accessing a static dict in Python 3.6 - python-3.x

I have an Enum class of compass directions as follows.
I also have an 'opposites' dict declared in the same class.
from enum import Enum
class Compass(Enum):
N = 'N' # North
S = 'S' # South
E = 'E' # East
W = 'W' # West
opposites = {N: S, S: N, E: W, W: E}
# static method to provide the opposite values.
#staticmethod
def other(com):
return opposites[com]
when I attempt to call other, eg. Compass.other(Compass.N), I expect to get Compass.S, but instead I am getting..
TypeError: 'Com' object is not subscriptable
What's going on, and how can I remedy this pythonically ?

The basic problem is that opposite is being transformed into an Enum member just like N, S,E, and W are. The next problem is the values in opposite -- they do not get transformed into Enum members.
Ideally, we would have something like:
# NB: does not currently work!
class Compass(Enum):
N = 'N', S
S = 'S', N
E = 'E', W
W = 'W', E
Compass.E.opposite is Compass.W # True
The reasons this does not currently work are twofold:
the final transformation from plain value to Enum member happens after the class has been created
forward references are not allowed
So, to get a clean(er) implementation and API we have to post-process the Enum. I would use a decorator:
class reverse():
"decorator to add reverse lookups to Enum members"
def __init__(self, reverse_map):
"initialize decorator by saving map"
self.reverse_map = reverse_map
def __call__(self, enum):
"apply map to newly created Enum"
for first, second in self.reverse_map.items():
enum[first].opposite = enum[second]
enum[second].opposite = enum[first]
# don't forget to return the now-decorated Enum
return enum
and in use:
#reverse({'N':'S', 'E':'W'})
class Compass(Enum):
N = 'N' # North
S = 'S' # South
E = 'E' # East
W = 'W' # West
>>> Compass.N.opposite is Compass.S
True

Your custom class Compass is derived from Enum class which is enumeration but not subscriptable sequence.
Consider this line:
print(type(Compass.N))
While you expect it to output <class 'str'> - it outputs:
<enum 'Compass'>
To access enumaration object property use value attribute.
print(Compass.N.value) # prints "N"
print(Compass.opposites.value) # prints {'S': 'N', 'N': 'S', 'E': 'W', 'W': 'E'}
A proper Compass.other() function declaration should look as below:
# static method to provide the opposite values.
#staticmethod
def other(item):
if item in Compass.opposites.value:
return Compass.opposites.value[item]
else:
raise AttributeError('unknown compass direction :', item)
Usage:
print(Compass.other(Compass.N.value)) # prints "S"

#RomanPerekhrest got the credit for this purely due to speed of response, but it took a bit more wrangling to get what I wanted, which was an enum from the class. The cast to the Enum itself raises an error if bad input is put into it..
The class file folloeinh RomanPerekhrest that worked for me looks like this.
from enum import Enum
class Compass(Enum):
N = 'N' # North
S = 'S' # South
E = 'E' # East
W = 'W' # West
_opposites = {N: S, S: N, E: W, W: E}
#staticmethod
def other(item):
return Compass(Compass._opposites.value[item.value])
if __name__ == "__main__":
print(Compass.other(Compass.E))
However, #EthanFurman's response is beautiful, and I actually implemented that, not that I completely understand it yet...

Related

switch case substitute for inside a python 3.9 class [duplicate]

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

Difference between lists direct assignment and slice assignment

I have:
def reverseString(self, s: List[str]) -> None:
s[:] = s[::-1] # Works
... and
def reverseString(self, s: List[str]) -> None:
s = s[::-1] # Doesn't work
Where s is a list of characters lets say s = ["k","a","k","a","s","h","i"]
While doing a question on leetcode it rejected when I used s = ... but accepted when I used s[:] = ... and also it was written that DO NOT RETURN ANYTHING but return s.reverse also worked.
This is actually a bit complex and requires two explanations.
First, a python function argument act as label on the passed object. For example, in the following code, arg is the local label (/name) attached to the initial list. When the label arg is re-used, for example by attaching it to a new object (17), the original list is not reachable anymore within function f.
On the other hand, outside of f, the list labeled L is still here, untouched:
def f(arg):
arg = 17
print(arg) # 17
L = ['a', 'list']
f(L)
print(L) # ['a', 'list']
That explains why the following function doesn't reverse your list in place:
def reverse_list(arg):
arg = arg[::-1]
print(arg) # ['list', 'a']
L = ['a', 'list']
reverse_list(L)
print(L) # ['a', 'list']
This function simply attach the label arg to a new list (that is indeed equal to the reversed list).
Secondly, the difference between arg[:] = ... and arg = ... is that the first will modify the content of the list (instead of attaching the label arg to a new object). This is the reason why the following works as expected:
def alt_reverse_list(arg):
arg[:] = arg[::-1]
L = ['a', 'list']
alt_reverse_list(L)
print(L) # ['list', 'a']
In this second example we say that the list has been mutated (modified in place). Here is a detailed explanation on slice assignments
For the same reason, calling arg.reverse() would have worked.
Identifying objects
Using the id() function can help figure out what is going on with the argument in the first example (where we don't mutate the list but affect a new value):
def reverse_list(arg):
print("List ID before: ", id(arg))
arg = arg[::-1]
print("List ID after: ", id(arg))
L = ['a', 'list']
print("Original list ID: ", id(L))
reverse_list(L)
print("Final list ID: ", id(L))
Which will print something like:
Original list ID: 140395368281088
List ID before: 140395368281088
List ID after: 140395368280447 <--- intruder spotted
Final list ID: 140395368281088
Here we can clearly see that after calling arg = arg[::-1] the object we are manipulating under the name arg is not the same. This shows why the function doesn't have any (side) effect.

How can I make an Enum that allows reused keys? [duplicate]

I'm trying to get the name of a enum given one of its multiple values:
class DType(Enum):
float32 = ["f", 8]
double64 = ["d", 9]
when I try to get one value giving the name it works:
print DType["float32"].value[1] # prints 8
print DType["float32"].value[0] # prints f
but when I try to get the name out of a given value only errors will come:
print DataType(8).name
print DataType("f").name
raise ValueError("%s is not a valid %s" % (value, cls.name))
ValueError: 8 is not a valid DataType
ValueError: f is not a valid DataType
Is there a way to make this? Or am I using the wrong data structure?
The easiest way is to use the aenum library1, which would look like this:
from aenum import MultiValueEnum
class DType(MultiValueEnum):
float32 = "f", 8
double64 = "d", 9
and in use:
>>> DType("f")
<DType.float32: 'f'>
>>> DType(9)
<DType.double64: 'd'>
As you can see, the first value listed is the canonical value, and shows up in the repr().
If you want all the possible values to show up, or need to use the stdlib Enum (Python 3.4+), then the answer found here is the basis of what you want (and will also work with aenum):
class DType(Enum):
float32 = "f", 8
double64 = "d", 9
def __new__(cls, *values):
obj = object.__new__(cls)
# first value is canonical value
obj._value_ = values[0]
for other_value in values[1:]:
cls._value2member_map_[other_value] = obj
obj._all_values = values
return obj
def __repr__(self):
return '<%s.%s: %s>' % (
self.__class__.__name__,
self._name_,
', '.join([repr(v) for v in self._all_values]),
)
and in use:
>>> DType("f")
<DType.float32: 'f', 8>
>>> Dtype(9)
<DType.float32: 'd', 9>
1 Disclosure: I am the author of the Python stdlib Enum, the enum34 backport, and the Advanced Enumeration (aenum) library.

A simple Python program to study classes

For the sake of studying the concept of classes in Python, I have written a program which is meant to calculate the average of a tuple of numbers. However, the program returns an error message which is quoted.
#!/usr/bin/python3
"""
Python program to calculate the average value of
a set of integers or float numbers.
Input format: a tuple, e.g. (1,2,3)
When run, the program generates an error message in line 27
"""
class Mean_value():
def __init__(self, operand):
self.operand = operand
def calculate_average(self, operand):
self.operand = operand
all_in_all = sum(operand)
nmbr = len(operand)
average = all_in_all/nmbr
self.average = average
return self.average
operand = input("Key in numbers as a tuple: ")
print(operand) #temp, the operand is taken in by the program
x = Mean_value.calculate_average(operand) #line 27
print(x)
The error message:
Traceback (most recent call last):
File "D:\Python\Exercise76a.py", line 27, in <module>
x = Mean_value.calculate_average(operand)
TypeError: calculate_average() missing 1 required positional argument: 'operand'
I would highly appreciate any hints from members more experienced than myself.
Any method in your class with self as the first parameter is an instance method, meaning it's supposed to be called on an instance of the class and not on the class itself.
In other words, the self parameter isn't just for show. When you do this:
x = Mean_value(operand)
x.calculate_average(operand)
the python interpreter actually takes x and passes it through to the function as the first parameter (i.e. self). Hence, when you try to call calculate_average() on the class Mean_value instead of on an object of that type, it only passes one of the two required parameters (there's no instance to pass automatically as self, so it just passes the one argument you've given it, leaving the second argument unspecified).
If you want to have a method be static (called on the class instead of on an instance of the class), you should use the #staticmethod decorator on the method in question, and omit the self parameter.
Another way to fix this error is to make your calculate_average method static. Like this:
#staticmethod
def calculate_average(operand):
# but be careful here as you can't access properties with self here.
all_in_all = sum(operand)
nmbr = len(operand)
average = all_in_all/nmbr
return average
The program contains comments
#!/usr/bin/python3
"""
The program computes the average value of a sequence of positive integers,
keyed in as a tuple.
After entering the tuple, the input function returns a string,
e.g.(1,2,3) (tuple) --> (1,2,3) (string).
On screen the two objects look the same.
The major code block deals with reversing the type of the input,
i.e. string --> tuple,
e.g. (1,2,3) (string) --> (1,2,3) (tuple).
The maths is dealt with by the class Average.
"""
class Average:
def __init__(self, tup):
self.tup = tup
def calculate(self):
return sum(self.tup)/len(self.tup)
"""Major code block begins ----------"""
#create containers
L_orig_lst = []
S_str = ""
print("The program computes the average value of")
print("a sequence of positive integers, input as a tuple.\n")
#in orig_str store the string-type of the tuple keyed in
orig_str = input("Key in the numbers as a tuple:\n")
lnth = len(orig_str)
#copy each character from orig_str into the list L_orig_lst (the original list)
for i in range(lnth):
if orig_str[i] in ['(', '.', ',' , ')', '1', '2', '3','4', '5', '6', '7', '8', '9', '0']:
#if one of the characters left parenthesis, period, comma, right parenthesis or a digit
#is found in orig_str, then S_str is extended with that character
S_str = S_str + orig_str[i]
L_orig_lst.append(S_str)
#set S_str to be empty
S_str = ""
elif orig_str[i] == " ":
pass
else:
print("Error in input")
break
#at this stage the following transformation has taken place,
#tuple (string) --> tuple (list)
#e.g. (1,2,3) (string) --> ['(' , '1' , ',' , '2' , ',' , '3' , ')'], L_orig_lst
#create new container
#and set S_str to be empty
L_rev_lst = []
S_str = ""
lnth = len(L_orig_lst)
#from the original list, L_orig_lst, copy those elements which are digits (type string)
#and append them to the revised list, L_rev_lst.
for i in range(lnth):
if L_orig_lst[i] in ['1', '2', '3','4', '5', '6', '7', '8', '9', '0']:
#if the element in the original list is a digit (type string),
#then extend S_str with this element
S_str = S_str + L_orig_lst[i]
elif L_orig_lst[i] == ',':
#if the element in the original list is a comma, then finalize the reading of the number,
#convert the current number (type string) into an integer
S_int = int(S_str)
#and append the integer to the revised list
L_rev_lst.append(S_int)
#set S_str to be empty
S_str = ""
else:
pass
#also convert the last number (type string) to an integer,
S_int = int(S_str)
#and also append the last integer to the revised list
L_rev_lst.append(S_int)
#now convert the revised list into a tuple
T_tpl = tuple(L_rev_lst)
"""Major code block ends --------"""
#calculate the average for the tuple T_tpl
#call the class
x = Average(T_tpl)
#instantiate the class
y = x.calculate()
print("Average value: ", y)

Python 3 Dictionary Comprehension Exec Error

Can someone explain this error? The contents of DictTest.py are below. If I copy (%paste) this code into an ipython terminal the test passes. If if call
>>> %run DictTest.py -m
The test fails with
name 'keys' is not defined
The 'keys' that it is complaining about is the "in keys" part of the dict comprehension. I am using 3.4.1 |Anaconda 2.1.0 (64-bit) on linux.
#!/usr/bin/python3.4
import unittest
class DictTest(unittest.TestCase):
def test_dict_comprehension(self):
code = """
d = {'a':1, 'b':2, 'c':3, 'd':4}
keys = ['a', 'd']
items = d.items()
nd = {k: v for k, v in items if k in keys}
print('>>>' + str(nd))
"""
try:
exec(code)
except Exception as e:
self.assertTrue(False, "Exec ERROR>>> %s" % e)
def main():
dt = DictTest()
dt.test_dict_comprehension()
if __name__ =='__main__':main()
The answer is (mostly) in the docs for exec, assignment statements, and comprehensions.\
Exec: exec(s) is equivalent to exec(s, globals(), locals()). At module scope (case1), locals is globals(). In function scope (case2), they are two different objects. "If exec gets two separate objects as globals and locals, the code will be executed as if it were embedded in a class definition." The following gives the same error about 'keys' not recognized.
class C:
d = {'a':1, 'b':2, 'c':3, 'd':4}
keys = ['a', 'd']
items = d.items()
nd = {k: v for k, v in items if k in keys}
print('>>>' + str(nd))
=: name = value binds name to value in the local namespace, which may or may not be the same as the global namespace.
{comprehension}: In 3.x, a comprehension is evaluated in a separate context (except for the source of the first for clause -- not documented very well). So items is immediately evaluated and while 'keys' is evaluated in the new context, where locals only has binding for 'k', and 'v' (which is why 'k' gets evaluated). For case 2, 'keys' in not in globals either, and an exception is raised.
A solution for this code:
d = {}
...
exec(code, d, d)
Other uses might require additional initialization for d.

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