How do I use pre-increment/decrement operators (++, --), just like in C++?
Why does ++count run, but not change the value of the variable?
++ is not an operator. It is two + operators. The + operator is the identity operator, which does nothing. (Clarification: the + and - unary operators only work on numbers, but I presume that you wouldn't expect a hypothetical ++ operator to work on strings.)
++count
Parses as
+(+count)
Which translates to
count
You have to use the slightly longer += operator to do what you want to do:
count += 1
I suspect the ++ and -- operators were left out for consistency and simplicity. I don't know the exact argument Guido van Rossum gave for the decision, but I can imagine a few arguments:
Simpler parsing. Technically, parsing ++count is ambiguous, as it could be +, +, count (two unary + operators) just as easily as it could be ++, count (one unary ++ operator). It's not a significant syntactic ambiguity, but it does exist.
Simpler language. ++ is nothing more than a synonym for += 1. It was a shorthand invented because C compilers were stupid and didn't know how to optimize a += 1 into the inc instruction most computers have. In this day of optimizing compilers and bytecode interpreted languages, adding operators to a language to allow programmers to optimize their code is usually frowned upon, especially in a language like Python that is designed to be consistent and readable.
Confusing side-effects. One common newbie error in languages with ++ operators is mixing up the differences (both in precedence and in return value) between the pre- and post-increment/decrement operators, and Python likes to eliminate language "gotcha"-s. The precedence issues of pre-/post-increment in C are pretty hairy, and incredibly easy to mess up.
Python does not have pre and post increment operators.
In Python, integers are immutable. That is you can't change them. This is because the integer objects can be used under several names. Try this:
>>> b = 5
>>> a = 5
>>> id(a)
162334512
>>> id(b)
162334512
>>> a is b
True
a and b above are actually the same object. If you incremented a, you would also increment b. That's not what you want. So you have to reassign. Like this:
b = b + 1
Many C programmers who used python wanted an increment operator, but that operator would look like it incremented the object, while it actually reassigns it. Therefore the -= and += operators where added, to be shorter than the b = b + 1, while being clearer and more flexible than b++, so most people will increment with:
b += 1
Which will reassign b to b+1. That is not an increment operator, because it does not increment b, it reassigns it.
In short: Python behaves differently here, because it is not C, and is not a low level wrapper around machine code, but a high-level dynamic language, where increments don't make sense, and also are not as necessary as in C, where you use them every time you have a loop, for example.
While the others answers are correct in so far as they show what a mere + usually does (namely, leave the number as it is, if it is one), they are incomplete in so far as they don't explain what happens.
To be exact, +x evaluates to x.__pos__() and ++x to x.__pos__().__pos__().
I could imagine a VERY weird class structure (Children, don't do this at home!) like this:
class ValueKeeper(object):
def __init__(self, value): self.value = value
def __str__(self): return str(self.value)
class A(ValueKeeper):
def __pos__(self):
print 'called A.__pos__'
return B(self.value - 3)
class B(ValueKeeper):
def __pos__(self):
print 'called B.__pos__'
return A(self.value + 19)
x = A(430)
print x, type(x)
print +x, type(+x)
print ++x, type(++x)
print +++x, type(+++x)
TL;DR
Python does not have unary increment/decrement operators (--/++). Instead, to increment a value, use
a += 1
More detail and gotchas
But be careful here. If you're coming from C, even this is different in python. Python doesn't have "variables" in the sense that C does, instead python uses names and objects, and in python ints are immutable.
so lets say you do
a = 1
What this means in python is: create an object of type int having value 1 and bind the name a to it. The object is an instance of int having value 1, and the name a refers to it. The name a and the object to which it refers are distinct.
Now lets say you do
a += 1
Since ints are immutable, what happens here is as follows:
look up the object that a refers to (it is an int with id 0x559239eeb380)
look up the value of object 0x559239eeb380 (it is 1)
add 1 to that value (1 + 1 = 2)
create a new int object with value 2 (it has object id 0x559239eeb3a0)
rebind the name a to this new object
Now a refers to object 0x559239eeb3a0 and the original object (0x559239eeb380) is no longer refered to by the name a. If there aren't any other names refering to the original object it will be garbage collected later.
Give it a try yourself:
a = 1
print(hex(id(a)))
a += 1
print(hex(id(a)))
In python 3.8+ you can do :
(a:=a+1) #same as ++a (increment, then return new value)
(a:=a+1)-1 #same as a++ (return the incremented value -1) (useless)
You can do a lot of thinks with this.
>>> a = 0
>>> while (a:=a+1) < 5:
print(a)
1
2
3
4
Or if you want write somthing with more sophisticated syntaxe (the goal is not optimization):
>>> del a
>>> while (a := (a if 'a' in locals() else 0) + 1) < 5:
print(a)
1
2
3
4
It will return 0 even if 'a' doesn't exist without errors, and then will set it to 1
Python does not have these operators, but if you really need them you can write a function having the same functionality.
def PreIncrement(name, local={}):
#Equivalent to ++name
if name in local:
local[name]+=1
return local[name]
globals()[name]+=1
return globals()[name]
def PostIncrement(name, local={}):
#Equivalent to name++
if name in local:
local[name]+=1
return local[name]-1
globals()[name]+=1
return globals()[name]-1
Usage:
x = 1
y = PreIncrement('x') #y and x are both 2
a = 1
b = PostIncrement('a') #b is 1 and a is 2
Inside a function you have to add locals() as a second argument if you want to change local variable, otherwise it will try to change global.
x = 1
def test():
x = 10
y = PreIncrement('x') #y will be 2, local x will be still 10 and global x will be changed to 2
z = PreIncrement('x', locals()) #z will be 11, local x will be 11 and global x will be unaltered
test()
Also with these functions you can do:
x = 1
print(PreIncrement('x')) #print(x+=1) is illegal!
But in my opinion following approach is much clearer:
x = 1
x+=1
print(x)
Decrement operators:
def PreDecrement(name, local={}):
#Equivalent to --name
if name in local:
local[name]-=1
return local[name]
globals()[name]-=1
return globals()[name]
def PostDecrement(name, local={}):
#Equivalent to name--
if name in local:
local[name]-=1
return local[name]+1
globals()[name]-=1
return globals()[name]+1
I used these functions in my module translating javascript to python.
In Python, a distinction between expressions and statements is rigidly
enforced, in contrast to languages such as Common Lisp, Scheme, or
Ruby.
Wikipedia
So by introducing such operators, you would break the expression/statement split.
For the same reason you can't write
if x = 0:
y = 1
as you can in some other languages where such distinction is not preserved.
Yeah, I missed ++ and -- functionality as well. A few million lines of c code engrained that kind of thinking in my old head, and rather than fight it... Here's a class I cobbled up that implements:
pre- and post-increment, pre- and post-decrement, addition,
subtraction, multiplication, division, results assignable
as integer, printable, settable.
Here 'tis:
class counter(object):
def __init__(self,v=0):
self.set(v)
def preinc(self):
self.v += 1
return self.v
def predec(self):
self.v -= 1
return self.v
def postinc(self):
self.v += 1
return self.v - 1
def postdec(self):
self.v -= 1
return self.v + 1
def __add__(self,addend):
return self.v + addend
def __sub__(self,subtrahend):
return self.v - subtrahend
def __mul__(self,multiplier):
return self.v * multiplier
def __div__(self,divisor):
return self.v / divisor
def __getitem__(self):
return self.v
def __str__(self):
return str(self.v)
def set(self,v):
if type(v) != int:
v = 0
self.v = v
You might use it like this:
c = counter() # defaults to zero
for listItem in myList: # imaginary task
doSomething(c.postinc(),listItem) # passes c, but becomes c+1
...already having c, you could do this...
c.set(11)
while c.predec() > 0:
print c
....or just...
d = counter(11)
while d.predec() > 0:
print d
...and for (re-)assignment into integer...
c = counter(100)
d = c + 223 # assignment as integer
c = c + 223 # re-assignment as integer
print type(c),c # <type 'int'> 323
...while this will maintain c as type counter:
c = counter(100)
c.set(c + 223)
print type(c),c # <class '__main__.counter'> 323
EDIT:
And then there's this bit of unexpected (and thoroughly unwanted) behavior,
c = counter(42)
s = '%s: %d' % ('Expecting 42',c) # but getting non-numeric exception
print s
...because inside that tuple, getitem() isn't what used, instead a reference to the object is passed to the formatting function. Sigh. So:
c = counter(42)
s = '%s: %d' % ('Expecting 42',c.v) # and getting 42.
print s
...or, more verbosely, and explicitly what we actually wanted to happen, although counter-indicated in actual form by the verbosity (use c.v instead)...
c = counter(42)
s = '%s: %d' % ('Expecting 42',c.__getitem__()) # and getting 42.
print s
There are no post/pre increment/decrement operators in python like in languages like C.
We can see ++ or -- as multiple signs getting multiplied, like we do in maths (-1) * (-1) = (+1).
E.g.
---count
Parses as
-(-(-count)))
Which translates to
-(+count)
Because, multiplication of - sign with - sign is +
And finally,
-count
A straight forward workaround
c = 0
c = (lambda c_plusplus: plusplus+1)(c)
print(c)
1
No more typing
c = c + 1
Also, you could just write
c++
and finish all your code and then do search/replace for "c++", replace with "c=c+1". Just make sure regular expression search is off.
Extending Henry's answer, I experimentally implemented a syntax sugar library realizing a++: hdytto.
The usage is simple. After installing from PyPI, place sitecustomize.py:
from hdytto import register_hdytto
register_hdytto()
in your project directory. Then, make main.py:
# coding: hdytto
a = 5
print(a++)
print(++a)
b = 10 - --a
print(b--)
and run it by PYTHONPATH=. python main.py. The output will be
5
7
4
hdytto replaces a++ as ((a:=a+1)-1) when decoding the script file, so it works.
Related
In an unpacking assignment statement, can the assigned object inspect the number of variables it is being assigned to?
class MyObject:
def __iter__(self):
n = some_diabolical_hack()
print(f"yielding {n} vals")
return iter(["potato"]*n)
Something like:
>>> x, y = MyObject()
yielding 2 vals
>>> a, b, c = MyObject()
yielding 3 vals
In the more general case, can it introspect the "shape" of the target_list being used in an assignment?
>>> first, *blob, d[k], (x, y), L[3:7], obj.attr, last = MyObject()
unpacking to <_ast.Tuple object at 0xcafef00d>
Example potential use case: an improved MagicMock() which doesn't need to be pre-configured with a fixed iteration length when being used to patch out some object on the right hand side of an assignment statement.
You could use the traceback module:
import traceback
def diabolically_invoke_traceback():
call = traceback.extract_stack()[-2]
print call[3]
unpackers = call[3].split('=')[0].split(',')
print len (unpackers)
return range(len(unpackers))
In [63]: a, b, c = diabolically_invoke_traceback()
a, b, c = diabolically_invoke_traceback()
3
In [64]: a
Out[64]: 0
In [65]: b
Out[65]: 1
In [66]: c
Out[66]: 2
(Disclaimer: I don't recommend using diabolical techniques in production-quality code. Everything in this answer might not work on a different computer from mine, or a different Python version from mine, or on a non-CPython distribution, and it might not work tomorrow morning.)
Perhaps you could do this by inspecting the calling frame's bytecode. If I'm reading the bytecode guide correctly, multiple assignment is handled by the instructions UNPACK_SEQUENCE or UNPACK_EX, depending on whether the target list has a starred name. Both of these instructions provide information about the shape of the target list in their arguments.
You could write your diabolical function to climb the frame hierarchy until it finds the calling frame, and inspect the bytecode instruction that occurs after the FUNCTION_CALL that represents the right-hand-side of the assignment. (this is assuming that your call to MyObject() is the only thing on the right side of the statement). Then you can extract the target list size from the instruction's argument and return it.
import inspect
import dis
import itertools
def diabolically_retrieve_target_list_size():
#one f_back takes us to `get_diabolically_sized_list`'s frame. A second one takes us to the frame of the caller of `get_diabolically_sized_list`.
frame = inspect.currentframe().f_back.f_back
#explicitly delete frame when we're done with it to avoid reference cycles.
try:
#get the bytecode instruction that immediately follows the CALL_FUNCTION that is executing right now
bytecode_idx = frame.f_lasti // 2
unresolved_bytecodes = itertools.islice(dis.get_instructions(frame.f_code), bytecode_idx+1, bytecode_idx+3)
next_bytecode = next(unresolved_bytecodes)
if next_bytecode.opname == "UNPACK_SEQUENCE": #simple multiple assignment, like `a,b,c = ...`
return next_bytecode.arg
elif next_bytecode.opname == "EXTENDED_ARG": #multiple assignment with splat, like `a, *b, c = ...`
next_bytecode = next(unresolved_bytecodes)
if next_bytecode.opname != "UNPACK_EX":
raise Exception(f"Expected UNPACK_EX after EXTENDED_ARG, got {next_bytecode.opname} instead")
args_before_star = next_bytecode.arg % 256
args_after_star = next_bytecode.arg >> 8
return args_before_star + args_after_star
elif next_bytecode.opname in ("STORE_FAST", "STORE_NAME"): #single assignment, like `a = ...`
return 1
else:
raise Exception(f"Unrecognized bytecode: {frame.f_lasti} {next_bytecode.opname}")
finally:
del frame
def get_diabolically_sized_list():
count = diabolically_retrieve_target_list_size()
return list(range(count))
a,b,c = get_diabolically_sized_list()
print(a,b,c)
d,e,f,g,h,i = get_diabolically_sized_list()
print(d,e,f,g,h,i)
j, *k, l = get_diabolically_sized_list()
print(j,k,l)
x = get_diabolically_sized_list()
print(x)
Result:
0 1 2
0 1 2 3 4 5
0 [] 1
[0]
Suppose I have defined a function f(x), which is syntactically correct. I want to make sure that f works "functionally", in the sense that its output depends solely on the input x.
Sometimes, if the definition of f is complicated, one may unintentionally (because of a typo, or just not being careful enough) refer to some external variables in its definition, which can cause bugs that are difficult to find out.
Is there any tool, any "directive pragma" (so to say), or any "best practice" to make sure this does not happen?
Example:
xx = 1.0
def f(x, y, p=1):
return xx * y**p # A typo here: should be x * y**p
If there is no simple way to achieve this in python, which languages have such a feature? As far as I know, C, C++, and Fortran does not have this. Fortran 95 has pure subroutines and functions, but it is used by the programmer to "promise" a subroutine/function will not modify any external variables, while the subroutine/function can still take value from them.
Although it's a little hackish, you could do something like this which checks the instructions used in the function's code object:
import opcode # see /Python/Lib/opcode.py
GLOBAL_INSTRUCTIONS = {opcode.opmap['DELETE_GLOBAL'],
opcode.opmap['LOAD_GLOBAL'],
opcode.opmap['STORE_GLOBAL']}
def is_pure(func):
for inst in instructions(func.func_code.co_code):
op = inst[0]
if op in GLOBAL_INSTRUCTIONS:
return False
return True
def instructions(code):
"""Iterates over a code string yielding integer [op, arg] pairs
"""
code = map(ord, code)
i, L = 0, len(code)
extended_arg = 0
while i < L:
op = code[i]
i+= 1
if op < opcode.HAVE_ARGUMENT:
yield [op, None]
continue
oparg = code[i] + (code[i+1] << 8) + extended_arg
extended_arg = 0
i += 2
if op == opcode.EXTENDED_ARG:
extended_arg = oparg << 16
continue
yield [op, oparg]
xx = 1.0
def f(x, y, p=1):
return xx * y**p # A typo here: should be x * y**p
def f2(x, y, p=1):
return x * y**p # No typo
print(is_pure(f)) # --> False
print(is_pure(f2)) # --> True
To start with - you can ask your question just as "How to check if my function is pure".
Answer - it's impossible in python. Don't look. Also, if you want to check purity in your code, you probably 'd be better with another language.
It's not generally possible in python. If you want a language which enforces pure functions and referential transparency, try using Haskell.
If I write the following in python, I get a syntax error, why so?
a = 1
b = (a+=1)
I am using python version 2.7
what I get when I run it, the following:
>>> a = 1
>>> b = (a +=1)
File "<stdin>", line 1
b = (a +=1)
^
SyntaxError: invalid syntax
>>>
Unlike in some other languages, assignment (including augmented assignment, like +=) in Python is not an expression. This also affects things like this:
(a=1) > 2
which is legal in C, and several other languages.
The reason generally given for this is because it helps to prevent a class of bugs like this:
if a = 1: # instead of ==
pass
else:
pass
since assignment isn't an expression, this is a SyntaxError in Python. In the equivalent C code, it is a subtle bug where the variable will be modified rather than checked, the check will always be true (in C, like in Python, a non-zero integer is always truthy), and the else block can never fire.
You can still do chained assignment in Python, so this works:
>>> a = 1
>>> a = b = a+1
>>> a
2
>>> b
2
a +=1 is a statement in Python and you can't assign a statement to a variable. Though it is a valid syntax in languages like C, PHP, etc but not Python.
b = (a+=1)
An equivalent version will be:
>>> a = 1
>>> a += 1
>>> b = a
As #Ashwini stated, a+=1 is an assigment, not a value. You can't assign it to b, or any variable. What you probably want is:
b = a+1
All the answers provided here are good, I just want to add that you can achieve what you want in a one-line expression, but written in a different manner:
b, a = a+1, a+1
Here you're doing almost the same thing: incrementing a by 1, and assigning the value of a+1 to b - I'm telling 'almost' because here we have two summations instead of one.
In order to make Python look more familiar, I've tried to assign an operator symbol to a variable's name,just for educational purposes: import operator equals = operator.eq
This seems to work fine for equals(a,b) but not for a equals b
Is there a way to express that a equals b instead of a == b
No, Python (and most mainstream languages) does not allow this kind of customization. In Python the restriction is quite intentional — an expression such as a equals b would look ungrammatical to any reader familiar with Python.
Not necessarily, but another SO answer shows how you can use this simple trick to "create" new operators. However, they only work if you surround the operator by | | or by << >>:
equals = Infix(lambda x, y: x == y):
print 2 |equals| 2 # True
The best you can do is
def equals(a,b):
return a == b
equals(1,5)
>> False
or
class my:
value = 0
def equals(self, b):
return self.value == b
a = my()
a.equals(3)
>>False
But you should use the built-in operator for readability. This way, a reader can distinguish, at once, an operator, a function, a symbol (a variable), a member function, etc...
Code
def change1(list1):
list1[1] = list1[1] + 5
def change2(number):
number = number + 2
def main():
numbers = [4, 8, 12]
change1(numbers)
variable = 15
change2(variable)
i = 0
while i < 3:
print numbers[i]
i += 1
print variable
main()
When I read it, I thought it will output 4 8 12 15 but it outputs 4 13 12 15. I can see here that Python deals with integer and lists differently, I assumed that the last thing is impossible without global. I cannot understand the output, in such case, why would it not output 4 13 12 17?
You can see here almost identical code with different types and different reference:
$ python test2.py
4
13
12
15
$ python test3.py
4
13
12
17
$ cat test2.py test3.py
Pass-by-reference examples
test2.py: pass-by-reference and mutable data type -example. Table/list is not enough to affect the local variable in main, you need the Reference!
def change1(list1):
list1[1] = list1[1] + 5
def change2(number):
number = [x+2 for x in number]
def main():
numbers = [4, 8, 12]
change1(numbers)
variable = [15]
change2(variable)
i = 0
while i < 3:
print numbers[i]
i += 1
print variable[0]
main()
test3.py: pass-by-reference example, changing a mutable data type list/table outside the main function
def change1(list1):
list1[1] = list1[1] + 5
def change2(number):
number[0] += 2
def main():
numbers = [4, 8, 12]
change1(numbers)
variable = [15]
change2(variable)
i = 0
while i < 3:
print numbers[i]
i += 1
print variable[0]
main()
pass-by-value examples
test4.py: trying to find an example with pass-by-value, why it does not work?
$ cat test4.py
# Not yet a pass-by-value example!
global variable
variable = [15]
def change1(list1):
list1[1] = list1[1] + 5
def change2(number):
number = [x+2 for x in number]
def main():
numbers = [4, 8, 12]
change1(numbers)
#variable = 15
change2(variable)
i = 0
while i < 3:
print numbers[i]
i += 1
print variable[0]
main()
$ python test4.py
4
13
12
15 # I expected 17! Why no 17?
def change1(list1):
# `list1[1] =` means you are changing the object passed in
list1[1] = list1[1] + 5
def change2(number):
# `number = ` means you create a **new local variable**, number,
# based on the `number`you passed in
number = [x+2 for x in number]
So if you want to change existing objects, you have to referene them in some way, for example in
def change3(number):
# `number[:]` is the whole existing list and you overwrite it
number[:] = [x+2 for x in number]
Note the [ .. ] when changing a list.
Python parameters are passed by reference. You mutating only one object in change1.
However, numerical values and Strings are all immutable. You cannot change the value of a passed in immutable and see that value change in the caller. Dictionaries and Lists on the other hand are mutable, and changes made to them by a called function will be preserved when the function returns.
More: http://www.penzilla.net/tutorials/python/functions/
The definitive answer is that Python is actually "call by sharing", also known as "call by object" or "call by object reference".
This has been extensively discussed before. From that article:
From time to time, people who’ve read a little CS but not a lot CS (or too much of just one kind of CS) pop up on comp.lang.python and waste a lot of energy trying to tell everyone that Python’s using some calling model that it doesn’t really use. It always turns out that they don’t really understand Python’s model, and quite often, they don’t understand their favourite model either.
But nevermind, the only thing you need to know is that Python’s model is neither “call by value” nor “call by reference” (because any attempt to use those terms for Python requires you to use non-standard definitions of the words “-value” and “-reference”). The most accurate description is CLU’s “call by object” or “call by sharing“. Or, if you prefer, “call by object reference“.
You should also read this, if you haven’t done so already.
Python's semantics are most similar to the semantics of the language CLU. The CLU Reference Manual by Liskov et al describes the semantics like this:
"We call the argument passing technique call by sharing,
because the argument objects are shared between the
caller and the called routine. This technique does not
correspond to most traditional argument passing techniques
(it is similar to argument passing in LISP). In particular it
is not call by value because mutations of arguments per-
formed by the called routine will be visible to the caller.
And it is not call by reference because access is not given
to the variables of the caller, but merely to certain objects."
In change1 you exchange the value in the list with value + 5.
In change2 you add 5 to number. The result is a new object and is not just applied to the passed variable.
If you come from C++: No there is no int& var in Python.
You get the expected result when doing this:
def change2(number):
return number + 5
variable = 15
variable = change2(variable)
If you still don't want to return a value, you could create a MutableInt class.
class MutableInt(object):
def __init__(self, value = 0):
self._value = int(value)
def __add__(self, other):
self._value += int(other)
return self
def __sub__(self, other):
self._value -= int(other)
return self
...
All the examples show call-by-value. Python only has call-by-value. There is no call-by-reference. All values in python are references (it is not possible to have an "object" as the value). Hence it is references that are copied when passed to the function. Lists are mutable, so it is possible to mutate its contents through a shared reference. In change2 you are reassigning a local variable to point to another object, which, like all assignments to local variables, has no effect on any calling scope, since it is call-by-value.