Subsections

- 7.1 Fancier Output Formatting
- 7.2 Reading and Writing Files
  - 7.2.1 Methods of File Objects
  - 7.2.2 The `pickle` Module

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7. 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.

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7.1 Fancier Output Formatting

So far we've encountered two ways of writing values: expression statements and the `print` statement. (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 lay-out you can imagine. The standard module `string` contains some useful operations for padding strings to a given column width; these will be discussed shortly. The second way is to use the `%` operator with a string as the left argument. The `%` operator 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.

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()` functions, or just write the value between reverse quotes (````, equivalent to `repr()`).

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 not 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 and floating point numbers, in particular, have two distinct representations.

Some examples:

      >>> s = 'Hello, world.'
      >>> str(s)
      'Hello, world.'
      >>> `s`
      "'Hello, world.'"
      >>> str(0.1)
      '0.1'
      >>> `0.1`
      '0.10000000000000001'
      >>> x = 10 * 3.25
      >>> y = 200 * 200
      >>> s = 'The value of x is ' + `x` + ', and y is ' + `y` + '...'
      >>> print s
      The value of x is 32.5, and y is 40000...
      >>> # Reverse quotes work on other types besides numbers:
      ... p = [x, y]
      >>> ps = repr(p)
      >>> ps
      '[32.5, 40000]'
      >>> # Converting a string adds string quotes and backslashes:
      ... hello = 'hello, world\n'
      >>> hellos = `hello`
      >>> print hellos
      'hello, world\n'
      >>> # The argument of reverse quotes may be a tuple:
      ... `x, y, ('spam', 'eggs')`
      "(32.5, 40000, ('spam', 'eggs'))"

Here are two ways to write a table of squares and cubes:

      >>> import string
      >>> for x in range(1, 11):
      ...     print string.rjust(`x`, 2), string.rjust(`x*x`, 3),
      ...     # Note trailing comma on previous line
      ...     print string.rjust(`x*x*x`, 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 '%2d %3d %4d' % (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 one space between each column was added by the way `print` works: it always adds spaces between its arguments.)

This example demonstrates the function `string.rjust()`, which right-justifies a string in a field of a given width by padding it with spaces on the left. There are similar functions `string.ljust()` and `string.center()`. These functions 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 "`string.ljust(x, n)[0:n]`".)

There is another function, `string.zfill()`, which pads a numeric string on the left with zeros. It understands about plus and minus signs:

      >>> import string
      >>> string.zfill('12', 5)
      '00012'
      >>> string.zfill('-3.14', 7)
      '-003.14'
      >>> string.zfill('3.14159265359', 5)
      '3.14159265359'

Using the `%` operator looks like this:

      >>> import math
      >>> print 'The value of PI is approximately %5.3f.' % math.pi
      The value of PI is approximately 3.142.

If there is more than one format in the string, you need to pass a tuple as right operand, as in this example:

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

Most formats work exactly as in C and require that you pass the proper type; however, if you don't you get an exception, not a core dump. The `%s` format is more relaxed: if the corresponding argument is not a string object, it is converted to string using the `str()` built-in function. Using `*` to pass the width or precision in as a separate (integer) argument is supported. The C formats `%n` and `%p` are not supported.

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 using form `%(name)format`, as shown here:

      >>> table = {'Sjoerd': 4127, 'Jack': 4098, 'Dcab': 8637678}
      >>> print 'Jack: %(Jack)d; Sjoerd: %(Sjoerd)d; Dcab: %(Dcab)d' % table
      Jack: 4098; Sjoerd: 4127; Dcab: 8637678

This is particularly useful in combination with the new built-in `vars()` function, which returns a dictionary containing all local variables.

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7.2 Reading and Writing Files

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

      >>> f=open('/tmp/workfile', 'w')
      >>> print f
      <open file '/tmp/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.

On Windows and the Macintosh, `'b'` appended to the mode opens the file in binary mode, so there are also modes like `'rb'`, `'wb'`, and `'r+b'`. Windows makes a distinction between text and binary files; the end-of-line characters in text files are automatically altered slightly when data is read or written. This behind-the-scenes modification to file data is fine for ASCII text files, but it'll corrupt binary data like that in JPEGs or .EXE files. Be very careful to use binary mode when reading and writing such files. (Note that the precise semantics of text mode on the Macintosh depends on the underlying C library being used.)

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7.2.1 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. 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()
      ''

`f.readlines()` returns a list containing all the lines of data in the file. If given an optional parameter sizehint, it reads that many bytes from the file and enough more to complete a line, and returns the lines from that. This is often used to allow efficient reading of a large file by lines, but without having to load the entire file in memory. Only complete lines will be returned.

      >>> f.readlines()
      ['This is the first line of the file.\n', 'Second line of the file\n']

`f.write(string)` writes the contents of string to the file, returning `None`.

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

`f.tell()` returns an integer giving the file object's current position in the file, measured in bytes from the beginning of the file. 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('/tmp/workfile', 'r+')
      >>> f.write('0123456789abcdef')
      >>> f.seek(5)     # Go to the 6th byte in the file
      >>> f.read(1)
      '5'
      >>> f.seek(-3, 2) # Go to the 3rd byte before the end
      >>> f.read(1)
      'd'

When you're done with a file, call `f.close()` to close it and free up any system resources taken up by the open file. After 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 ?
      ValueError: I/O operation on closed file

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.

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7.2.2 The `pickle` Module

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 `string.atoi()`, which takes a string like `'123'` and returns its numeric value 123. However, when you want to save more complex data types like lists, dictionaries, or class instances, things get a lot more complicated.

Rather than have users be constantly writing and debugging code to save complicated data types, Python provides a standard module called `pickle`. This is an amazing module that can take almost any Python object (even some forms of Python code!), and convert it to a string representation; this process is called pickling. Reconstructing the object from the string representation is called unpickling. Between pickling and unpickling, the string representing the object may have been stored in a file or data, or sent over a network connection to some distant machine.

If you have an object `x`, and a file object `f` that's been opened for writing, the simplest way to pickle the object takes only one line of code:

      pickle.dump(x, f)

To unpickle the object again, if `f` is a file object which has been opened for reading:

      x = pickle.load(f)

(There are other variants of this, used when pickling many objects or when you don't want to write the pickled data to a file; consult the complete documentation for `pickle` in the Library Reference.)

`pickle` is the standard way to make Python objects which can be stored and reused by other programs or by a future invocation of the same program; the technical term for this is a persistent object. Because `pickle` is so widely used, many authors who write Python extensions take care to ensure that new data types such as matrices can be properly pickled and unpickled.