Future statements tell the interpreter to compile some semantics as the semantics which will be available in the future Python version. In other words, Python uses from __future__ import feature to backport features from other higher Python versions to the current interpreter. In Python 3, many features such as print_function are already enabled, but we still leave these future statements for backward compatibility.

Future statements are NOT import statements. Future statements change how Python interprets the code. They MUST be at the top of the file. Otherwise, Python interpreter will raise SyntaxError.

If you’re interested in future statements and want to acquire more explanation, further information can be found on PEP 236 - Back to the __future__

List All New Features

__future__ is a Python module. We can use it to check what kind of future features can import to current Python interpreter. The fun is import __future__ is NOT a future statement, it is a import statement.

>>> from pprint import pprint
>>> import __future__
>>> pprint(__future__.all_feature_names)

Future statements not only change the behavior of the Python interpreter but also import __future__._Feature into the current program.

>>> from __future__ import print_function
>>> print_function
_Feature((2, 6, 0, 'alpha', 2), (3, 0, 0, 'alpha', 0), 65536)


As print function, making text become Unicode is another infamous decision. Nevertheless, many modern programming languages’ text is Unicode. This change compels us to decode texts early in order to prevent runtime error after we run programs for a while. Further information can be found on PEP 3112.

>>> type("Guido") # string type is str in python2
<type 'str'>
>>> from __future__ import unicode_literals
>>> type("Guido") # string type become unicode
<type 'unicode'>


Sometimes, it is counterintuitive when the division result is int or long. In this case, Python 3 enables the true division by default. However, in Python 2, we have to backport division to the current interpreter. Further information can be found on PEP 238.

>>> 1 / 2
>>> from __future__ import division
>>> 1 / 2   # return a float (classic division)
>>> 1 // 2  # return a int (floor division)


Before Python 3.7, we cannot assign annotations in a class or a function if it is not available in the current scope. A common situation is the definition of a container class.

class Tree(object):

    def insert(self, tree: Tree): ...


$ python3 foo.py
Traceback (most recent call last):
  File "foo.py", line 1, in <module>
    class Tree(object):
  File "foo.py", line 3, in Tree
    def insert(self, tree: Tree): ...
NameError: name 'Tree' is not defined

In this case, the definition of the class is not available yet. Python interpreter cannot parse the annotation during their definition time. To solve this issue, Python uses string literals to replace the class.

class Tree(object):

    def insert(self, tree: 'Tree'): ...

After version 3.7, Python introduces the future statement, annotations, to perform postponed evaluation. It will become the default feature in Python 4. For further information please refer to PEP 563.

from __future__ import annotations

class Tree(object):

    def insert(self, tree: Tree): ...

BDFL Retirement

New in Python 3.1

PEP 401 is just an Easter egg. This feature brings the current interpreter back to the past. It enables the diamond operator <> in Python 3.

>>> 1 != 2
>>> from __future__ import barry_as_FLUFL
>>> 1 != 2
  File "<stdin>", line 1
    1 != 2
SyntaxError: with Barry as BDFL, use '<>' instead of '!='
>>> 1 <> 2


braces is an Easter egg. The source code can be found on future.c.

>>> from __future__ import braces
  File "<stdin>", line 1
SyntaxError: not a chance