Related
From Google Python Class
D. Verbing :
Given a string, if its length is at least 3, add 'ing' to its end.
Unless it already ends in 'ing', in which case add 'ly' instead.
If the string length is less than 3, leave it unchanged.
Return the resulting string.
def verbing(s):
if len(s) < 3:
return s
if len(s) >= 3 and s[-3:] == 'ing':
s = s + 'ly'
return s
elif s[:-3] != 'ing':
s = s + 'ing'
return s
Test Cases
print 'verbing'
test(verbing('hail'), 'hailing')
test(verbing('runt'), 'runting')
test(verbing('swiming'), 'swimingly')
test(verbing('do'), 'do')
test(verbing('hi'), 'hi')
You can use str.endswith:
test_cases = ["ing", "webbing", "xy", "house"]
def verbing(s):
return s if len(s) < 3 else (s + "ly" if s.endswith("ing") else s + "ing")
for t in test_cases:
print(t, verbing(t))
Prints:
ing ingly
webbing webbingly
xy xy
house houseing
Your control flow statements (if/elif/else) all end with return s, so you could restructure things to eliminate the redundant return s statements:
def verbing(s):
if len(s) >= 3:
if s[-3:] == 'ing':
s = s + 'ly'
elif s[:-3] != 'ing':
s = s + 'ing'
return s
This also eliminates the if len(s) < 3 line, since if len(s) isn't greater than or equal to 3, that must mean it is less than 3, so there isn't much of a point in checking for that explicitly.
Similarly, since the if s[-3:] == 'ing' line asks "does this end in -ing? yes or no?", if the answer is not "yes", it must be "no" (or in this case, False). So the elif statement can be replaced with a simpler and more efficient else (more efficient since it's not checking & evaluating another condition). You can also shorten s = s + something statements to s += something, which is a bit shorter and nicer to read:
def verbing(s):
if len(s) >= 3:
if s[-3:] == 'ing':
s += 'ly'
else:
s += 'ing'
return s
Finally, there's a shorter way to write simple if/else statements which in other languages is known as the ternary operator, which applied here would look something like this:
def verbing(s):
if len(s) >= 3:
# the parentheses are not needed but do
# help make it more clear what's going on
s += ('ly' if s[-3:] == 'ing' else 'ing')
return s
This ('ly' if s[-3:] == 'ing' else 'ing') statement gets evaluated in the same way as the previous if/else statement, just written in a different way. It can be read as "this statement should be equal to 'ly' if the string ends in 'ing'; otherwise, this statement should be equal to 'ing'." The value of that statement is what will get tacked onto the end of the string s.
Ultimately, I think the code you began with is a good place to start, since it does in fact work. And you're right to want to review that code to see if there are places where it could be cleaner, shorter, and/or more efficient. This is roughly how I personally go about these sorts of things and I hope this may help you in the process of improving and refactoring the code you write in future. Good luck and have fun!
Here's what I could come up with on a short notice:
def verbing(string: str) -> str:
if len(string) >= 3:
if not string.endswith("ing"):
string += "ing"
else:
string += "ly"
return string
Hope that helps.
There are many different ways to solve this problem. I think that first you need to ask yourself why your solution isn't good enough. Maybe if you will run import this you will understand better how code in python should look like and what are the values that you should follow.
Although this pattern is way to much for this small problem, for education purpose I will intrude another pattern that can be handy if the problem should be address from the scale point of view.
def cond_ing(st):
return st[-3:] != "ing"
def add_ing(st):
return st + "ing"
def cond_ly(st):
return st[-3:] == "ing"
def add_ly(st):
return st + "ly"
d = {
cond_ing: add_ing,
cond_ly: add_ly
}
now you can run a simple for loop and every one can just add which condition that they would like. something like:
for s in tests:
if len(s) <= 3:
print(s)
continue
for con in d:
if con(s):
print(d[con](s))
This question's answers are a community effort. Edit existing answers to improve this post. It is not currently accepting new answers or interactions.
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?
Python 3.10 (2021) introduced the match-case statement which provides a first-class implementation of a "switch" for Python. For example:
def f(x):
match x:
case 'a':
return 1
case 'b':
return 2
case _:
return 0 # 0 is the default case if x is not found
The match-case statement is considerably more powerful than this simple example.
The original answer below was written in 2008, before match-case was available:
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]) function:
def f(x):
return {
'a': 1,
'b': 2
}.get(x, 9) # 9 will be returned default if x is 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.
Python >= 3.10
Wow, Python 3.10+ now has a match/case syntax which is like switch/case and more!
PEP 634 -- Structural Pattern Matching
Selected features of match/case
1 - Match values:
Matching values is similar to a simple switch/case in another language:
match something:
case 1 | 2 | 3:
# Match 1-3.
case _:
# Anything else.
#
# Match will throw an error if this is omitted
# and it doesn't match any of the other patterns.
2 - Match structural patterns:
match something:
case str() | bytes():
# Match a string like object.
case [str(), int()]:
# Match a `str` and an `int` sequence
# (`list` or a `tuple` but not a `set` or an iterator).
case [_, _]:
# Match a sequence of 2 variables.
# To prevent a common mistake, sequence patterns don’t match strings.
case {"bandwidth": 100, "latency": 300}:
# Match this dict. Extra keys are ignored.
3 - Capture variables
Parse an object; saving it as variables:
match something:
case [name, count]
# Match a sequence of any two objects and parse them into the two variables.
case [x, y, *rest]:
# Match a sequence of two or more objects,
# binding object #3 and on into the rest variable.
case bytes() | str() as text:
# Match any string like object and save it to the text variable.
Capture variables can be useful when parsing data (such as JSON or HTML) that may come in one of a number of different patterns.
Capture variables is a feature. But it also means that you need to use dotted constants (ex: COLOR.RED) only. Otherwise, the constant will be treated as a capture variable and overwritten.
More sample usage:
match something:
case 0 | 1 | 2:
# Matches 0, 1 or 2 (value).
print("Small number")
case [] | [_]:
# Matches an empty or single value sequence (structure).
# Matches lists and tuples but not sets.
print("A short sequence")
case str() | bytes():
# Something of `str` or `bytes` type (data type).
print("Something string-like")
case _:
# Anything not matched by the above.
print("Something else")
Python <= 3.9
My favorite Python recipe for switch/case was:
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. 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!"
Some of the comments indicated that a context manager solution using with foo as case rather than for case in foo might be cleaner, and for large switch statements the linear rather than quadratic behavior might be a nice touch. Part of the value in this answer with a for loop is the ability to have breaks and fallthrough, and if we're willing to play with our choice of keywords a little bit we can get that in a context manager too:
class Switch:
def __init__(self, value):
self.value = value
self._entered = False
self._broken = False
self._prev = None
def __enter__(self):
return self
def __exit__(self, type, value, traceback):
return False # Allows a traceback to occur
def __call__(self, *values):
if self._broken:
return False
if not self._entered:
if values and self.value not in values:
return False
self._entered, self._prev = True, values
return True
if self._prev is None:
self._prev = values
return True
if self._prev != values:
self._broken = True
return False
if self._prev == values:
self._prev = None
return False
#property
def default(self):
return self()
Here's an example:
# Prints 'bar' then 'baz'.
with Switch(2) as case:
while case(0):
print('foo')
while case(1, 2, 3):
print('bar')
while case(4, 5):
print('baz')
break
while case.default:
print('default')
break
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))
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 "there's 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. I.e.,
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 out in PEP 8, including "There's only one right way to do something."
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))
Here 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.
Solution to run functions:
result = {
'case1': foo1,
'case2': foo2,
'case3': foo3,
}.get(option)(parameters_optional)
where foo1(), foo2() and foo3() are functions
Example 1 (with parameters):
option = number['type']
result = {
'number': value_of_int, # result = value_of_int(number['value'])
'text': value_of_text, # result = value_of_text(number['value'])
'binary': value_of_bin, # result = value_of_bin(number['value'])
}.get(option)(value['value'])
Example 2 (no parameters):
option = number['type']
result = {
'number': func_for_number, # result = func_for_number()
'text': func_for_text, # result = func_for_text()
'binary': func_for_bin, # result = func_for_bin()
}.get(option)()
Example 4 (only values):
option = number['type']
result = {
'number': lambda: 10, # result = 10
'text': lambda: 'ten', # result = 'ten'
'binary': lambda: 0b101111, # result = 47
}.get(option)()
If you have a complicated case block you can consider using a function dictionary lookup table...
If you haven't done this before it's 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
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.
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'
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.
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.
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
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.
# 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
I was quite confused after reading the accepted answer, but this cleared it all up:
def numbers_to_strings(argument):
switcher = {
0: "zero",
1: "one",
2: "two",
}
return switcher.get(argument, "nothing")
This code is analogous to:
function(argument){
switch(argument) {
case 0:
return "zero";
case 1:
return "one";
case 2:
return "two";
default:
return "nothing";
}
}
Check the Source for more about dictionary mapping to functions.
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.
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.
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.
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.
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.
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
This question's answers are a community effort. Edit existing answers to improve this post. It is not currently accepting new answers or interactions.
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?
Python 3.10 (2021) introduced the match-case statement which provides a first-class implementation of a "switch" for Python. For example:
def f(x):
match x:
case 'a':
return 1
case 'b':
return 2
case _:
return 0 # 0 is the default case if x is not found
The match-case statement is considerably more powerful than this simple example.
The original answer below was written in 2008, before match-case was available:
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]) function:
def f(x):
return {
'a': 1,
'b': 2
}.get(x, 9) # 9 will be returned default if x is 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.
Python >= 3.10
Wow, Python 3.10+ now has a match/case syntax which is like switch/case and more!
PEP 634 -- Structural Pattern Matching
Selected features of match/case
1 - Match values:
Matching values is similar to a simple switch/case in another language:
match something:
case 1 | 2 | 3:
# Match 1-3.
case _:
# Anything else.
#
# Match will throw an error if this is omitted
# and it doesn't match any of the other patterns.
2 - Match structural patterns:
match something:
case str() | bytes():
# Match a string like object.
case [str(), int()]:
# Match a `str` and an `int` sequence
# (`list` or a `tuple` but not a `set` or an iterator).
case [_, _]:
# Match a sequence of 2 variables.
# To prevent a common mistake, sequence patterns don’t match strings.
case {"bandwidth": 100, "latency": 300}:
# Match this dict. Extra keys are ignored.
3 - Capture variables
Parse an object; saving it as variables:
match something:
case [name, count]
# Match a sequence of any two objects and parse them into the two variables.
case [x, y, *rest]:
# Match a sequence of two or more objects,
# binding object #3 and on into the rest variable.
case bytes() | str() as text:
# Match any string like object and save it to the text variable.
Capture variables can be useful when parsing data (such as JSON or HTML) that may come in one of a number of different patterns.
Capture variables is a feature. But it also means that you need to use dotted constants (ex: COLOR.RED) only. Otherwise, the constant will be treated as a capture variable and overwritten.
More sample usage:
match something:
case 0 | 1 | 2:
# Matches 0, 1 or 2 (value).
print("Small number")
case [] | [_]:
# Matches an empty or single value sequence (structure).
# Matches lists and tuples but not sets.
print("A short sequence")
case str() | bytes():
# Something of `str` or `bytes` type (data type).
print("Something string-like")
case _:
# Anything not matched by the above.
print("Something else")
Python <= 3.9
My favorite Python recipe for switch/case was:
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. 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!"
Some of the comments indicated that a context manager solution using with foo as case rather than for case in foo might be cleaner, and for large switch statements the linear rather than quadratic behavior might be a nice touch. Part of the value in this answer with a for loop is the ability to have breaks and fallthrough, and if we're willing to play with our choice of keywords a little bit we can get that in a context manager too:
class Switch:
def __init__(self, value):
self.value = value
self._entered = False
self._broken = False
self._prev = None
def __enter__(self):
return self
def __exit__(self, type, value, traceback):
return False # Allows a traceback to occur
def __call__(self, *values):
if self._broken:
return False
if not self._entered:
if values and self.value not in values:
return False
self._entered, self._prev = True, values
return True
if self._prev is None:
self._prev = values
return True
if self._prev != values:
self._broken = True
return False
if self._prev == values:
self._prev = None
return False
#property
def default(self):
return self()
Here's an example:
# Prints 'bar' then 'baz'.
with Switch(2) as case:
while case(0):
print('foo')
while case(1, 2, 3):
print('bar')
while case(4, 5):
print('baz')
break
while case.default:
print('default')
break
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))
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 "there's 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. I.e.,
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 out in PEP 8, including "There's only one right way to do something."
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))
Here 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.
Solution to run functions:
result = {
'case1': foo1,
'case2': foo2,
'case3': foo3,
}.get(option)(parameters_optional)
where foo1(), foo2() and foo3() are functions
Example 1 (with parameters):
option = number['type']
result = {
'number': value_of_int, # result = value_of_int(number['value'])
'text': value_of_text, # result = value_of_text(number['value'])
'binary': value_of_bin, # result = value_of_bin(number['value'])
}.get(option)(value['value'])
Example 2 (no parameters):
option = number['type']
result = {
'number': func_for_number, # result = func_for_number()
'text': func_for_text, # result = func_for_text()
'binary': func_for_bin, # result = func_for_bin()
}.get(option)()
Example 4 (only values):
option = number['type']
result = {
'number': lambda: 10, # result = 10
'text': lambda: 'ten', # result = 'ten'
'binary': lambda: 0b101111, # result = 47
}.get(option)()
If you have a complicated case block you can consider using a function dictionary lookup table...
If you haven't done this before it's 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
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.
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'
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.
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.
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
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.
# 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
I was quite confused after reading the accepted answer, but this cleared it all up:
def numbers_to_strings(argument):
switcher = {
0: "zero",
1: "one",
2: "two",
}
return switcher.get(argument, "nothing")
This code is analogous to:
function(argument){
switch(argument) {
case 0:
return "zero";
case 1:
return "one";
case 2:
return "two";
default:
return "nothing";
}
}
Check the Source for more about dictionary mapping to functions.
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.
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.
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.
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.
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.
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
If I have a function with multiple conditional statements where every branch gets executed returns from the function. Should I use multiple if statements, or if/elif/else? For example, say I have a function:
def example(x):
if x > 0:
return 'positive'
if x < 0:
return 'negative'
return 'zero'
Is it better to write:
def example(x):
if x > 0:
return 'positive'
elif x < 0:
return 'negative'
else:
return 'zero'
Both have the same outcome, but is one more efficient or considered more idiomatic than the other?
Edit:
A couple of people have said that in the first example both if statements are always evaluated, which doesn't seem to be the case to me
for example if I run the code:
l = [1,2,3]
def test(a):
if a > 0:
return a
if a > 2:
l.append(4)
test(5)
l will still equal [1,2,3]
I'll expand out my comment to an answer.
In the case that all cases return, these are indeed equivalent. What becomes important in choosing between them is then what is more readable.
Your latter example uses the elif structure to explicitly state that the cases are mutually exclusive, rather than relying on the fact they are implicitly from the returns. This makes that information more obvious, and therefore the code easier to read, and less prone to errors.
Say, for example, someone decides there is another case:
def example(x):
if x > 0:
return 'positive'
if x == -15:
print("special case!")
if x < 0:
return 'negative'
return 'zero'
Suddenly, there is a potential bug if the user intended that case to be mutually exclusive (obviously, this doesn't make much sense given the example, but potentially could in a more realistic case). This ambiguity is removed if elifs are used and the behaviour is made visible to the person adding code at the level they are likely to be looking at when they add it.
If I were to come across your first code example, I would probably assume that the choice to use ifs rather than elifs implied the cases were not mutually exclusive, and so things like changing the value of x might be used to change which ifs execute (obviously in this case the intention is obvious and mutually exclusive, but again, we are talking about less obvious cases - and consistency is good, so even in a simple example when it is obvious, it's best to stick to one way).
Check this out to understand the difference:
>>> a = 2
>>> if a > 1: a = a+1
...
>>> if a > 2: a = a+1
...
>>> a
4
versus
>>> a = 2
>>> if a > 1: a = a+1
... elif a > 2: a = a+1
...
>>> a
3
The first case is equivalent to two distinct if's with empty else statements (or imagine else: pass); in the second case elif is part of the first if statement.
In some cases, elif is required for correct semantics. This is the case when the conditions are not mutually exclusive:
if x == 0: result = 0
elif y == 0: result = None
else: result = x / y
In some cases it is efficient because the interpreter doesn't need to check all conditions, which is the case in your example. If x is negative then why do you check the positive case? An elif in this case also makes code more readable as it clearly shows only a single branch will be executed.
In general (e.g. your example), you would always use an if..elif ladder to explicitly show the conditions are mutually-exclusive. It prevents ambiguity, bugs etc.
The only reason I can think of that you might ever not use elif and use if instead would be if the actions from the body of the preceding if statement (or previous elif statements) might have changed the condition so as to potentially make it no longer mutually exclusive. So it's no longer really a ladder, just separate concatenated if(..elif..else) blocks. (Leave an empty line between the separate blocks, for good style, and to prevent someone accidentally thinking it should have been elif and 'fixing' it)
Here's a contrived example, just to prove the point:
if total_cost>=10:
if give_shopper_a_random_discount():
print 'You have won a discount'
total_cost -= discount
candidate_prime = True
if total_cost<10:
print 'Spend more than $10 to enter our draw for a random discount'
You can see it's possible to hit both conditions, if the first if-block applies the discount, so then we also execute the second, which prints a message which would be confusing since our original total had been >=10.
An elif here would prevent that scenario.
But there could be other scenarios where we want the second block to run, even for that scenario.
if total_cost<10:
<some other action we should always take regardless of original undiscounted total_cost>
In regards to the edit portion of your question when you said:
"A couple of people have said that in the first example both if statements are always evaluated, which doesn't seem to be the case to me"
And then you provided this example:
l = [1,2,3]
def test(a):
if a > 0:
return a
if a > 2:
l.append(4)
test(5)
Yes indeed the list l will still equal [1,2,3] in this case, ONLY because you're RETURNING the result of running the block, because the return statement leads to exiting the function, which would result in the same thing if you used elif with the return statement.
Now try to use the print statement instead of the return one, you'll see that the 2nd if statement will execute just fine, and that 4 will indeed be appended to the list l using append.
Well.. now what if the first ifstatement changes the value of whatever is being evaluated in the 2nd if statement?
And yes that's another situation. For instance, say you have a variable x and you used if statement to evaluate a block of code that actually changed the x value.
Now, if you use another if statement that evaluates the same variable x will be wrong since you're considering x value to be the same as its initial one, while in fact it was changed after the first if was executed. Therefore your code will be wrong.
It happens pretty often, and sometimes you even want it explicitly to be changed. If that's how you want your code to behave, then yes you should use multiple if's which does the job well. Otherwise stick to elif.
In my example, the 1st if block is executed and changed the value of x, which lead to have the 2nd if evaluates a different x (since its value was changed).
That's where elif comes in handy to prevent such thing from happening, which is the primary benefit of using it.
The other secondary good benefit of using elif instead of multiple if's is to avoid confusion and better code readability.
Consider this For someone looking for a easy way:
>>> a = ['fb.com', 'tw.com', 'cat.com']
>>> for i in a:
... if 'fb' in i:
... pass
... if 'tw' in i:
... pass
... else:
... print(i)
output:
fb.com
cat.com
And
>>> a = ['fb.com', 'tw.com', 'cat.com']
>>> for i in a:
... if 'fb' in i:
... pass
... elif 'tw' in i:
... pass
... else:
... print(i)
Output:
cat.com
'If' checks for the first condition then searches for the elif or else, whereas using elif, after if, it goes on checking for all the elif condition and lastly going to else.
elif is a bit more efficient, and it's quite logical: with ifs the program has to evaluate each logical expression every time. In elifs though, it's not always so. However, in your example, this improvement would be very, very small, probably unnoticeable, as evaluating x > 0 is one of the cheapest operations.
When working with elifs it's also a good idea to think about the best order. Consider this example:
if (x-3)**3+(x+1)**2-6*x+4 > 0:
#do something 1
elif x < 0:
#do something 2
Here the program will have to evaluate the ugly expression every time! However, if we change the order:
if x < 0:
#do something 2
elif (x-3)**3+(x+1)**2-6*x+4 > 0:
#do something 1
Now the program will first check if x < 0 (cheap and simple) and only if it isn't, will it evaluate the more complicated expression (btw, this code doesn't make much sense, it's just a random example)
Also, what perreal said.
Is there a goto or any equivalent in Python to be able to jump to a specific line of code?
No, Python does not support labels and goto. It's a (highly) structured programming language.
Python offers you the ability to do some of the things you could do with a goto using first class functions. For example:
void somefunc(int a)
{
if (a == 1)
goto label1;
if (a == 2)
goto label2;
label1:
...
label2:
...
}
Could be done in Python like this:
def func1():
...
def func2():
...
funcmap = {1 : func1, 2 : func2}
def somefunc(a):
funcmap[a]() #Ugly! But it works.
Granted, that isn't the best way to substitute for goto. But without knowing exactly what you're trying to do with the goto, it's hard to give specific advice.
#ascobol:
Your best bet is to either enclose it in a function or use an exception. For the function:
def loopfunc():
while 1:
while 1:
if condition:
return
For the exception:
try:
while 1:
while 1:
raise BreakoutException #Not a real exception, invent your own
except BreakoutException:
pass
Using exceptions to do stuff like this may feel a bit awkward if you come from another programming language. But I would argue that if you dislike using exceptions, Python isn't the language for you. :-)
I recently wrote a function decorator that enables goto in Python, just like that:
from goto import with_goto
#with_goto
def range(start, stop):
i = start
result = []
label .begin
if i == stop:
goto .end
result.append(i)
i += 1
goto .begin
label .end
return result
I'm not sure why one would like to do something like that though. That said, I'm not too serious about it. But I'd like to point out that this kind of meta programming is actual possible in Python, at least in CPython and PyPy, and not only by misusing the debugger API as that other guy did. You have to mess with the bytecode though.
I found this in the official python Design and History FAQ.
Why is there no goto?
You can use exceptions to provide a “structured goto” that even works
across function calls. Many feel that exceptions can conveniently
emulate all reasonable uses of the “go” or “goto” constructs of C,
Fortran, and other languages. For example:
class label(Exception): pass # declare a label
try:
...
if condition: raise label() # goto label
...
except label: # where to goto
pass
...
This doesn’t allow you to jump into the middle of a loop, but that’s
usually considered an abuse of goto anyway. Use sparingly.
It's very nice that this is even mentioned in the official FAQ, and that a nice solution sample is provided. I really like python because its community is treating even goto like this ;)
A working version has been made: http://entrian.com/goto/.
Note: It was offered as an April Fool's joke. (working though)
# Example 1: Breaking out from a deeply nested loop:
from goto import goto, label
for i in range(1, 10):
for j in range(1, 20):
for k in range(1, 30):
print i, j, k
if k == 3:
goto .end
label .end
print "Finished\n"
Needless to say. Yes its funny, but DONT use it.
To answer the #ascobol's question using #bobince's suggestion from the comments:
for i in range(5000):
for j in range(3000):
if should_terminate_the_loop:
break
else:
continue # no break encountered
break
The indent for the else block is correct. The code uses obscure else after a loop Python syntax. See Why does python use 'else' after for and while loops?
It is technically feasible to add a 'goto' like statement to python with some work. We will use the "dis" and "new" modules, both very useful for scanning and modifying python byte code.
The main idea behind the implementation is to first mark a block of code as using "goto" and "label" statements. A special "#goto" decorator will be used for the purpose of marking "goto" functions. Afterwards we scan that code for these two statements and apply the necessary modifications to the underlying byte code. This all happens at source code compile time.
import dis, new
def goto(fn):
"""
A function decorator to add the goto command for a function.
Specify labels like so:
label .foo
Goto labels like so:
goto .foo
Note: you can write a goto statement before the correspnding label statement
"""
labels = {}
gotos = {}
globalName = None
index = 0
end = len(fn.func_code.co_code)
i = 0
# scan through the byte codes to find the labels and gotos
while i < end:
op = ord(fn.func_code.co_code[i])
i += 1
name = dis.opname[op]
if op > dis.HAVE_ARGUMENT:
b1 = ord(fn.func_code.co_code[i])
b2 = ord(fn.func_code.co_code[i+1])
num = b2 * 256 + b1
if name == 'LOAD_GLOBAL':
globalName = fn.func_code.co_names[num]
index = i - 1
i += 2
continue
if name == 'LOAD_ATTR':
if globalName == 'label':
labels[fn.func_code.co_names[num]] = index
elif globalName == 'goto':
gotos[fn.func_code.co_names[num]] = index
name = None
i += 2
# no-op the labels
ilist = list(fn.func_code.co_code)
for label,index in labels.items():
ilist[index:index+7] = [chr(dis.opmap['NOP'])]*7
# change gotos to jumps
for label,index in gotos.items():
if label not in labels:
raise Exception("Missing label: %s"%label)
target = labels[label] + 7 # skip NOPs
ilist[index] = chr(dis.opmap['JUMP_ABSOLUTE'])
ilist[index + 1] = chr(target & 255)
ilist[index + 2] = chr(target >> 8)
# create new function from existing function
c = fn.func_code
newcode = new.code(c.co_argcount,
c.co_nlocals,
c.co_stacksize,
c.co_flags,
''.join(ilist),
c.co_consts,
c.co_names,
c.co_varnames,
c.co_filename,
c.co_name,
c.co_firstlineno,
c.co_lnotab)
newfn = new.function(newcode,fn.func_globals)
return newfn
if __name__ == '__main__':
#goto
def test1():
print 'Hello'
goto .the_end
print 'world'
label .the_end
print 'the end'
test1()
Hope this answers the question.
Python 2 & 3
pip3 install goto-statement
Tested on Python 2.6 through 3.6 and PyPy.
Link: goto-statement
foo.py
from goto import with_goto
#with_goto
def bar():
label .bar_begin
...
goto .bar_begin
Labels for break and continue were proposed in PEP 3136 back in 2007, but it was rejected. The Motivation section of the proposal illustrates several common (if inelegant) methods for imitating labeled break in Python.
you can use User-defined Exceptions to emulate goto
example:
class goto1(Exception):
pass
class goto2(Exception):
pass
class goto3(Exception):
pass
def loop():
print 'start'
num = input()
try:
if num<=0:
raise goto1
elif num<=2:
raise goto2
elif num<=4:
raise goto3
elif num<=6:
raise goto1
else:
print 'end'
return 0
except goto1 as e:
print 'goto1'
loop()
except goto2 as e:
print 'goto2'
loop()
except goto3 as e:
print 'goto3'
loop()
I was looking for some thing similar to
for a in xrange(1,10):
A_LOOP
for b in xrange(1,5):
for c in xrange(1,5):
for d in xrange(1,5):
# do some stuff
if(condition(e)):
goto B_LOOP;
So my approach was to use a boolean to help breaking out from the nested for loops:
for a in xrange(1,10):
get_out = False
for b in xrange(1,5):
if(get_out): break
for c in xrange(1,5):
if(get_out): break
for d in xrange(1,5):
# do some stuff
if(condition(e)):
get_out = True
break
Though there isn't any code equivalent to goto/label in Python, you could still get such functionality of goto/label using loops.
Lets take a code sample shown below where goto/label can be used in a arbitrary language other than python.
String str1 = 'BACK'
label1:
print('Hello, this program contains goto code\n')
print('Now type BACK if you want the program to go back to the above line of code. Or press the ENTER key if you want the program to continue with further lines of code')
str1 = input()
if str1 == 'BACK'
{
GoTo label1
}
print('Program will continue\nBla bla bla...\nBla bla bla...\nBla bla bla...')
Now the same functionality of the above code sample can be achieved in python by using a while loop as shown below.
str1 = 'BACK'
while str1 == 'BACK':
print('Hello, this is a python program containing python equivalent code for goto code\n')
print('Now type BACK if you want the program to go back to the above line of code. Or press the ENTER key if you want the program to continue with further lines of code')
str1 = input()
print('Program will continue\nBla bla bla...\nBla bla bla...\nBla bla bla...')
You can achieve it using nested methods inside python
def func1():
print("inside func1")
def inline():
print("im inside")
inline()
func1()
There is now. goto
I think this might be useful for what you are looking for.
When implementing "goto", one must first ask what a goto is. While it may seem obvious, most people don't think about how goto relates to function stacks.
If you perform a "goto" inside a function, you are, in effect, abandoning the function call stack. This is considered bad practice, because function stacks are designed with the expectation that you will continue where you left off, after delegating an intermediate task. This is why gotos are used for exceptions, and exceptions can be used to emulate goto, which i will explain.
Finite state machines are probably the best use case for goto, which most of the time are implemented in a kludgy way with loops and switch statements, but I believe that "top level" gotos, are the cleanest, most semantic way to implement finite state machines. In this case, you want to make sure, if you have more variables, they are globals, and don't require encapsulation. Make sure you first model your variable state space(which may be different from execution state, ie the finite state machine).
I believe there are legitimate design reasons to use goto, exception handling being the special case where mixing goto with functions makes sense. However, in most cases, you want to restrict yourself to "top level" goto, so you never call goto within a function, but only within a global scope.
The easiest way to emulate top level goto in modern languages, is to realize that top-level gotos, simply require global variables and an empty call stack. So to keep the call stack empty, you return whenever you call a new function. Here's an example to print the first n fibonacci numbers:
a = 0
b = 1
n = 100
def A():
global a, b
a = a + b
n -= 1
print(a)
return B() if n > 0 else 0
def B():
global a, b
b = a + b
n -= 1
print(b)
return A() if n > 0 else 0
A()
While this example may be more verbose than loop implementations, it is also much more powerful and flexible, and requires no special cases. It lets you have a full finite state machine. You could also modify this with a goto runner.
def goto(target):
while(target) target = target()
def A():
global a, b
a = a + b
print(a)
return B
def B():
global a, b
b = a + b
print(b)
return A
goto(A)
To enforce the "return" part, you could write a goto function that simply throws an exception when finished.
def goto(target):
target()
throw ArgumentError("goto finished.")
def A():
global a, b
a = a + b
print(a)
goto(B)
def B()
global a, b
b = a + b
print(b)
goto(A)
goto(A)
So you see, a lot of this is overthinking, and a helper function that calls a function and then throws an error is all you need. You could further wrap it in a "start" function, so the error gets caught, but I don't think that's strictly necessary. While some of these implementations may use up your call stack, the first runner example keeps it empty, and if compilers can do tail call optimization, that helps as well.
I wanted the same answer and I didnt want to use goto. So I used the following example (from learnpythonthehardway)
def sample():
print "This room is full of gold how much do you want?"
choice = raw_input("> ")
how_much = int(choice)
if "0" in choice or "1" in choice:
check(how_much)
else:
print "Enter a number with 0 or 1"
sample()
def check(n):
if n < 150:
print "You are not greedy, you win"
exit(0)
else:
print "You are nuts!"
exit(0)
I have my own way of doing gotos.
I use separate python scripts.
If I want to loop:
file1.py
print("test test")
execfile("file2.py")
a = a + 1
file2.py
print(a)
if a == 10:
execfile("file3.py")
else:
execfile("file1.py")
file3.py
print(a + " equals 10")
(NOTE: This technique only works on Python 2.x versions)
For a forward Goto, you could just add:
while True:
if some condition:
break
#... extra code
break # force code to exit. Needed at end of while loop
#... continues here
This only helps for simple scenarios though (i.e. nesting these would get you into a mess)
In lieu of a python goto equivalent I use the break statement in the following fashion for quick tests of my code. This assumes you have structured code base. The test variable is initialized at the start of your function and I just move the "If test: break" block to the end of the nested if-then block or loop I want to test, modifying the return variable at the end of the code to reflect the block or loop variable I'm testing.
def x:
test = True
If y:
# some code
If test:
break
return something
no there is an alternative way to implement goto statement
class id:
def data1(self):
name=[]
age=[]
n=1
while n>0:
print("1. for enter data")
print("2. update list")
print("3. show data")
print("choose what you want to do ?")
ch=int(input("enter your choice"))
if ch==1:
n=int(input("how many elemet you want to enter="))
for i in range(n):
name.append(input("NAME "))
age.append(int(input("age ")))
elif ch==2:
name.append(input("NAME "))
age.append(int(input("age ")))
elif ch==3:
try:
if name==None:
print("empty list")
else:
print("name \t age")
for i in range(n):
print(name[i]," \t ",age[i])
break
except:
print("list is empty")
print("do want to continue y or n")
ch1=input()
if ch1=="y":
n=n+1
else:
print("name \t age")
for i in range(n):
print(name[i]," \t ",age[i])
n=-1
p1=id()
p1.data1()
I think while loop is alternate for the "goto_Statement". Because after 3.6 goto loop is not working anymore. I also write an example of the while loop.
str1 = "stop"
while str1 == "back":
var1 = int(input(" Enter Ist Number: "))
var2 = int(input(" Enter 2nd Number: "))
var3 = print(""" What is your next operation
For Addition Press And Enter : 'A'
For Muliplt Press And Enter : 'M'
For Division Press And Enter : 'D'
For Subtaction Press And Enter : 'S' """)
var4 = str(input("For operation press any number : "))
if(var1 == 45) and (var2 == 3):
print("555")
elif(var1 == 56) and (var2 == 9):
print("77")
elif(var1 == 56) and (var2 == 6):
print("4")
else:
if(var4 == "A" or "a"):
print(var1 + var2)
if(var4 == "M" or "m"):
print(var1 * var2)
if(var4 == "D" or "d"):
print(var1 / var2)
if(var4 == "S" or "s"):
print(var1 - var2)
print("if you want to continue then type 'stop'")
str1 = input()
print("Strt again")
I solved this problem with functions. Only thing I did was change labels with functions. Here is a very basic code:
def goto_holiday(): #label: holiday
print("I went to holiday :)")
def goto_work(): #label: work
print("I went to work")
salary=5000
if salary>6000:
goto_holiday()
else:
goto_work()