, 2)``) and the only valid *offset* values are
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those returned from the ``f.tell()``, or zero. Any other *offset* value produces
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undefined behaviour.
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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-json:
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Saving structured data with :mod:`json`
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---------------------------------------
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.. index:: module: json
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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. When you want to save more complex data
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types like nested lists and dictionaries, parsing and serializing by hand
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becomes complicated.
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Rather than having users constantly writing and debugging code to save
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complicated data types to files, Python allows you to use the popular data
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interchange format called `JSON (JavaScript Object Notation)
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<http://json.org>`_. The standard module called :mod:`json` can take Python
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data hierarchies, and convert them to string representations; this process is
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called :dfn:`serializing`. Reconstructing the data from the string representation
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is called :dfn:`deserializing`. Between serializing and deserializing, the
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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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.. note::
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The JSON format is commonly used by modern applications to allow for data
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exchange. Many programmers are already familiar with it, which makes
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it a good choice for interoperability.
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If you have an object ``x``, you can view its JSON string representation with a
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simple line of code::
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>>> import json
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>>> x = [1, 'simple', 'list']
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>>> json.dumps(x)
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'[1, "simple", "list"]'
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Another variant of the :func:`~json.dumps` function, called :func:`~json.dump`,
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simply serializes the object to a :term:`text file`. So if ``f`` is a
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:term:`text file` object opened for writing, we can do this::
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json.dump(x, f)
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To decode the object again, if ``f`` is a :term:`text file` object which has
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been opened for reading::
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x = json.load(f)
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This simple serialization technique can handle lists and dictionaries, but
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serializing arbitrary class instances in JSON requires a bit of extra effort.
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The reference for the :mod:`json` module contains an explanation of this.
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.. seealso::
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:mod:`pickle` - the pickle module
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Contrary to :ref:`JSON <tut-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:
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|
deserializing pickle data coming from an untrusted source can execute
|
|
arbitrary code, if the data was crafted by a skilled attacker.
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