Guido van Rossum believes that using indentation for grouping is extremely
elegant and contributes a lot to the clarity of the average Python program.
-Most people learn to love this feature after awhile.
+Most people learn to love this feature after a while.
Since there are no begin/end brackets there cannot be a disagreement between
grouping perceived by the parser and the human reader. Occasionally C
People are often very surprised by results like this::
- >>> 1.2-1.0
+ >>> 1.2 - 1.0
0.199999999999999996
and think it is a bug in Python. It's not. This has nothing to do with Python,
``==`` fails. Instead, you have to check that the difference between the two
numbers is less than a certain threshold::
- epsilon = 0.0000000000001 # Tiny allowed error
+ epsilon = 0.0000000000001 # Tiny allowed error
expected_result = 0.4
if expected_result-epsilon <= computation() <= expected_result+epsilon:
Second, it means that no special syntax is necessary if you want to explicitly
reference or call the method from a particular class. In C++, if you want to
use a method from a base class which is overridden in a derived class, you have
-to use the ``::`` operator -- in Python you can write baseclass.methodname(self,
-<argument list>). This is particularly useful for :meth:`__init__` methods, and
-in general in cases where a derived class method wants to extend the base class
-method of the same name and thus has to call the base class method somehow.
+to use the ``::`` operator -- in Python you can write
+``baseclass.methodname(self, <argument list>)``. This is particularly useful
+for :meth:`__init__` methods, and in general in cases where a derived class
+method wants to extend the base class method of the same name and thus has to
+call the base class method somehow.
Finally, for instance variables it solves a syntactic problem with assignment:
since local variables in Python are (by definition!) those variables to which a
-value assigned in a function body (and that aren't explicitly declared global),
-there has to be some way to tell the interpreter that an assignment was meant to
-assign to an instance variable instead of to a local variable, and it should
-preferably be syntactic (for efficiency reasons). C++ does this through
+value is assigned in a function body (and that aren't explicitly declared
+global), there has to be some way to tell the interpreter that an assignment was
+meant to assign to an instance variable instead of to a local variable, and it
+should preferably be syntactic (for efficiency reasons). C++ does this through
declarations, but Python doesn't have declarations and it would be a pity having
-to introduce them just for this purpose. Using the explicit "self.var" solves
+to introduce them just for this purpose. Using the explicit ``self.var`` solves
this nicely. Similarly, for using instance variables, having to write
-"self.var" means that references to unqualified names inside a method don't have
-to search the instance's directories. To put it another way, local variables
-and instance variables live in two different namespaces, and you need to tell
-Python which namespace to use.
+``self.var`` means that references to unqualified names inside a method don't
+have to search the instance's directories. To put it another way, local
+variables and instance variables live in two different namespaces, and you need
+to tell Python which namespace to use.
Why can't I use an assignment in an expression?
"1, 2, 4, 8, 16".split(", ")
is an instruction to a string literal to return the substrings delimited by the
-given separator (or, by default, arbitrary runs of white space). In this case a
-Unicode string returns a list of Unicode strings, an ASCII string returns a list
-of ASCII strings, and everyone is happy.
+given separator (or, by default, arbitrary runs of white space).
:meth:`~str.join` is a string method because in using it you are telling the
separator string to iterate over a sequence of strings and insert itself between
adjacent elements. This method can be used with any argument which obeys the
rules for sequence objects, including any new classes you might define yourself.
-
-Because this is a string method it can work for Unicode strings as well as plain
-ASCII strings. If ``join()`` were a method of the sequence types then the
-sequence types would have to decide which type of string to return depending on
-the type of the separator.
-
-.. XXX remove next paragraph eventually
-
-If none of these arguments persuade you, then for the moment you can continue to
-use the ``join()`` function from the string module, which allows you to write ::
-
- string.join(['1', '2', '4', '8', '16'], ", ")
+Similar methods exist for bytes and bytearray objects.
How fast are exceptions?
expensive. In versions of Python prior to 2.0 it was common to use this idiom::
try:
- value = dict[key]
+ value = mydict[key]
except KeyError:
- dict[key] = getvalue(key)
- value = dict[key]
+ mydict[key] = getvalue(key)
+ value = mydict[key]
This only made sense when you expected the dict to have the key almost all the
time. If that wasn't the case, you coded it like this::
- if key in dict(key):
- value = dict[key]
+ if mydict.has_key(key):
+ value = mydict[key]
else:
- dict[key] = getvalue(key)
- value = dict[key]
+ mydict[key] = getvalue(key)
+ value = mydict[key]
For this specific case, you could also use ``value = dict.setdefault(key,
getvalue(key))``, but only if the ``getvalue()`` call is cheap enough because it
-----------------------------------------------------------------
Not easily. Python's high level data types, dynamic typing of objects and
-run-time invocation of the interpreter (using :func:`eval` or :keyword:`exec`)
+run-time invocation of the interpreter (using :func:`eval` or :func:`exec`)
together mean that a "compiled" Python program would probably consist mostly of
calls into the Python run-time system, even for seemingly simple operations like
``x+1``.
<http://www.cosc.canterbury.ac.nz/~greg/python/Pyrex/>`_, `PyInline
<http://pyinline.sourceforge.net/>`_, `Py2Cmod
<http://sourceforge.net/projects/py2cmod/>`_, and `Weave
-<http://www.scipy.org/site_content/weave>`_.
+<http://www.scipy.org/Weave>`_.
How does Python manage memory?
difference can cause some subtle porting problems if your Python code depends on
the behavior of the reference counting implementation.
-Sometimes objects get stuck in tracebacks temporarily and hence are not
-deallocated when you might expect. Clear the tracebacks with::
+.. XXX relevant for Python 3?
- import sys
- sys.exc_clear()
- sys.exc_traceback = sys.last_traceback = None
+ Sometimes objects get stuck in traceback temporarily and hence are not
+ deallocated when you might expect. Clear the traceback with::
-Tracebacks are used for reporting errors, implementing debuggers and related
-things. They contain a portion of the program state extracted during the
-handling of an exception (usually the most recent exception).
+ import sys
+ sys.last_traceback = None
-In the absence of circularities and tracebacks, Python programs need not
-explicitly manage memory.
+ Tracebacks are used for reporting errors, implementing debuggers and related
+ things. They contain a portion of the program state extracted during the
+ handling of an exception (usually the most recent exception).
+
+In the absence of circularities, Python programs do not need to manage memory
+explicitly.
Why doesn't Python use a more traditional garbage collection scheme? For one
thing, this is not a C standard feature and hence it's not portable. (Yes, we
In Jython, the following code (which is fine in CPython) will probably run out
of file descriptors long before it runs out of memory::
- for file in <very long list of files>:
+ for file in very_long_list_of_files:
f = open(file)
c = f.read(1)
Using the current reference counting and destructor scheme, each new assignment
to f closes the previous file. Using GC, this is not guaranteed. If you want
to write code that will work with any Python implementation, you should
-explicitly close the file; this will work regardless of GC::
+explicitly close the file or use the :keyword:`with` statement; this will work
+regardless of GC::
- for file in <very long list of files>:
- f = open(file)
- c = f.read(1)
- f.close()
+ for file in very_long_list_of_files:
+ with open(file) as f:
+ c = f.read(1)
Why isn't all memory freed when Python exits?
- Hash lists by their address (object ID). This doesn't work because if you
construct a new list with the same value it won't be found; e.g.::
- d = {[1,2]: '12'}
- print d[[1,2]]
+ mydict = {[1, 2]: '12'}
+ print(mydict[[1, 2]])
- would raise a KeyError exception because the id of the ``[1,2]`` used in the
+ would raise a KeyError exception because the id of the ``[1, 2]`` used in the
second line differs from that in the first line. In other words, dictionary
keys should be compared using ``==``, not using :keyword:`is`.
There is a trick to get around this if you need to, but use it at your own risk:
You can wrap a mutable structure inside a class instance which has both a
-:meth:`__cmp_` and a :meth:`__hash__` method. You must then make sure that the
+:meth:`__eq__` and a :meth:`__hash__` method. You must then make sure that the
hash value for all such wrapper objects that reside in a dictionary (or other
hash based structure), remain fixed while the object is in the dictionary (or
other structure). ::
class ListWrapper:
def __init__(self, the_list):
self.the_list = the_list
- def __cmp__(self, other):
+ def __eq__(self, other):
return self.the_list == other.the_list
def __hash__(self):
l = self.the_list
result = 98767 - len(l)*555
- for i in range(len(l)):
+ for i, el in enumerate(l):
try:
- result = result + (hash(l[i]) % 9999999) * 1001 + i
- except:
+ result = result + (hash(el) % 9999999) * 1001 + i
+ except Exception:
result = (result % 7777777) + i * 333
return result
members of the list may be unhashable and also by the possibility of arithmetic
overflow.
-Furthermore it must always be the case that if ``o1 == o2`` (ie ``o1.__cmp__(o2)
-== 0``) then ``hash(o1) == hash(o2)`` (ie, ``o1.__hash__() == o2.__hash__()``),
+Furthermore it must always be the case that if ``o1 == o2`` (ie ``o1.__eq__(o2)
+is True``) then ``hash(o1) == hash(o2)`` (ie, ``o1.__hash__() == o2.__hash__()``),
regardless of whether the object is in a dictionary or not. If you fail to meet
these restrictions dictionaries and other hash based structures will misbehave.
creates a new list from a provided iterable, sorts it and returns it. For
example, here's how to iterate over the keys of a dictionary in sorted order::
- for key in sorted(dict.iterkeys()):
- ... # do whatever with dict[key]...
+ for key in sorted(mydict):
+ ... # do whatever with mydict[key]...
How do you specify and enforce an interface spec in Python?
This type of bug commonly bites neophyte programmers. Consider this function::
- def foo(D={}): # Danger: shared reference to one dict for all calls
+ def foo(mydict={}): # Danger: shared reference to one dict for all calls
... compute something ...
- D[key] = value
- return D
+ mydict[key] = value
+ return mydict
-The first time you call this function, ``D`` contains a single item. The second
-time, ``D`` contains two items because when ``foo()`` begins executing, ``D``
-starts out with an item already in it.
+The first time you call this function, ``mydict`` contains a single item. The
+second time, ``mydict`` contains two items because when ``foo()`` begins
+executing, ``mydict`` starts out with an item already in it.
It is often expected that a function call creates new objects for default
values. This is not what happens. Default values are created exactly once, when
inside the function, check if the parameter is ``None`` and create a new
list/dictionary/whatever if it is. For example, don't write::
- def foo(dict={}):
+ def foo(mydict={}):
...
but::
- def foo(dict=None):
- if dict is None:
- dict = {} # create a new dict for local namespace
+ def foo(mydict=None):
+ if mydict is None:
+ mydict = {} # create a new dict for local namespace
This feature can be useful. When you have a function that's time-consuming to
compute, a common technique is to cache the parameters and the resulting value
reasonable uses of the "go" or "goto" constructs of C, Fortran, and other
languages. For example::
- class label: pass # declare a label
+ class label: pass # declare a label
try:
...
- if (condition): raise label() # goto label
+ if (condition): raise label() # goto label
...
- except label: # where to goto
+ except label: # where to goto
pass
...
If you're trying to build Windows pathnames, note that all Windows system calls
accept forward slashes too::
- f = open("/mydir/file.txt") # works fine!
+ f = open("/mydir/file.txt") # works fine!
If you're trying to build a pathname for a DOS command, try e.g. one of ::
def foo(a):
with a:
- print x
+ print(x)
The snippet assumes that "a" must have a member attribute called "x". However,
there is nothing in Python that tells the interpreter this. What should happen
The primary benefit of "with" and similar language features (reduction of code
volume) can, however, easily be achieved in Python by assignment. Instead of::
- function(args).dict[index][index].a = 21
- function(args).dict[index][index].b = 42
- function(args).dict[index][index].c = 63
+ function(args).mydict[index][index].a = 21
+ function(args).mydict[index][index].b = 42
+ function(args).mydict[index][index].c = 63
write this::
- ref = function(args).dict[index][index]
+ ref = function(args).mydict[index][index]
ref.a = 21
ref.b = 42
ref.c = 63
This also has the side-effect of increasing execution speed because name
bindings are resolved at run-time in Python, and the second version only needs
-to perform the resolution once. If the referenced object does not have a, b and
-c attributes, of course, the end result is still a run-time exception.
+to perform the resolution once.
Why are colons required for the if/while/def/class statements?
the experimental ABC language). Consider this::
if a == b
- print a
+ print(a)
versus ::
if a == b:
- print a
+ print(a)
Notice how the second one is slightly easier to read. Notice further how a
colon sets off the example in this FAQ answer; it's a standard usage in English.
The arguments are the same as for the Popen constructor. Example:
- retcode = call(["ls", "-l"])
+ >>> retcode = call(["ls", "-l"])
check_call(*popenargs, **kwargs):
Run command with arguments. Wait for command to complete. If the
The arguments are the same as for the Popen constructor. Example:
- check_call(["ls", "-l"])
+ >>> check_call(["ls", "-l"])
+ 0
getstatusoutput(cmd):
Return (status, output) of executing cmd in a shell.
is stripped from the output. The exit status for the command can be
interpreted according to the rules for the C function wait(). Example:
- >>> import subprocess
>>> subprocess.getstatusoutput('ls /bin/ls')
(0, '/bin/ls')
>>> subprocess.getstatusoutput('cat /bin/junk')
Like getstatusoutput(), except the exit status is ignored and the return
value is a string containing the command's output. Example:
- >>> import subprocess
>>> subprocess.getoutput('ls /bin/ls')
'/bin/ls'
check_output(*popenargs, **kwargs):
- Run command with arguments and return its output as a byte string.
+ Run command with arguments and return its output as a byte string.
- If the exit code was non-zero it raises a CalledProcessError. The
- CalledProcessError object will have the return code in the returncode
- attribute and output in the output attribute.
+ If the exit code was non-zero it raises a CalledProcessError. The
+ CalledProcessError object will have the return code in the returncode
+ attribute and output in the output attribute.
- The arguments are the same as for the Popen constructor. Example:
+ The arguments are the same as for the Popen constructor. Example:
- output = subprocess.check_output(["ls", "-l", "/dev/null"])
+ >>> output = subprocess.check_output(["ls", "-l", "/dev/null"])
Exceptions
def check_output(*popenargs, **kwargs):
- """Run command with arguments and return its output as a byte string.
+ r"""Run command with arguments and return its output as a byte string.
If the exit code was non-zero it raises a CalledProcessError. The
CalledProcessError object will have the return code in the returncode
The arguments are the same as for the Popen constructor. Example:
>>> check_output(["ls", "-l", "/dev/null"])
- 'crw-rw-rw- 1 root root 1, 3 Oct 18 2007 /dev/null\n'
+ b'crw-rw-rw- 1 root root 1, 3 Oct 18 2007 /dev/null\n'
The stdout argument is not allowed as it is used internally.
- To capture standard error in the result, use stderr=subprocess.STDOUT.
+ To capture standard error in the result, use stderr=STDOUT.
>>> check_output(["/bin/sh", "-c",
- "ls -l non_existent_file ; exit 0"],
- stderr=subprocess.STDOUT)
- 'ls: non_existent_file: No such file or directory\n'
+ ... "ls -l non_existent_file ; exit 0"],
+ ... stderr=STDOUT)
+ b'ls: non_existent_file: No such file or directory\n'
"""
if 'stdout' in kwargs:
raise ValueError('stdout argument not allowed, it will be overridden.')
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