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.

Which methods you can to use to output data in Python?

• expression statements in interactive mode
• print function and derivative functions
• io.TextIOBase.write method of file objects
• the standard output file can be referenced as sys.stdout

Which methods you can use to format output data in Python?

• 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'
print(f'Results of the {year} {event}' 'Results of the 2016 Referendum')
# Results of the 2016 ReferendumResults of the 2016 Referendum

• The 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. In the following code block there are two examples of how to format variables:

yes_votes = 42_572_654
total_votes = 85_705_149
percentage = yes_votes / total_votes
# 42572654 YES votes  49.67%'), yes_votes padded, percentage 2 decimal places
print("{:-9} YES votes  {:2.2%}".format(yes_votes, percentage))

• 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 ==repr or str== functions.

What is difference between str and repr functions?
str - human-readable; repr - unambiguous (as is) representation of the object. The str function is meant to return representations of values which are fairly human-readable, while repr is meant to generate representations which can be read by the interpreter (or will force a SyntaxError if there is no equivalent syntax).
For objects which don’t have a particular representation for human consumption, str will return the same value as repr. Many values, such as numbers or structures like lists and dictionaries, have the same representation using either function. Strings, in particular, have two distinct representations.

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'
print(hello) # hello, world
 
hellos = repr(hello)
print(hellos) # 'hello, world\n'
 
# The argument to `repr()` (and `str()`) may be any Python object
repr((x, y, ('spam', 'eggs')))  # "(32.5, 40000, ('spam', 'eggs'))"
 

The string module contains a 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.

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}.

Is it possible to adjust variable formatting with f-strings?
Yes. 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.

How to set minimum width for variable formatting with f-strings?
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
 

How to apply ascii, str and raw for variable in f-strings?
You can use these modifiers to convert the value before it is formatted. '!a' applies ascii, '!s' applies str, and '!r' applies repr:

animals = 'eels'
print(f'My hovercraft is full of {animals}.')
# My hovercraft is full of eels.
 
animals = 'пушистик eels'
print(f'My hovercraft is full of {animals!a}.')
# My hovercraft is full of '\u043f\u0443\u0448\u0438\u0441\u0442\u0438\u043a eels'.
 
print(f'My hovercraft is full of {animals!r}.')
# My hovercraft is full of 'eels'.

What = specifier after expression in f-strings does?
This is self-documenting expressions. The = expand an expression to the text of the expression with equal sign and the representation of the evaluated expression:

bugs = 'roaches'
count = 13
area = 'living room'
print(f'Debugging {bugs=} {count=} {area=}')
# Debugging bugs='roaches' count=13 area='living room'

See also What’s New In Python 3.8

How to use str.format method?
Basic usage of the 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 `str.format` method. A number
# in the brackets can be used to refer to the position of the object
# passed into the `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 `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` dictionary as keyword
# arguments with the `**` notation. :
table = {'Sjoerd': 4127, 'Jack': 4098, 'Dcab': 8637678}
print('Jack: {Jack:d}; Sjoerd: {Sjoerd:d}; Dcab: {Dcab:d}'.format(**table))
# Jack: 4098; Sjoerd: 4127; Dcab: 8637678
 
# This is particularly useful in combination with the built-in function
# `vars`, which returns a dictionary containing all local variables:
table = {k: str(v) for k, v in vars().items()}
message = " ".join([f'{k}: ' + '{' + k +'};' for k in table.keys()])
print(message)
# __name__: {__name__}; __doc__: {__doc__}; __package__: {__package__}; ...
print(message.format(**table))
# __name__: __main__; __doc__: None; __package__: None; __loader__: ...

What this code will output?

for x in range(1, 11):
    print('{0:2d} {1:3d} {2:4d}'.format(x, x*x, x*x*x))

The following lines produce a tidily aligned set of columns giving integers and their squares and cubes:
Results:

 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 str.format, see formatstrings

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

How rjust (or similar string methods) is working in general, what if variable is longer than padding?
The 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 also similar methods str.ljust and str.center.
These methods do not write anything, they just return a new string.
If the input string is too long, they don’t truncate it, but return it unchanged; this will mess up your column lay-out but that’s usually better than the alternative, which would be lying about a value. (If you really want truncation you can always add a slice operation, as in x.rjust(n)[:n].)

How to pad a numeric string on the left with zeros (str method)?
str.zfill, which pads a numeric string on the left with zeros. It understands about plus and minus signs:

'12'.zfill(5)             # '00012'
'-3.14'.zfill(7)          # '-003.14'
'3.14159265359'.zfill(5)  # '3.14159265359'

How working old-string-formatting in Python (%)?
The % operator (modulo) can also be used for string formatting. Given format % values (where format is a string), % conversion specifications in format are replaced with zero or more elements of values. This operation is commonly known as string interpolation. For example:

import math
print('The value of pi is approximately %5.3f.' % math.pi)
# The value of pi is approximately 3.142.

open function returns a file object, and is most commonly used with two positional arguments and one keyword argument (which one):
open(filename, mode, encoding=None)

# filename, mode, encoding
f = open('/tmp/workfile', 'w', encoding="utf-8")
print(f)
# <_io.TextIOWrapper name='/tmp/workfile' mode='w' encoding='utf-8'>

Which text mode arguments can be used with open function?
mode argument (way in which the file be used) in built-in open file function can be (text mode):

• 'r' when the file will only be read (used by default, if mode omitted);
• 'w' for only writing (an existing file with the same name will be erased);
• '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.

Normally, files are opened with open function in ==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. Because UTF-8 is the modern de-facto standard, encoding="utf-8" is recommended unless you know that you need to use a different encoding.

Appending a 'b' to the open function mode opens the file in ==binary mode==. Data is read and written as bytes objects. You can not specify encoding when opening file in binary mode.

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 is appropriate for text files. Be very careful to use binary mode when reading and writing any binary files.

How to automatically close file after open function finishes or there was some exception during writing?
Use the with keyword when dealing with file objects. with is also much shorter than writing equivalent try-finally blocks.

f = None  # just to show that `f` will be reassigned
with open('/tmp/workfile', encoding="utf-8") as f:
    print(f.read())
 
# We can check that the file has been automatically closed.
print(f.closed)  # True

If you’re not using the with keyword, then you should call ==f.close()== on file object to close the file and immediately free up any system resources used by it.

WARNING

Calling f.write() without using the ==with== keyword or calling f.close() might result in the arguments of f.write() not being completely written to the disk, even if the program exits successfully.

What if you try to use file object after it was closed?
After a file object is closed, either by a with statement or by calling f.close(), attempts to use the file object will automatically fail.

f = open('/tmp/workfile', 'w', encoding="utf-8")
f.close()
f.read()
# Traceback (most recent call last):
#   File "<stdin>", line 1, in <module>
# ValueError: I/O operation on closed file.

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 characters (in text mode) or size bytes (in binary mode) are read and returned. If the end of the file has been reached, f.read() will return an empty string (''). :

with open('/tmp/workfile') as f:
    print(f.read())  # Entire file is read and printed
    print(f.read())  # Empty string

==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. :

# The file data is:
# This is the first line of the file.
# Second line of the file.
 
with open('/tmp/workfile') as f:
    print(f.readline(), end="") # 'This is the first line of the file.\n'
    print(f.readline(), end="") # 'Second line of the file\n'
    print(f.readline(), end="") # ''

How to read lines from file in more efficient way?
For reading lines from a file, you can loop over the file object. This is memory efficient, fast, and leads to simple code:

# The file data is:
# This is the first line of the file.
# Second line of the file.
with open('/tmp/workfile') as f:
    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 use ==list(f) or f.readlines()==.

f.write(string) writes the contents of string to the file, returning the number of characters written. :

with open('/tmp/workfile', 'w') as f:
    lines_written = f.write("""\
This is the first line of the file.
Second line of the file.\
""")
    print(lines_written)  # 60

How to write non-string data to file?
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:

with open('/tmp/workfile', 'w') as f:
    value = ('the answer', 42)
    # f.write(value) # TypeError
    s = str(value)  # convert the tuple to string
    print(f.write(s))  # 18
    print(f.tell())    # 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, whence)==. The position is computed from adding offset to a reference point; the reference point is selected by the whence argument. A whence 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. whence can be omitted and defaults to 0, using the beginning of the file as the reference point. :

f = open('/tmp/workfile', 'rb+')
f.truncate()  # truncate file to 0 bytes, delete all content
print(f.write(b'0123456789abcdef'))  # 16, number of written bytes
print(f.seek(5))      # 5, go to the 6th byte in the file
print(f.read(1))      # b'5', read the 6th byte
print(f.seek(-3, 2))  # 13, Go to the 3rd byte before the end
print(f.read(1))      # b'd', read the 14th byte
f.close()

Can be used f.seek(offset) with some random value in text files?
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 io.IOBase.isatty and io.IOBase.truncate which are less frequently used; consult the Library Reference for a complete guide to file objects.

When you want to save more complex data types like nested lists and dictionaries, parsing and serializing by hand (using file read method for example) becomes complicated.

Python allows you to use the popular data interchange format called JSON (JavaScript Object Notation). The standard module called json can take Python data hierarchies, and convert them to string representations; this process is called ==serializing==.

Reconstructing the data from the string representation is called ==deserializing==.

Between serializing and deserializing, the string representing the object may have been stored in a file or data, or sent over a network connection to some distant machine.

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 (==dumps== method of json module):

import json
x = [1, 'simple', 'list']
print(json.dumps(x))  # '[1, "simple", "list"]'

Another variant of the json.dumps function, called json.dump, simply serializes the object to a ==text file, like f in example==.

json.dump(x, f)

To decode the object again (JSON), if f is a binary file or text file object which has been opened for reading, need to use ==json.load== method:

# JSON files must be encoded in UTF-8. Use `encoding="utf-8"` when
# opening JSON file as a `text file` for both of reading and writing.
x = json.load(f)

Contrary to JSON, ==pickle== is a protocol which allows the serialization of arbitrarily complex Python objects. As such, it is specific to Python and cannot be used to communicate with applications written in other languages. It is also insecure by default: deserializing its data coming from an untrusted source can execute arbitrary code, if the data was crafted by a skilled attacker.