I want to write a function in Python that returns different fixed values based on the value of an input index.

In other languages I would use a switch or case statement, but Python does not appear to have a switch statement. What are the recommended Python solutions in this scenario?

You could use a dictionary:

def f(x):
    return {
        'a': 1,
        'b': 2,
    }[x]

If you’d like defaults you could use the dictionary get(key[, default]) method:

def f(x):
    return {
        'a': 1,
        'b': 2
    }.get(x, 9)    # 9 is default if x not found

I’ve always liked doing it this way

result = {
  'a': lambda x: x * 5,
  'b': lambda x: x + 7,
  'c': lambda x: x - 2
}[value](x)

From here

In addition to the dictionary methods (which I really like, BTW), you can also use if–elif–else to obtain the switch/case/default functionality:

if x == 'a':
    # Do the thing
elif x == 'b':
    # Do the other thing
if x in 'bc':
    # Fall-through by not using elif, but now the default case includes case 'a'!
elif x in 'xyz':
    # Do yet another thing
else:
    # Do the default

This of course is not identical to switch/case – you cannot have fall-through as easily as leaving off the break statement, but you can have a more complicated test. Its formatting is nicer than a series of nested ifs, even though functionally that’s what it is closer to.

My favorite Python recipe for switch/case is:

choices = {'a': 1, 'b': 2}
result = choices.get(key, 'default')

Short and simple for simple scenarios.

Compare to 11+ lines of C code:

// C Language version of a simple 'switch/case'.
switch( key ) 
{
    case 'a' :
        result = 1;
        break;
    case 'b' :
        result = 2;
        break;
    default :
        result = -1;
}

You can even assign multiple variables by using tuples:

choices = {'a': (1, 2, 3), 'b': (4, 5, 6)}
(result1, result2, result3) = choices.get(key, ('default1', 'default2', 'default3'))

class switch(object):
    value = None
    def __new__(class_, value):
        class_.value = value
        return True

def case(*args):
    return any((arg == switch.value for arg in args))

Usage:

while switch(n):
    if case(0):
        print "You typed zero."
        break
    if case(1, 4, 9):
        print "n is a perfect square."
        break
    if case(2):
        print "n is an even number."
    if case(2, 3, 5, 7):
        print "n is a prime number."
        break
    if case(6, 8):
        print "n is an even number."
        break
    print "Only single-digit numbers are allowed."
    break

Tests:

n = 2
#Result:
#n is an even number.
#n is a prime number.
n = 11
#Result:
#Only single-digit numbers are allowed.

My favorite one is a really nice recipe. You’ll really like it. It’s the closest one I’ve seen to actual switch case statements, especially in features.

class switch(object):
    def __init__(self, value):
        self.value = value
        self.fall = False

    def __iter__(self):
        """Return the match method once, then stop"""
        yield self.match
        raise StopIteration

    def match(self, *args):
        """Indicate whether or not to enter a case suite"""
        if self.fall or not args:
            return True
        elif self.value in args: # changed for v1.5, see below
            self.fall = True
            return True
        else:
            return False

Here’s an example:

# The following example is pretty much the exact use-case of a dictionary,
# but is included for its simplicity. Note that you can include statements
# in each suite.
v = 'ten'
for case in switch(v):
    if case('one'):
        print 1
        break
    if case('two'):
        print 2
        break
    if case('ten'):
        print 10
        break
    if case('eleven'):
        print 11
        break
    if case(): # default, could also just omit condition or 'if True'
        print "something else!"
        # No need to break here, it'll stop anyway

# break is used here to look as much like the real thing as possible, but
# elif is generally just as good and more concise.

# Empty suites are considered syntax errors, so intentional fall-throughs
# should contain 'pass'
c = 'z'
for case in switch(c):
    if case('a'): pass # only necessary if the rest of the suite is empty
    if case('b'): pass
    # ...
    if case('y'): pass
    if case('z'):
        print "c is lowercase!"
        break
    if case('A'): pass
    # ...
    if case('Z'):
        print "c is uppercase!"
        break
    if case(): # default
        print "I dunno what c was!"

# As suggested by Pierre Quentel, you can even expand upon the
# functionality of the classic 'case' statement by matching multiple
# cases in a single shot. This greatly benefits operations such as the
# uppercase/lowercase example above:
import string
c = 'A'
for case in switch(c):
    if case(*string.lowercase): # note the * for unpacking as arguments
        print "c is lowercase!"
        break
    if case(*string.uppercase):
        print "c is uppercase!"
        break
    if case('!', '?', '.'): # normal argument passing style also applies
        print "c is a sentence terminator!"
        break
    if case(): # default
        print "I dunno what c was!"

class Switch:
    def __init__(self, value):
        self.value = value

    def __enter__(self):
        return self

    def __exit__(self, type, value, traceback):
        return False # Allows a traceback to occur

    def __call__(self, *values):
        return self.value in values


from datetime import datetime

with Switch(datetime.today().weekday()) as case:
    if case(0):
        # Basic usage of switch
        print("I hate mondays so much.")
        # Note there is no break needed here
    elif case(1,2):
        # This switch also supports multiple conditions (in one line)
        print("When is the weekend going to be here?")
    elif case(3,4):
        print("The weekend is near.")
    else:
        # Default would occur here
        print("Let's go have fun!") # Didn't use case for example purposes

There’s a pattern that I learned from Twisted Python code.

class SMTP:
    def lookupMethod(self, command):
        return getattr(self, 'do_' + command.upper(), None)
    def do_HELO(self, rest):
        return 'Howdy ' + rest
    def do_QUIT(self, rest):
        return 'Bye'

SMTP().lookupMethod('HELO')('foo.bar.com') # => 'Howdy foo.bar.com'
SMTP().lookupMethod('QUIT')('') # => 'Bye'

You can use it any time you need to dispatch on a token and execute extended piece of code. In a state machine you would have state_ methods, and dispatch on self.state. This switch can be cleanly extended by inheriting from base class and defining your own do_ methods. Often times you won’t even have do_ methods in the base class.

Edit: how exactly is that used

In case of SMTP you will receive HELO from the wire. The relevant code (from twisted/mail/smtp.py, modified for our case) looks like this

class SMTP:
    # ...

    def do_UNKNOWN(self, rest):
        raise NotImplementedError, 'received unknown command'

    def state_COMMAND(self, line):
        line = line.strip()
        parts = line.split(None, 1)
        if parts:
            method = self.lookupMethod(parts[0]) or self.do_UNKNOWN
            if len(parts) == 2:
                return method(parts[1])
            else:
                return method('')
        else:
            raise SyntaxError, 'bad syntax'

SMTP().state_COMMAND('   HELO   foo.bar.com  ') # => Howdy foo.bar.com

You’ll receive ' HELO foo.bar.com ' (or you might get 'QUIT' or 'RCPT TO: foo'). This is tokenized into parts as ['HELO', 'foo.bar.com']. The actual method lookup name is taken from parts[0].

(The original method is also called state_COMMAND, because it uses the same pattern to implement a state machine, i.e. getattr(self, 'state_' + self.mode))

Let’s say you don’t want to just return a value, but want to use methods that change something on an object. Using the approach stated here would be:

result = {
  'a': obj.increment(x),
  'b': obj.decrement(x)
}.get(value, obj.default(x))

What happens here is that python evaluates all methods in the dictionary. So even if your value is ‘a’, the object will get incremented and decremented by x.

Solution:

func, args = {
  'a' : (obj.increment, (x,)),
  'b' : (obj.decrement, (x,)),
}.get(value, (obj.default, (x,)))

result = func(*args)

So you get a list containing a function and its arguments. This way, only the function pointer and the argument list get returned, not evaluated. ‘result’ then evaluates the returned function call.

I’m just going to drop my two cents in here. The reason there isn’t a case/switch statement in Python is because Python follows the principle of ‘Theres only one right way to do something’. So obviously you could come up with various ways of recreating switch/case functionality, but the Pythonic way of accomplishing this is the if/elif construct. ie

if something:
    return "first thing"
elif somethingelse:
    return "second thing"
elif yetanotherthing:
    return "third thing"
else:
    return "default thing"

I just felt PEP 8 deserved a nod here. One of the beautiful things about Python is its simplicity and elegance. That is largely derived from principles laid our in PEP 8, including “There’s only one right way to do something”

expanding on the “dict as switch” idea. if you want to use a default value for your switch:

def f(x):
    try:
        return {
            'a': 1,
            'b': 2,
        }[x]
    except KeyError:
        return 'default'

If you have a complicated case block you can consider using a function dictionary lookup table…

If you haven’t done this before its a good idea to step into your debugger and view exactly how the dictionary looks up each function.

NOTE: Do not use “()” inside the case/dictionary lookup or it will call each of your functions as the dictionary / case block is created. Remember this because you only want to call each function once using a hash style lookup.

def first_case():
    print "first"

def second_case():
    print "second"

def third_case():
    print "third"

mycase = {
'first': first_case, #do not use ()
'second': second_case, #do not use ()
'third': third_case #do not use ()
}
myfunc = mycase['first']
myfunc()

If you’re searching extra-statement, as “switch”, I built a python module that extends Python. It’s called ESPY as “Enhanced Structure for Python” and it’s available for both Python 2.x and Python 3.x.

For example, in this case, a switch statement could be performed by the following code:

macro switch(arg1):
    while True:
        cont=False
        val=%arg1%
        socket case(arg2):
            if val==%arg2% or cont:
                cont=True
                socket
        socket else:
            socket
        break

that can be used like this:

a=3
switch(a):
    case(0):
        print("Zero")
    case(1):
        print("Smaller than 2"):
        break
    else:
        print ("greater than 1")

so espy translate it in Python as:

a=3
while True:
    cont=False
    if a==0 or cont:
        cont=True
        print ("Zero")
    if a==1 or cont:
        cont=True
        print ("Smaller than 2")
        break
    print ("greater than 1")
    break

I found that a common switch structure:

switch ...parameter...
case p1: v1; break;
case p2: v2; break;
default: v3;

can be expressed in Python as follows:

(lambda x: v1 if p1(x) else v2 if p2(x) else v3)

or formatted in a clearer way:

(lambda x:
     v1 if p1(x) else
     v2 if p2(x) else
     v3)

Instead of being a statement, the python version is an expression, which evaluates to a value.

Most of the answers here are pretty old, and especially the accepted ones, so it seems worth updating.

First, the official Python FAQ covers this, and recommends the elif chain for simple cases and the dict for larger or more complex cases. It also suggests a set of visit_ methods (a style used by many server frameworks) for some cases:

def dispatch(self, value):
    method_name = 'visit_' + str(value)
    method = getattr(self, method_name)
    method()

The FAQ also mentions PEP 275, which was written to get an official once-and-for-all decision on adding C-style switch statements. But that PEP was actually deferred to Python 3, and it was only officially rejected as a separate proposal, PEP 3103. The answer was, of course, no—but the two PEPs have links to additional information if you’re interested in the reasons or the history.

One thing that came up multiple times (and can be seen in PEP 275, even though it was cut out as an actual recommendation) is that if you’re really bothered by having 8 lines of code to handle 4 cases, vs. the 6 lines you’d have in C or Bash, you can always write this:

if x == 1: print('first')
elif x == 2: print('second')
elif x == 3: print('third')
else: print('did not place')

This isn’t exactly encouraged by PEP 8, but it’s readable and not too unidiomatic.

Over the more than a decade since PEP 3103 was rejected, the issue of C-style case statements, or even the slightly more powerful version in Go, has been considered dead; whenever anyone brings it up on python-ideas or -dev, they’re referred to the old decision.

However, the idea of full ML-style pattern matching arises every few years, especially since languages like Swift and Rust have adopted it. The problem is that it’s hard to get much use out of pattern matching without algebraic data types. While Guido has been sympathetic to the idea, nobody’s come up with a proposal that fits into Python very well. (You can read my 2014 strawman for an example.) This could change with dataclass in 3.7 and some sporadic proposals for a more powerful enum to handle sum types, or with various proposals for different kinds of statement-local bindings (like PEP 3150, or the set of proposals currently being discussed on -ideas). But so far, it hasn’t.

There are also occasionally proposals for Perl 6-style matching, which is basically a mishmash of everything from elif to regex to single-dispatch type-switching.

Solution to run functions:

result = {
    'case1':     foo1, 
    'case2':     foo2,
    'case3':     foo3,
    'default':   default,
}.get(option)()

where foo1(), foo2(), foo3() and default() are functions

I didn’t find the simple answer I was looking for anywhere on Google search. But I figured it out anyway. It’s really quite simple. Decided to post it, and maybe prevent a few less scratches on someone else’s head. The key is simply “in” and tuples. Here is the switch statement behavior with fall-through, including RANDOM fall-through.

l = ['Dog', 'Cat', 'Bird', 'Bigfoot',
     'Dragonfly', 'Snake', 'Bat', 'Loch Ness Monster']

for x in l:
    if x in ('Dog', 'Cat'):
        x += " has four legs"
    elif x in ('Bat', 'Bird', 'Dragonfly'):
        x += " has wings."
    elif x in ('Snake',):
        x += " has a forked tongue."
    else:
        x += " is a big mystery by default."
    print(x)

print()

for x in range(10):
    if x in (0, 1):
        x = "Values 0 and 1 caught here."
    elif x in (2,):
        x = "Value 2 caught here."
    elif x in (3, 7, 8):
        x = "Values 3, 7, 8 caught here."
    elif x in (4, 6):
        x = "Values 4 and 6 caught here"
    else:
        x = "Values 5 and 9 caught in default."
    print(x)

Provides:

Dog has four legs
Cat has four legs
Bird has wings.
Bigfoot is a big mystery by default.
Dragonfly has wings.
Snake has a forked tongue.
Bat has wings.
Loch Ness Monster is a big mystery by default.

Values 0 and 1 caught here.
Values 0 and 1 caught here.
Value 2 caught here.
Values 3, 7, 8 caught here.
Values 4 and 6 caught here
Values 5 and 9 caught in default.
Values 4 and 6 caught here
Values 3, 7, 8 caught here.
Values 3, 7, 8 caught here.
Values 5 and 9 caught in default.

The solutions I use:

A combination of 2 of the solutions posted here, which is relatively easy to read and supports defaults.

result = {
  'a': lambda x: x * 5,
  'b': lambda x: x + 7,
  'c': lambda x: x - 2
}.get(whatToUse, lambda x: x - 22)(value)

where

.get('c', lambda x: x - 22)(23)

looks up "lambda x: x - 2" in the dict and uses it with x=23

.get('xxx', lambda x: x - 22)(44)

doesn’t find it in the dict and uses the default "lambda x: x - 22" with x=44.

# simple case alternative

some_value = 5.0

# this while loop block simulates a case block

# case
while True:

    # case 1
    if some_value > 5:
        print ('Greater than five')
        break

    # case 2
    if some_value == 5:
        print ('Equal to five')
        break

    # else case 3
    print ( 'Must be less than 5')
    break

def f(x):
    dictionary = {'a':1, 'b':2, 'c':3}
    return dictionary.get(x,'Not Found') 
##Returns the value for the letter x;returns 'Not Found' if x isn't a key in the dictionary

I liked Mark Bies’s answer

Since the x variable must used twice, I modified the lambda functions to parameterless.

I have to run with results[value](value)

In [2]: result = {
    ...:   'a': lambda x: 'A',
    ...:   'b': lambda x: 'B',
    ...:   'c': lambda x: 'C'
    ...: }
    ...: result['a']('a')
    ...: 
Out[2]: 'A'

In [3]: result = {
    ...:   'a': lambda : 'A',
    ...:   'b': lambda : 'B',
    ...:   'c': lambda : 'C',
    ...:   None: lambda : 'Nothing else matters'

    ...: }
    ...: result['a']()
    ...: 
Out[3]: 'A'

Edit: I noticed that I can use None type with with dictionaries. So this would emulate switch ; case else

def f(x):
     return 1 if x == 'a' else\
            2 if x in 'bcd' else\
            0 #default

Short and easy to read, has a default value and supports expressions in both conditions and return values.

However, it is less efficient than the solution with a dictionary. For example, Python has to scan through all the conditions before returning the default value.

you can use a dispatched dict:

#!/usr/bin/env python


def case1():
    print("This is case 1")

def case2():
    print("This is case 2")

def case3():
    print("This is case 3")


token_dict = {
    "case1" : case1,
    "case2" : case2,
    "case3" : case3,
}


def main():
    cases = ("case1", "case3", "case2", "case1")
    for case in cases:
        token_dict[case]()


if __name__ == '__main__':
    main()

Output:

This is case 1
This is case 3
This is case 2
This is case 1

Simple, not tested; each condition is evaluated independently: there is no fall-through, but all cases are evaluated (although the expression to switch on is only evaluated once), unless there is a break statement. For example,

for case in [expression]:
    if case == 1:
        print(end='Was 1. ')

    if case == 2:
        print(end='Was 2. ')
        break

    if case in (1, 2):
        print(end='Was 1 or 2. ')

    print(end='Was something. ')

prints Was 1. Was 1 or 2. Was something. ^{(Dammit! Why can’t I have trailing whitespace in inline code blocks?)} if expression evaluates to 1, Was 2. if expression evaluates to 2, or Was something. if expression evaluates to something else.

Defining:

def switch1(value, options):
  if value in options:
    options[value]()

allows you to use a fairly straightforward syntax, with the cases bundled into a map:

def sample1(x):
  local = 'betty'
  switch1(x, {
    'a': lambda: print("hello"),
    'b': lambda: (
      print("goodbye," + local),
      print("!")),
    })

I kept trying to redefine switch in a way that would let me get rid of the “lambda:”, but gave up. Tweaking the definition:

def switch(value, *maps):
  options = {}
  for m in maps:
    options.update(m)
  if value in options:
    options[value]()
  elif None in options:
    options[None]()

Allowed me to map multiple cases to the same code, and to supply a default option:

def sample(x):
  switch(x, {
    _: lambda: print("other") 
    for _ in 'cdef'
    }, {
    'a': lambda: print("hello"),
    'b': lambda: (
      print("goodbye,"),
      print("!")),
    None: lambda: print("I dunno")
    })

Each replicated case has to be in its own dictionary; switch() consolidates the dictionaries before looking up the value. It’s still uglier than I’d like, but it has the basic efficiency of using a hashed lookup on the expression, rather than a loop through all the keys.

I think the best way is to use the python language idioms to keep your code testable. As showed in previous answers, I use dictionaries to take advantage of python structures and language and keep the “case” code isolated in different methods. Below there is a class, but you can use directly a module, globals and functions. The class has methods that can be tested with isolation. Dependending to your needs, you can play with static methods and attributes too.

class ChoiceManager:

    def __init__(self):
        self.__choice_table = \
        {
            "CHOICE1" : self.my_func1,
            "CHOICE2" : self.my_func2,
        }

    def my_func1(self, data):
        pass

    def my_func2(self, data):
        pass

    def process(self, case, data):
        return self.__choice_table[case](data)

ChoiceManager().process("CHOICE1", my_data)

It is possible to take advantage of this method using also classes as keys of “__choice_table”. In this way you can avoid isinstance abuse and keep all clean and testable.

Supposing you have to process a lot of messages or packets from the net or your MQ. Every packet has its own structure and its management code (in a generic way). With the above code it is possible to do something like this:

class PacketManager:

    def __init__(self):
        self.__choice_table = \
        {
            ControlMessage : self.my_func1,
            DiagnosticMessage : self.my_func2,
        }

    def my_func1(self, data):
        # process the control message here
        pass

    def my_func2(self, data):
        # process the diagnostic message here
        pass

    def process(self, pkt):
        return self.__choice_table[pkt.__class__](pkt)

pkt = GetMyPacketFromNet()
PacketManager().process(pkt)


# isolated test or isolated usage example
def test_control_packet():
    p = ControlMessage()
    PacketManager().my_func1(p)

So complexity is not spread in the code flow but it is rendered in code structure.

Expanding on Greg Hewgill’s answer – We can encapsulate the dictionary-solution using a decorator:

def case(callable):
    """switch-case decorator"""
    class case_class(object):
        def __init__(self, *args, **kwargs):
            self.args = args
            self.kwargs = kwargs

        def do_call(self):
            return callable(*self.args, **self.kwargs)

return case_class

def switch(key, cases, default=None):
    """switch-statement"""
    ret = None
    try:
        ret = case[key].do_call()
    except KeyError:
        if default:
            ret = default.do_call()
    finally:
        return ret

This can then be used with the @case-decorator

@case
def case_1(arg1):
    print 'case_1: ', arg1

@case
def case_2(arg1, arg2):
    print 'case_2'
    return arg1, arg2

@case
def default_case(arg1, arg2, arg3):
    print 'default_case: ', arg1, arg2, arg3

ret = switch(somearg, {
    1: case_1('somestring'),
    2: case_2(13, 42)
}, default_case(123, 'astring', 3.14))

print ret

The good news are that this has already been done in NeoPySwitch-module. Simply install using pip:

pip install NeoPySwitch

A solution I tend to use which also makes use of dictionaries is :

def decision_time( key, *args, **kwargs):
    def action1()
        """This function is a closure - and has access to all the arguments"""
        pass
    def action2()
        """This function is a closure - and has access to all the arguments"""
        pass
    def action3()
        """This function is a closure - and has access to all the arguments"""
        pass

   return {1:action1, 2:action2, 3:action3}.get(key,default)()

This has the advantage that it doesn’t try to evaluate the functions every time, and you just have to ensure that the outer function gets all the information that the inner functions need.

There have been a lot of answers so far that have said, “we don’t have a switch in Python, do it this way”. However, I would like to point out that the switch statement itself is an easily-abused construct that can and should be avoided in most cases because they promote lazy programming. Case in point:

def ToUpper(lcChar):
    if (lcChar == 'a' or lcChar == 'A'):
        return 'A'
    elif (lcChar == 'b' or lcChar == 'B'):
        return 'B'
    ...
    elif (lcChar == 'z' or lcChar == 'Z'):
        return 'Z'
    else:
        return None        # or something

Now, you could do this with a switch-statement (if Python offered one) but you’d be wasting your time because there are methods that do this just fine. Or maybe, you have something less obvious:

def ConvertToReason(code):
    if (code == 200):
        return 'Okay'
    elif (code == 400):
        return 'Bad Request'
    elif (code == 404):
        return 'Not Found'
    else:
        return None

However, this sort of operation can and should be handled with a dictionary because it will be faster, less complex, less prone to error and more compact.

And the vast majority of “use cases” for switch statements will fall into one of these two cases; there’s just very little reason to use one if you’ve thought about your problem thoroughly.

So, rather than asking “how do I switch in Python?”, perhaps we should ask, “why do I want to switch in Python?” because that’s often the more interesting question and will often expose flaws in the design of whatever you’re building.

Now, that isn’t to say that switches should never be used either. State machines, lexers, parsers and automata all use them to some degree and, in general, when you start from a symmetrical input and go to an asymmetrical output they can be useful; you just need to make sure that you don’t use the switch as a hammer because you see a bunch of nails in your code.