I have some topic to discuss. I have a fragment of code with 24 ifs/elifs. Operation is my own class that represents functionality similar to Enum. Here is a fragment of code:
if operation == Operation.START:
strategy = strategy_objects.StartObject()
elif operation == Operation.STOP:
strategy = strategy_objects.StopObject()
elif operation == Operation.STATUS:
strategy = strategy_objects.StatusObject()
(...)
I have concerns from readability point of view. Is is better to change it into 24 classes and use polymorphism? I am not convinced that it will make my code maintainable... From one hand those ifs are pretty clear and it shouldn't be hard to follow, on the other hand there are too many ifs.
My question is rather general, however I'm writing code in Python so I cannot use constructions like switch.
What do you think?
UPDATE:
One important thing is that StartObject(), StopObject() and StatusObject() are constructors and I wanted to assign an object to strategy reference.
You could possibly use a dictionary. Dictionaries store references, which means functions are perfectly viable to use, like so:
operationFuncs = {
Operation.START: strategy_objects.StartObject
Operation.STOP: strategy_objects.StopObject
Operation.STATUS: strategy_objects.StatusObject
(...)
}
It's good to have a default operation just in case, so when you run it use a try except and handle the exception (ie. the equivalent of your else clause)
try:
strategy = operationFuncs[operation]()
except KeyError:
strategy = strategy_objects.DefaultObject()
Alternatively use a dictionary's get method, which allows you to specify a default if the key you provide isn't found.
strategy = operationFuncs.get(operation(), DefaultObject())
Note that you don't include the parentheses when storing them in the dictionary, you just use them when calling your dictionary. Also this requires that Operation.START be hashable, but that should be the case since you described it as a class similar to an ENUM.
Python's equivalent to a switch statement is to use a dictionary. Essentially you can store the keys like you would the cases and the values are what would be called for that particular case. Because functions are objects in Python you can store those as the dictionary values:
operation_dispatcher = {
Operation.START: strategy_objects.StartObject,
Operation.STOP: strategy_objects.StopObject,
}
Which can then be used as follows:
try:
strategy = operation_dispatcher[operation] #fetch the strategy
except KeyError:
strategy = default #this deals with the else-case (if you have one)
strategy() #call if needed
Or more concisely:
strategy = operation_dispatcher.get(operation, default)
strategy() #call if needed
This can potentially scale a lot better than having a mess of if-else statements. Note that if you don't have an else case to deal with you can just use the dictionary directly with operation_dispatcher[operation].
You could try something like this.
For instance:
def chooseStrategy(op):
return {
Operation.START: strategy_objects.StartObject
Operation.STOP: strategy_objects.StopObject
}.get(op, strategy_objects.DefaultValue)
Call it like this
strategy = chooseStrategy(operation)()
This method has the benefit of providing a default value (like a final else statement). Of course, if you only need to use this decision logic in one place in your code, you can always use strategy = dictionary.get(op, default) without the function.
Starting from python 3.10
match i:
case 1:
print("First case")
case 2:
print("Second case")
case _:
print("Didn't match a case")
https://pakstech.com/blog/python-switch-case/
You can use some introspection with getattr:
strategy = getattr(strategy_objects, "%sObject" % operation.capitalize())()
Let's say the operation is "STATUS", it will be capitalized as "Status", then prepended to "Object", giving "StatusObject". The StatusObject method will then be called on the strategy_objects, failing catastrophically if this attribute doesn't exist, or if it's not callable. :) (I.e. add error handling.)
The dictionary solution is probably more flexible though.
If the Operation.START, etc are hashable, you can use dictionary with keys as the condition and the values as the functions to call, example -
d = {Operation.START: strategy_objects.StartObject ,
Operation.STOP: strategy_objects.StopObject,
Operation.STATUS: strategy_objects.StatusObject}
And then you can do this dictionary lookup and call the function , Example -
d[operation]()
Here is a bastardized switch/case done using dictionaries:
For example:
# define the function blocks
def start():
strategy = strategy_objects.StartObject()
def stop():
strategy = strategy_objects.StopObject()
def status():
strategy = strategy_objects.StatusObject()
# map the inputs to the function blocks
options = {"start" : start,
"stop" : stop,
"status" : status,
}
Then the equivalent switch block is invoked:
options["string"]()
Related
Let's say,
def sample():
if a==1:
print(a)
else:
continue
for i in language:
a=i
sample()
I want to use this function in a loop, but the continue command gives me an error because there is no loop. What can I do?
Return a boolean from the function and based on the return value make continue or not because continue must be within a loop
continue keyword in python is only available in for or while loops. Also block defined variables like a are not available on the global scope.
I don't know what you want to achieve but assuming your code, you want to extract a condition into a function, something like this:
def condition(a):
return a == 1
def sample(a):
print(a)
for i in language:
a=i
if condition(a):
sample(a)
else:
continue
There are several best-practice patterns of exactly how to do this, depending on your needs.
0. Factor your code better
Before doing any of the below, stop and ask yourself if you can just do this instead:
def sample(a):
print(a)
for i in language:
if i != 1:
continue
sample(i)
This is so much better:
it's clearer to the reader (everything you need to understand the loop's control flow is entirely local to the loop - it's right there in the loop, we don't have to look anywhere else farther away like a function definition to know when or why or how the loop will do the next thing),
it's cleaner (less boilerplate code than any of the solutions below),
it's more efficient, technically (not that this should matter until you measure a performance problem, but this might appeal to you; going into a function and coming back out of it, plus somehow telling the loop outside the function to continue - that's more work to achieve the same thing), and
it's simpler (objectively: there is less code complected together - the loop behavior is no longer tied to the body of the sample function, for example).
But, if you must:
1. Add boolean return
The simplest change that works with your example is to return a boolean:
def sample(a):
if a==1:
print(a)
else:
return True
return False
for i in language:
if sample(i):
continue
However, don't just mindlessly always use True for continue - for each function, use the one that fits with the function. In fact, in well-factored code, the boolean return value will make sense without even knowing that you are using it in some loop to continue or not.
For example, if you have a function called check_if_valid, then the boolean return value just makes sense without any loops - it tells you if the input is valid - and at the same time, either of these loops is sensible depending on context:
for thing in thing_list:
if check_if_valid(thing):
continue
... # do something to fix the invalid things
for thing in thing_list:
if not check_if_valid(thing):
continue
... # do something only with valid things
2. Reuse existing return
If your function already returns something, or you can rethink your code so that returns make sense, then you can ask yourself: is there a good way to decide to continue based on that return value?
For example, let's say inside your sample function you were actually trying to do something like this:
def sample(a):
record = select_from_database(a)
if record.status == 1:
print(record)
else:
continue
Well then you can rewrite it like this:
def sample(a):
record = select_from_database(a)
if record.status == 1:
print(record)
return record
for i in language:
record = sample(a)
if record.status != 1:
continue
Of course in this simple example, it's cleaner to just not have the sample function, but I am trusting that your sample function is justifiably more complex.
3. Special "continue" return
If no existing return value makes sense, or you don't want to couple the loop to the return value of your function, the next simplest pattern is to create and return a special unique "sentinel" object instance:
_continue = object()
def sample(a):
if a==1:
print(a)
else:
return _continue
for i in language:
result = sample(i):
if result = _continue:
continue
(If this is part of a module's API, which is something that you are saying if you name it like sample instead of like _sample, then I would name the sentinel value continue_ rather than _continue... But I also would not make something like this part of an API unless I absolutely had to.)
(If you're using a type checker and it complains about returning an object instance conflicting with your normal return value, you can make a Continue class and return an instance of that instead of an instance of object(). Then the type hinting for the function return value can be a type union between your normal return type and the Continue type. If you have multiple control flow constructs in your code that you want to smuggle across function call lines like this.)
4. Wrap return value (and "monads")
Sometimes, if the type union thing isn't good enough for some reason, you may want to create a wrapper object, and have it store either your original return value, or indicate control flow. I only mention this option for completeness, without examples, because I think the previous options are better most of the time in Python. But if you take the time to learn about "Option types" and "maybe monads", it's kinda like that.
(Also, notice that in all of my examples, I fixed your backdoor argument passing through a global variable to be an explicit clearly passed argument. This makes the code easier to understand, predict, and verify for correctness - you might not see that yet but keep an eye out for implicit state passing making code harder to follow and keep correct as you grow as a developer, read more code by others, and deal with bugs.)
It is because the scope of the function doesn't know we are in a loop. You have to put the continue keyword inside the loop
continue keyword cannot be used inside a function. It must be inside the loop. There is a similar question here. Maybe you can do something like the following.
language = [1,1,1,2,3]
a = 1
def sample():
if a == 1:
print(a)
return False
else:
return True
for i in language:
if sample():
continue
else:
a = i
OR something like this:
language = [1,1,1,2,3]
a = 1
def gen(base):
for item in base:
if a == 1:
yield a
else:
continue
for i in gen(language):
a = i
print(a)
I'm trying to store a function in a list, retrieve the function from the list later, and then call on that function. This is basically what I want to do, without any specifics. It doesn't show my purpose, but it's the same issue.
elements: list = [] # List meant to contain a tuple with the name of the item and the function of the item.
def quit_code():
exit()
element.append(("quit", quit_code))
Now, somewhere else in the code, I want to be able to use an if statement to check the name of the item and, if it's the right one at that time, run the function.
user_input = "quit" # For brevity, I'm just writing this. Let's just imagine the user actually typed this.
if elements[0][0] == user_input:
#This is the part I don't understand so I'm just going to make up some syntax.
run_method(elements[0][1])
The method run_method that I arbitrarily made is the issue. I need a way to run the method returned by elements[0][1], which is the quit_code method. I don't need an alternative solution to this example because I just made it up to display what I want to do. If I have a function or object that contains a function, how can I run that function.
(In the most simplified way I can word it) If I have object_a (for me it's a tuple) that contains str_1 and fun_b, how can I run fun_b from the object.
To expand on this a little more, the reason I can't just directly call the function is because in my program, the function gets put into the tuple via user input and is created locally and then stored in the tuple.
__list_of_stuff: list = []
def add_to_list(name, function):
__list_of_stuff.append((name, function))
And then somewhere else
def example_init_method():
def stop_code():
exit()
add_to_list("QUIT", stop_code())
Now notice that I can't access the stop_code method anywhere else in the code unless I use it through the __list_of_stuff object.
Finally, It would be nice to not have to make a function for the input. By this, I mean directly inserting code into the parameter without creating a local function like stop_code. I don't know how to do this though.
Python treats functions as first-class citizens. As such, you can do things like:
def some_function():
# do something
pass
x = some_function
x()
Since you are storing functions and binding each function with a word (key), the best approach would be a dictionary. Your example could be like this:
def quit_code():
exit()
operations = dict(quit=quit_code)
operations['quit']()
A dictionary relates a value with a key. The only rule is the key must be immutable. That means numbers, strings, tuples and other immutable objects.
To create a dictionary, you can use { and }. And to get a value by its key, use [ and ]:
my_dictionary = { 'a' : 1, 'b' : 10 }
print(my_dictionary['a']) # It will print 1
You can also create a dictionary with dict, like so:
my_dictionary = dict(a=1, b=10)
However this only works for string keys.
But considering you are using quit_code to encapsulate the exit call, why not using exit directly?
operations = dict(quit=exit)
operations['quit']()
If dictionaries aren't an option, you could still use lists and tuples:
operations = [('quit',exit)]
for key, fun in operations:
if key == 'quit':
fun()
I am developing this Python project where I encounter a situation many times and I wondered if there is a better way.
There is a list of class instances. Some part of lists are empty(filled with None).
Here is an example list.
ins_list = [ins_1, ins_2, None, ins_3, None]
I have to do some confirmations throughout the program flow. There are points where I need the control an attribute of these instances. But only indexes are given for choosing an instance from the list and it may be one of the empty elements. Which would give an error when the attribute is called. Here is an example program flow.
ind = 2
if ins_list[ind].some_attribute == "thing":
# This would give error when empty element is selected.
I deal with this by using,
if ins_list[ind]:
if ins_list[ind].some_attribute == "thing":
# This works
I am okay with using this. However the program is a long one, I apply this hundreds of times. Is there an easier, better way of doing this, it means I am producing reduntant code and increasing indentation level for no reason. I wish to know if there is such a solution.
Use a boolean operator and.
if ins_list[ind] and ins_list[ind].some_attribute == "thing":
# Code
As coder proposed, you can remove None from your list, or use dictionaries instead, to avoid to have to create an entry for each index.
I want to propose another way: you can create a dummyclass and replace None by it. This way there will be no error if you set an attribute:
class dummy:
def __nonzero__(self):
return False
def __setattr__(self, k, v):
return
mydummy = dummy()
mylist = [ins_1, ins_2, mydummy, ins_3, mydummy]
nothing will be stored to the dummyinstances when setting an attribute
edit:
If the content of the original list cannot be chosen, then this class could help:
class PickyList(list):
def __init__(self, iterable, dummyval):
self.dummy = dummyval
return super(PickyList, self).__init__(iterable)
def __getitem__(self, k):
v = super(PickyList, self).__getitem__(k)
return (self.dummy if v is None else v)
mylist = PickyList(ins_list, mydummy)
There are these two options:
Using a dictionary:
Another way would be to use a dictionary instead. So you could create your dictionary once the list is filled up with elements. The dictionary's keys would be the values of your list and as values you could use the attributes of the elements that are not None and "No_attr" for those that are None. (Note: Have in mind that python dictionaries don't support duplicate keys and that's why I propose below to store as keys your list indexes else you will have to find a way to make keys be different)
For example for a list like:
l = [item1,item2,None,item4]
You could create a dictionary:
d = {item1:"thing1", item2:"thing2", None:"No_attr", item3:"thing3"}
So in this way every time you would need to make a check, you wouldn't have to check two conditions, but you could check only the value, such as:
if d.values()[your_index]=="thing":
The only cons of this method is that standard python dictionaries are inherently unordered, which makes accessing dictionary values by index a bit dangerous sometimes - you have to be careful not to change the form-arrangement of the dictionary.
Now, if you want to make sure that the index stays stable, then you would have to store it some way, for example select as keys of your dictionary the indexes, as you will have already stored the attributes of the items - But that is something that you will have to decide and depends strongly on the architecture of your project.
Using a list:
In using lists way I don't think there is a way to avoid your if statement - and is not bad actually. Maybe use an and operator as it is mentioned already in another answer but I don't think that makes any difference anyway.
Also, if you want to use your first approach:
if ins_list[ind].some_attribute == "thing":
You could try using and exception catcher like this:
try:
if ins_list[ind].some_attribute == "thing":
#do something
except:
#an error occured
pass
In this case I would use an try-except statement because of EAFP (easier to ask for forgivness than permission). It won't shorten yout code but it's a more Pythonic way to code when checking for valid attributes. This way you won't break against DRY (Don't Repat Yourself) either.
try:
if ins_list[ind].some_attribute == "thing":
# do_something()
except AttributeError:
# do_something_else()
I've heard that python functions are objects, similar to lists or dictionaries, etc. However, what would be a similar way of performing this type of action with a function?
# Assigning empty list to 'a'
a = list()
# Assigning empty function to 'a'
a = lambda: pass
# ???
How would you do this? Further, is it necessary or proper?
Here is the sense in which I would like to use it for better context:
I have a QListWidget for selecting items which are associated with keys in a dictionary. The values in this dictionary are also dictionaries, which hold certain properties of the items, which I can add. These certain properties are stored as keys, and the values in them are initialized or updated by calling different functions. So, I'm storing a variable in the window which gets updated when a button is pressed to tell this script which property to update.
As you can see, I would like to store the function to map to the data using the correct function based on the situation.
# Get selection from the list
name = selected_item
# Initialize an empty function
f = lambda: pass
# Use property that is being added now, which was updated by the specific button that was pushed
property_list = items[name][self.property_currently_being_added]
if self.property_currently_being_added == "prop1":
f = make_property1()
elif self.property_currently_being_added == "prop2":
f = make_property2()
elif self.property_currently_being_added == "prop3":
f = make_property3()
elif self.property_currently_being_added == "prop4":
f = make_property4()
# map the certain function to the data which was retrieved earlier
added_property = map(f, data)
property_list.append(added_property)
First, the reason this doesn't work:
a = lamdba: pass
… is that lambda only allows an expression, and defines a function that returns the value of the expression. Since pass is a statement, not an expression, this is illegal.
However, this works just fine:
a = lambda: None
In Python, a function that falls off the end without a return statement always returns None. So, these are equivalent:
def a(): return None
def a(): pass
However, I don't see why you want to write this as a lambda and an assignment anyway; the def is shorter, and more readable, and gives you an introspectable function object with a nice name (a instead of <lambda>), and so on. The only reasons to ever use lambda are when you don't want to give the function a name, or when you need to define the function inside an expression. Obviously neither of those are true, because you use the lambda directly inside an assignment statement. So, just use def.
Meanwhile, this is in a sense an "empty function", or at least as empty as possible (as you can see by, e.g., calling dis.dis(a), it still takes two bytecodes to do nothing but fall off the end and return None), but it's not useful for your case. You don't want an "empty function". If you try passing your a to map, you're just going to get a TypeError, because you're trying to call a function of no arguments with one argument. (Because that's what map does.)
What you might want is an identity function, which just returns its argument as-is. Like this:
def a(x): return x
But I'm not sure that's what you want. Did you want to append data as-is in that case? Or did you want to do something different, like return early, or raise an exception, or not append anything, or …?
Finally, I don't see why you want a function at all. Why not just not call map if you have nothing to map? You have a perfectly good else clause that already catches that case (especially handy if what you want to do is return early or raise…). Or, if you prefer, you can start with f = None, and then use an if f: do decide whether to map or not. Or, if you really want:
added_property = [f(element) if f else element for element in data]
… or …
added_property = map(f, data) if f else data
As one last note, instead of a long if/elif chain that repeats the same thing over and over again, you might want a dict:
propfuncs = {'prop1': make_property1(),
'prop2': make_property2(),
'prop3': make_property3(),
'prop4': make_property4()}
Then, all that cruft turns into these two lines:
f = propfuncs.get(self.property_currently_being_added)
added_property = map(f, data) if f else data
Or course an even better design might be to replace all those make_propertyN functions with a single function that you call as make_property(1) or make_property('prop1')… but without seeing what they actually do, I can't be sure of that.
For completeness and since the title is "empty function object in python", more general case is an empty function object that takes any number of parameters, so you can use it in any callback. It's this one:
callback = lambda *_, **__: None
Explanation is here: http://echochamber.me/viewtopic.php?t=64825
I am surprised to learn that you can even do...
def a(): "This is a test"
a()
this feels so much like you're looking for a Nothing functor, I am guessing that if you had knowledge of Monads you wouldn't even need an empty function , as inspiration PyMonad has a nice Nothing implementation, I usually like to create my own, but it's a good starting point.
I am trying to optimize code that was originally written using namedtuples and function to modify them.
Each function would be called a great number of time for various values of the same namedtuple type.
Basic example would be:
def modifyTuple(record):
if record.field1 == True:
record.field2 = "VALUE1"
elif record.field3 == "SPECIAL":
record.field2 = "VALUE2"
The analysis of the bottleneck which i was experiencing and it shows that using multiple dictionary lookups every time the function is called leads to lost time. I am now trying to rewrite functions on-the-fly using inspect and basic string replacements, based on simple lists and a map from field names to fields indices.
def modifyTuple(record):
if record[0] == True:
record[1] = "VALUE1"
elif record[2] == "SPECIAL":
record[3] = "VALUE2"
This code is generated and used (i have a function which returns the modified transformation function, after internally redefining and compiling it using exec). It seems to work well, but i can't seem to find a way to deal with the case when the function actually is a class method, and therefore has a complementary "self" argument.
How should this be dealt with ? Any ideas ?