cpython/Doc/tutorial/inputoutput.rst

.. _tut-io:

****************
Input and Output
****************

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.


.. _tut-formatting:

Fancier Output Formatting
=========================

So far we've encountered two ways of writing values: *expression statements* and
the :func:`print` function.  (A third way is using the :meth:`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.

* To use :ref:`formatted string literals <tut-f-strings>`, 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'

* The :meth:`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 :func:`repr` or :func:`str` functions.

The :func:`str` function is meant to return representations of values which are
fairly human-readable, while :func:`repr` is meant to generate representations
which can be read by the interpreter (or will force a :exc:`SyntaxError` if
there is no equivalent syntax).  For objects which don't have a particular
representation for human consumption, :func:`str` will return the same value as
:func:`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.

Some examples::

   >>> 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'))"

The :mod:`string` module contains a :class:`~string.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.


.. _tut-f-strings:

Formatted String Literals
-------------------------

:ref:`Formatted string literals <f-strings>` (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 :func:`ascii`, ``'!s'`` applies :func:`str`, and ``'!r'``
applies :func:`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 :ref:`formatspec`.

.. _tut-string-format:

The String format() Method
--------------------------

Basic usage of the :meth:`str.format` method looks like this::

   >>> 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 :meth:`str.format` method.  A number in the
brackets can be used to refer to the position of the object passed into the
:meth:`str.format` method. ::

   >>> 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 :meth:`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
:func:`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 :meth:`str.format`, see
:ref:`formatstrings`.


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 :func:`print` works: it always adds spaces between its arguments.)

The :meth:`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 :meth:`str.ljust` and :meth:`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, :meth:`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'


Old string formatting
---------------------

The ``%`` operator can also be used for string formatting. It interprets the
left argument much like a :c:func:`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.

More information can be found in the :ref:`old-string-formatting` section.


.. _tut-files:

Reading and Writing Files
=========================

.. index::
   builtin: open
   object: file

:func:`open` returns a :term:`file object`, and is most commonly used with
two arguments: ``open(filename, mode)``.

::

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

.. XXX str(f) is <io.TextIOWrapper object at 0x82e8dc4>

   >>> print(f)
   <open file 'workfile', mode 'w' at 80a0960>

The first argument is a string containing the filename.  The second argument is
another string containing a few characters describing the way in which the file
will be used.  *mode* can be ``'r'`` when the file will only be read, ``'w'``
for only writing (an existing file with the same name will be erased), and
``'a'`` opens the file for appending; any data written to the file is
automatically added to the end.  ``'r+'`` opens the file for both reading and
writing. The *mode* argument is optional; ``'r'`` will be assumed if it's
omitted.

Normally, files are opened in :dfn:`text mode`, that means, you read and write
strings from and to the file, which are encoded in a specific encoding. If
encoding is not specified, the default is platform dependent (see
:func:`open`). ``'b'`` appended to the mode opens the file in
:dfn:`binary mode`: now the data is read and written in the form of bytes
objects.  This mode should be used for all files that don't contain text.

In text mode, the default when reading is to convert platform-specific line
endings (``\n`` on Unix, ``\r\n`` on Windows) to just ``\n``.  When writing in
text mode, the default is to convert occurrences of ``\n`` back to
platform-specific line endings.  This behind-the-scenes modification
to file data is fine for text files, but will corrupt binary data like that in
:file:`JPEG` or :file:`EXE` files.  Be very careful to use binary mode when
reading and writing such files.

It is good practice to use the :keyword:`with` keyword when dealing
with file objects.  The advantage is that the file is properly closed
after its suite finishes, even if an exception is raised at some
point.  Using :keyword:`!with` is also much shorter than writing
equivalent :keyword:`try`\ -\ :keyword:`finally` blocks::

    >>> with open('workfile') as f:
    ...     read_data = f.read()

    >>> # We can check that the file has been automatically closed.
    >>> f.closed
    True

If you're not using the :keyword:`with` keyword, then you should call
``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.

After a file object is closed, either by a :keyword:`with` statement
or by calling ``f.close()``, attempts to use the file object will
automatically fail. ::

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


.. _tut-filemethods:

Methods of File Objects
-----------------------

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 :meth:`~file.isatty` and
:meth:`~file.truncate` which are less frequently used; consult the Library
Reference for a complete guide to file objects.


.. _tut-json:

Saving structured data with :mod:`json`
---------------------------------------

.. index:: module: json

Strings can easily be written to and read from a file.  Numbers take a bit more
effort, since the :meth:`read` method only returns strings, which will have to
be passed to a function like :func:`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 Object Notation)
<http://json.org>`_.  The standard module called :mod:`json` can take Python
data hierarchies, and convert them to string representations; this process is
called :dfn:`serializing`.  Reconstructing the data from the string representation
is called :dfn:`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.

.. note::
   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"]'

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

   json.dump(x, f)

To decode the object again, if ``f`` is a :term:`text file` 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 :mod:`json` module contains an explanation of this.

.. seealso::

   :mod:`pickle` - the pickle module

   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:
   deserializing pickle data coming from an untrusted source can execute
   arbitrary code, if the data was crafted by a skilled attacker.