I was wondering if the 'a=a', and 'b=b' can lead to problems/unexpected behaviour? code works fine in the example.
def add_func(a=2,b=3):
return a+b
a=4
b=5
answer = add_func(a=a, b=b)
Thanks
Not that I know of, although I'd love to be proved wrong.
The formal language reference defines the lexical structure of a function call. The important bit is that it defines a "keyword_item" as identifier "=" expression. Also, here's what it says about how the arguments to the call are interpreted:
If keyword arguments are present, they are first converted to
positional arguments, as follows. First, a list of unfilled slots is
created for the formal parameters. If there are N positional
arguments, they are placed in the first N slots. Next, for each
keyword argument, the identifier is used to determine the
corresponding slot (if the identifier is the same as the first formal
parameter name, the first slot is used, and so on). If the slot is
already filled, a TypeError exception is raised. Otherwise, the value
of the argument is placed in the slot, filling it (even if the
expression is None, it fills the slot). When all arguments have been
processed, the slots that are still unfilled are filled with the
corresponding default value from the function definition.
This lists a few possible scenarios.
In the simple case, like you mentioned, where there are two formal arguments (a and b), and if you specify the function call using keyword parameters like add_func(a=a, b=b), here's what happens:
Two slots are created to hold the parameters.
Since you didn't provide any positional arguments in the call (just keyword arguments), none of the slots are filled initially.
Each of your keyword arguments are analyzed individually, and the identifier of your argument (the "a" in the a= part) is compared with all of the formal parameters names of the function (the names that were given the parameters when the function was defined, in our case, a and b).
When a match occurs, the value of the keyword arguments (in this case, 4!) is used to fill the corresponding slot.
This repeats until all keyword arguments are analyzed. If all slots aren't filled, then Python tries to assign a default value to the remaining slots if one exists. If not, an error is raised.
So, Python treats the "identifier" in a keyword argument completely differently. This is only true for keyword arguments, though; obviously, if you tried something like add_func(b, a), even though your parameters themselves are called b and a, this would not be mapped to the formal parameters in the function; your parameters would be backwards. However, add_func(b=b, a=a) works fine; the positions don't matter as long as they are keyword arguments.
It depends on whether or not the global objects pointed to are mutable or immutable. immutable objects such as your integers are copies when modified, so it's safe. Mutable objects such as lists are modified in-place, and are NOT safe to use this way. Any change to them persists between calls and may (and probably will) cause unexpected behaviors.
This:
a=[]
def f(a=a):
pass
Is the same as:
def f(a=[]):
pass
Which is a known bad practice in Python programs.
Related
I was just wondering what would be the preferred way in Python to make a group of arguments of a function optional, but only as the whole group.
Meaning: they have to either all be given, or none.
For an example, let's say I want to make a print function, that takes a message string as first positional argument and optionally a file-like object and an encoding as second and third arguments.
Now I want this function to print to stdout if no file is given, and to the file otherwise.
The tricky bit is this: I want this function to always require an encoding to be specified whenever a file is used. And calling this function with an encoding, but no file should also be forbidden.
In Java, I could overload the function and give implementations for both valid variants:
public void print(string message);
public void print(string message, File f, string encoding);
This allows me to call this function in exactly the two ways I want to be possible, with either one or all three arguments.
In Python, I can make single arguments optional by supplying a default value, but I cannot group them together.
def print(msg, file=None, encoding=None)
allows me to call the function by providing a message and none, both or just any one of the other parameters:
print("test")
print("test", file=someFile)
print("test", encoding="utf-8")
print("test", file=someFile, encoding="utf-8")
These are all valid calls to the Python declaration above, even though with my implementation, setting an encoding or file without the other one might make no sense.
I am aware that I could simply check both optionals for an invalid default value and raise an Exception at runtime whenever I find only one is set, but I think that is bad for a couple of reasons:
The Exception is raised only if the invalid call is executed, so it might not occur during testing.
I have no way of telling that both parameters are required as a pair by just looking at the declaration or an auto-generated quick reference without diving into the implementation.
No code analysis tool would be able to warn me about an invalid call.
So is there any better way to syntactically specify that a number of optional arguments are grouped together?
Python is not supporting overloading methods. And there is not a really good way to simulate an overloading design. So best you can do is using if statements with different arguments. Like you do in your method.
Or you can use **kwargs as argument and use if only the desired argument is defined.
def a_very_important_method(**kwargs)
if kwargs["arg1"] is not None:
# logic
if kwargs["arg2"] is not None:
# another logic
a_very_important_method(arg1="value1", arg2="value2")
I mean you could make one parameter expect a tuple as input. Like idk an 2D-array might have a size attribute which requires an input in the shape (x, y). Though that won't save you from checking at runtime whether the supplied values make any sense, does it?
After reading the other answers, it seems to me like the most simple and readable solution would be to write the function with all parameters mandatory and then add a second, "wrapper"- function which has a reduced set of parameters, passes these arguments to the original function on and also gives default values for the other parameters:
def print(msg, file, encoding):
# no default values here, so no parameter is optional
pass
def printout(msg):
# forward the argument and provide default values for the others
print(msg, sys.stdout, "")
Implementing some Neural Network with tensorflow, I've faced a method which parameters have took my attention. I'm talking about tf.nn.sigmoid_cross_entropy_with_logits (Documentation here).
The first parameter it receives as first parameter _sentinel=None which, according to the documentation:
_sentinel: Used to prevent positional parameters. Internal, do not use.
I understand that by having this parameter, next ones have to be named instead of positional is this one don't have to be used, but my question is. In which cases does prevent positional parameters have some benefit? What is their main goal to use this? Because I could also run
tf.nn.sigmoid_cross_entropy_with_logits(None, my_labels, my_logits)
being all arguments positional. Anyway, I want to clarify that my question is not focused in TensorFlow, it's just the example that I have found.
Positional parameters couple the caller and receiver on the order of the parameters. It makes refactoring the order of the reciver's parameters more difficult.
For example, if I have
def foo(a, b, c):
do_stuff(a,b,c)
and I decide, for reasons, perhaps I want to make a partial function or whatever, that it would be better to have
def foo(b, a, c):
do_stuff(a,b,c)
But now I have callers in the wild and it would be very rude to change my contract, so I'm stuck.
Sandi Metz in Practical Object-Oriented Design in Ruby also addresses this. (I know this is python, but oop is oop)
When the code [is changed to use keyword arguments], it lost its dependency
on argument order but it gained a dependency on the names of the keys
in the [keyword arguments]. This change is healthy. The new dependency is
more stable than the old, and thus this code faces less risk of being
forced to change. Additionally, and perhaps unexpectedly, the [keywords]
provides one new, secondary benefit: The key names in the hash furnish
explicit documentation about the arguments. This is a byproduct of
using a hash but the fact that it is unintentional makes it no less
useful. Future maintainers of this code will be grateful for the
information.
Keyword arguments are also nice if you have a lot of parameters. Order is easy to get wrong. It may also make a nicer API in the opinion of the authors.
PEP-3102 also addresses this, but I find the rationale unsatisfying from the perspective of "why would I choose to design something like this"
The current Python function-calling paradigm allows arguments to be
specified either by position or by keyword. An argument can be filled
in either explicitly by name, or implicitly by position.
There are often cases where it is desirable for a function to take a
variable number of arguments. The Python language supports this using
the 'varargs' syntax (*name), which specifies that any 'left over'
arguments be passed into the varargs parameter as a tuple.
One limitation on this is that currently, all of the regular argument
slots must be filled before the vararg slot can be.
This is not always desirable. One can easily envision a function which
takes a variable number of arguments, but also takes one or more
'options' in the form of keyword arguments. Currently, the only way to
do this is to define both a varargs argument, and a 'keywords'
argument (**kwargs), and then manually extract the desired keywords
from the dictionary.
What is the use for keyword only parameters:
For some function, it is impossible to do otherwise (ex: print(a, b, end=''))
It prevents you from making silly mistakes, consider the following example:
# if it wasn't made with kw-only parameters, this would return 3
>>> sorted(3, 1)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: sorted expected 1 arguments, got 2
>>> sorted((1,2), reverse=True)
[2, 1]
It allows you to change things later:
# if
def sorted(iterable, reverse=False)
# becomes
def sorted(iterable, key=None, reverse=False)
# you can guarantee backwards compatibility
First, a caveat that I can't know the intention of the person who wrote that. However, I can offer reason why “prevent positional parameters” might be desirable.
It's often important that a parameter be keyword-only, that is, it must be used only by name. The parameter is not conceptually an input to the function's purpose; it's more a modifier (change the behaviour in this way), or an external resource (here is the log file to emit your messages to), etc.
For that reason, Python 3 now allows you to define, in the signature of the function, specific parameters as keyword-only parameters. The change is documented in PEP 3102 Keyword-only arguments along with rationale.
Let's consider
foo(arg1=123, arg2=None) and foo(arg1=123).
Tell me please, if these two ways are equivalent ?
No, the two given function signatures (and hence functions) are not equivalent.
In foo(arg1=123, arg2=None), you have two arguments -- arg1 and arg2, which can be used inside the function as local names. Note that, assigning a value of None to some name does not make it anything special/different as far as the assignment statements are concerned. It is in fact a common way to give a placeholder value for a variable that is not mandatory or may be an empty mutable object.
On the other hand, foo(arg1=123) has only one argument arg1, which is available on the function's local scope for use.
Edit:
If you have a function defined as foo(arg1, arg2), both arguments are mandatory (positional) arguments.
So, foo(arg1=21) will throw a TypeError as you have not provided arg2. Whereas, foo(arg1=21, arg2=None) will work just fine as you have provided values for both the arguments.
Edit2:
If you have a function defined as foo(arg1=None, arg2=None) (or something similar i.e. with default values), both arguments are optional (keyword) arguments. In that case, both of the mentioned definitions would be the same.
I have a SOAP web service I have to work with, and one of the commands it supports is a "SQL like" query where I input a select, from, and where statements. I think the "where" clause will be most demonstrative of what I'm trying to do so here:
def sql_soap(tablename, where):
sql_where = [soap_object(where_statement) for where_statement in where]
return query
sql_soap('student',where=[{'Condition':'=','Field':'Subject','Value':'Calculus'}])
Basically, the way I've thought to do this is to package a list of where-clause dictionaries. But the dictionaries should always have the same keys. Is there a way to define this type in the function definition? I don't want kwargs or args because I know in advance the data structure.
One thing I looked at was
def sql_soap(tablename, *, where):
Apparently this is only available in newer versions of Python (which I have) but my understanding is the where clause after this is expecting a dictionary, and I want a list of dictionaries.
Generally speaking how do I define a function argument, when I want a dictionary inside of a list, or something else nested? Is there any way besides a dictionary, that I can get a single function parameter (where) to accept all of the arguments I need to make the SOAP where object?
I do not know if this helps, but you could use *where to expect an arbitrary amount of args:
def sql_soap(tablename, *where):
sql_where = [soap_object(where_statement) for where_statement in where]
return query
sql_soap('student',
{'Condition':'=','Field':'Subject','Value':'Calculus'},
{'Condition':'=','Field':'Subject2','Value':'Calculus2'},
)
One thing you can also do, but you would to have to change probaply a lot of code for that, is use namedtuple instead of dictionaries:
from collections import namedtuple
wheretuple = namedtuple("wheretuple", "field condition value")
sql_soap('student', wheretuple("Subject", "=", "Calculus"))
You have not specified anything about types. The * syntax in a function definition only specifies how a caller can provide arguments for the parameters. Parameters before it can be filled with both positional arguments and keyword arguments, those that follow the * can only be specified with keyword arguments.
Put differently, the following calls are now legal:
sql_soap('student', where=[...]) # one positional, one keyword argument
sql_soap(tablename='student', where=[...]) # two keyword arguments
but the following is not:
sql_soap('student', [...]) # two positional arguments
You'll instead get a TypeError exception, TypeError: sql_soap() takes 1 positional argument but 2 were given.
Using * in a function definition does not say anything about what type of objects the parameter accepts. You can still pass anything you like to the function call.
Perhaps you got confused with the *args and **kwargs syntax in function definitions, where those parameters capture all remaining positional or keyword arguments passed in, which did not address any of the other parameters. They don't say anything about the argument types either; instead they put those remaining argument values in a tuple and dictionary, respectively.
Python does now support type hinting, but even type hinting will not let you specify what keys to use in a dictionary.
I'd use named tuples instead here, together with type hints:
from typing import NamedTuple, Sequence
class WhereClause(NamedTuple):
condition: str
field: str
value: str
def sql_soap(tablename: str, where: Sequence[WhereClause]):
...
This lets the type checker know that the where argument must be a sequence type (like a list), that contains only WhereClause instances. And those instances will have specific attributes.
Anytime you want to use any of the WhereClause instances, you can use attributes to get at the contents, so whereclause.condition and whereclause.value.
I am a beginner in python programming and recently i came across functions,parameters,arguments and...
I have done a lot of research on Parameters and Arguments(Even checked the answers of similar past questions on StackOverflow)but i couldn't get their meanings.
Some say,parameters are variables which we give them to functions while we are defining them and arguments are values that are passed in function once we given them to the function in order to run the function.While some other say no,it's not like that.Parameters and Arguments are same and do the same task...
Can anyone tell me the meaning Parameters and Arguments in a clear way?
Are Parameters and Arguments considered variables?
For what kind of purpose do we use them?
Please don't explain too much complicated,i am a beginner.
Thank you so much.
Per the official documentation:
Parameters are defined by the names that appear in a function definition, whereas arguments are the values actually passed to a function when calling it. Parameters define what types of arguments a function can accept. For example, given the function definition:
def func(foo, bar=None, **kwargs):
pass
foo, bar and kwargs are parameters of func. However, when calling func, for example:
func(42, bar=314, extra=somevar)
the values 42, 314, and somevar are arguments.
The glossary defines them as:
Argument: A value passed to a function (or method) when calling the function.
Parameter: A named entity in a function (or method) definition that specifies an argument (or in some cases, arguments) that the function can accept.
Python doesn't really have "variables" like some other languages - it has "names" referring to "objects". See e.g. "Code like a Pythonista" and "Facts and myths about Python names and values".
Take it this way:
Parameter:
A parameter represents a value that the procedure expects you to pass when you call it. The procedure's declaration defines its parameters.
Argument:
An argument represents the value that you pass to a procedure parameter when you call the procedure. The calling code supplies the arguments when it calls the procedure.
Example:
int add (int value1, int value2) // Here value1 and value2 are PARAMETERS.
{
return value1+value2;
}
Now while calling the function
answer = add(2,3); // Here values 2 and 3 are ARGUMENTS.
Same goes with Python, while declaration, they are parameters, while calling they are arguments.
Some may differ with what i have written, but this is how it is actually known in programming world.