
Idioms and Anti-Idioms in Python
********************************

Author:
   Moshe Zadka

This document is placed in the public domain.


Abstract
^^^^^^^^

This document can be considered a companion to the tutorial. It shows
how to use Python, and even more importantly, how *not* to use Python.


Language Constructs You Should Not Use
======================================

While Python has relatively few gotchas compared to other languages,
it still has some constructs which are only useful in corner cases, or
are plain dangerous.


from module import *
--------------------


Inside Function Definitions
~~~~~~~~~~~~~~~~~~~~~~~~~~~

``from module import *`` is *invalid* inside function definitions.
While many versions of Python do not check for the invalidity, it does
not make it more valid, no more than having a smart lawyer makes a man
innocent. Do not use it like that ever. Even in versions where it was
accepted, it made the function execution slower, because the compiler
could not be certain which names are local and which are global. In
Python 2.1 this construct causes warnings, and sometimes even errors.


At Module Level
~~~~~~~~~~~~~~~

While it is valid to use ``from module import *`` at module level it
is usually a bad idea. For one, this loses an important property
Python otherwise has --- you can know where each toplevel name is
defined by a simple "search" function in your favourite editor. You
also open yourself to trouble in the future, if some module grows
additional functions or classes.

One of the most awful question asked on the newsgroup is why this
code:

   f = open("www")
   f.read()

does not work. Of course, it works just fine (assuming you have a file
called "www".) But it does not work if somewhere in the module, the
statement ``from os import *`` is present. The ``os`` module has a
function called ``open()`` which returns an integer. While it is very
useful, shadowing a builtin is one of its least useful properties.

Remember, you can never know for sure what names a module exports, so
either take what you need --- ``from module import name1, name2``, or
keep them in the module and access on a per-need basis --- ``import
module; print(module.name)``.


When It Is Just Fine
~~~~~~~~~~~~~~~~~~~~

There are situations in which ``from module import *`` is just fine:

* The interactive prompt. For example, ``from math import *`` makes
  Python an amazing scientific calculator.

* When extending a module in C with a module in Python.

* When the module advertises itself as ``from import *`` safe.


from module import name1, name2
-------------------------------

This is a "don't" which is much weaker than the previous "don't"s but
is still something you should not do if you don't have good reasons to
do that. The reason it is usually bad idea is because you suddenly
have an object which lives in two separate namespaces. When the
binding in one namespace changes, the binding in the other will not,
so there will be a discrepancy between them. This happens when, for
example, one module is reloaded, or changes the definition of a
function at runtime.

Bad example:

   # foo.py
   a = 1

   # bar.py
   from foo import a
   if something():
       a = 2 # danger: foo.a != a

Good example:

   # foo.py
   a = 1

   # bar.py
   import foo
   if something():
       foo.a = 2


except:
-------

Python has the ``except:`` clause, which catches all exceptions. Since
*every* error in Python raises an exception, using ``except:`` can
make many programming errors look like runtime problems, which hinders
the debugging process.

The following code shows a great example of why this is bad:

   try:
       foo = opne("file") # misspelled "open"
   except:
       sys.exit("could not open file!")

The second line triggers a ``NameError``, which is caught by the
except clause. The program will exit, and the error message the
program prints will make you think the problem is the readability of
``"file"`` when in fact the real error has nothing to do with
``"file"``.

A better way to write the above is

   try:
       foo = opne("file")
   except IOError:
       sys.exit("could not open file")

When this is run, Python will produce a traceback showing the
``NameError``, and it will be immediately apparent what needs to be
fixed.

Because ``except:`` catches *all* exceptions, including
``SystemExit``, ``KeyboardInterrupt``, and ``GeneratorExit`` (which is
not an error and should not normally be caught by user code), using a
bare ``except:`` is almost never a good idea.  In situations where you
need to catch all "normal" errors, such as in a framework that runs
callbacks, you can catch the base class for all normal exceptions,
``Exception``.


Exceptions
==========

Exceptions are a useful feature of Python. You should learn to raise
them whenever something unexpected occurs, and catch them only where
you can do something about them.

The following is a very popular anti-idiom

   def get_status(file):
       if not os.path.exists(file):
           print("file not found")
           sys.exit(1)
       return open(file).readline()

Consider the case where the file gets deleted between the time the
call to ``os.path.exists()`` is made and the time ``open()`` is
called. In that case the last line will raise an ``IOError``.  The
same thing would happen if *file* exists but has no read permission.
Since testing this on a normal machine on existent and non-existent
files makes it seem bugless, the test results will seem fine, and the
code will get shipped.  Later an unhandled ``IOError`` (or perhaps
some other ``EnvironmentError``) escapes to the user, who gets to
watch the ugly traceback.

Here is a somewhat better way to do it.

   def get_status(file):
       try:
           return open(file).readline()
       except EnvironmentError as err:
           print("Unable to open file: {}".format(err))
           sys.exit(1)

In this version, *either* the file gets opened and the line is read
(so it works even on flaky NFS or SMB connections), or an error
message is printed that provides all the available information on why
the open failed, and the application is aborted.

However, even this version of ``get_status()`` makes too many
assumptions --- that it will only be used in a short running script,
and not, say, in a long running server. Sure, the caller could do
something like

   try:
       status = get_status(log)
   except SystemExit:
       status = None

But there is a better way.  You should try to use as few ``except``
clauses in your code as you can --- the ones you do use will usually
be inside calls which should always succeed, or a catch-all in a main
function.

So, an even better version of ``get_status()`` is probably

   def get_status(file):
       return open(file).readline()

The caller can deal with the exception if it wants (for example, if it
tries several files in a loop), or just let the exception filter
upwards to *its* caller.

But the last version still has a serious problem --- due to
implementation details in CPython, the file would not be closed when
an exception is raised until the exception handler finishes; and,
worse, in other implementations (e.g., Jython) it might not be closed
at all regardless of whether or not an exception is raised.

The best version of this function uses the ``open()`` call as a
context manager, which will ensure that the file gets closed as soon
as the function returns:

   def get_status(file):
       with open(file) as fp:
           return fp.readline()


Using the Batteries
===================

Every so often, people seem to be writing stuff in the Python library
again, usually poorly. While the occasional module has a poor
interface, it is usually much better to use the rich standard library
and data types that come with Python than inventing your own.

A useful module very few people know about is ``os.path``. It  always
has the correct path arithmetic for your operating system, and will
usually be much better than whatever you come up with yourself.

Compare:

   # ugh!
   return dir+"/"+file
   # better
   return os.path.join(dir, file)

More useful functions in ``os.path``: ``basename()``,  ``dirname()``
and ``splitext()``.

There are also many useful built-in functions people seem not to be
aware of for some reason: ``min()`` and ``max()`` can find the
minimum/maximum of any sequence with comparable semantics, for
example, yet many people write their own ``max()``/``min()``. Another
highly useful function is ``functools.reduce()`` which can be used to
repeatly apply a binary operation to a sequence, reducing it to a
single value.  For example, compute a factorial with a series of
multiply operations:

   >>> n = 4
   >>> import operator, functools
   >>> functools.reduce(operator.mul, range(1, n+1))
   24

When it comes to parsing numbers, note that ``float()``, ``int()`` and
``long()`` all accept string arguments and will reject ill-formed
strings by raising an ``ValueError``.


Using Backslash to Continue Statements
======================================

Since Python treats a newline as a statement terminator, and since
statements are often more than is comfortable to put in one line, many
people do:

   if foo.bar()['first'][0] == baz.quux(1, 2)[5:9] and \
      calculate_number(10, 20) != forbulate(500, 360):
         pass

You should realize that this is dangerous: a stray space after the
``\`` would make this line wrong, and stray spaces are notoriously
hard to see in editors. In this case, at least it would be a syntax
error, but if the code was:

   value = foo.bar()['first'][0]*baz.quux(1, 2)[5:9] \
           + calculate_number(10, 20)*forbulate(500, 360)

then it would just be subtly wrong.

It is usually much better to use the implicit continuation inside
parenthesis:

This version is bulletproof:

   value = (foo.bar()['first'][0]*baz.quux(1, 2)[5:9]
           + calculate_number(10, 20)*forbulate(500, 360))
