We Keep Coding

How do you call a method from a class? [duplicate]

Closed. This question does not meet Stack Overflow guidelines. It is not currently accepting answers.
Questions asking for code must demonstrate a minimal understanding of the problem being solved. Include attempted solutions, why they didn't work, and the expected results. See also: Stack Overflow question checklist
Closed 9 years ago.
Improve this question
What does "call" mean and do? How would you "call" a function in Python?

When you "call" a function you are basically just telling the program to execute that function. So if you had a function that added two numbers such as:
def add(a,b):
return a + b
you would call the function like this:
add(3,5)
which would return 8. You can put any two numbers in the parentheses in this case. You can also call a function like this:
answer = add(4,7)
Which would set the variable answer equal to 11 in this case.

I'll give a slightly advanced answer. In Python, functions are first-class objects. This means they can be "dynamically created, destroyed, passed to a function, returned as a value, and have all the rights as other variables in the programming language have."
Calling a function/class instance in Python means invoking the __call__ method of that object. For old-style classes, class instances are also callable but only if the object which creates them has a __call__ method. The same applies for new-style classes, except there is no notion of "instance" with new-style classes. Rather they are "types" and "objects".
As quoted from the Python 2 Data Model page, for function objects, class instances(old style classes), and class objects(new-style classes), "x(arg1, arg2, ...) is a shorthand for x.__call__(arg1, arg2, ...)".
Thus whenever you define a function with the shorthand def funcname(parameters): you are really just creating an object with a method __call__ and the shorthand for __call__ is to just name the instance and follow it with parentheses containing the arguments to the call. Because functions are first class objects in Python, they can be created on the fly with dynamic parameters (and thus accept dynamic arguments). This comes into handy with decorator functions/classes which you will read about later.
For now I suggest reading the Official Python Tutorial.

To "call" means to make a reference in your code to a function that is written elsewhere. This function "call" can be made to the standard Python library (stuff that comes installed with Python), third-party libraries (stuff other people wrote that you want to use), or your own code (stuff you wrote). For example:
#!/usr/env python
import os
def foo():
return "hello world"
print os.getlogin()
print foo()
I created a function called "foo" and called it later on with that print statement. I imported the standard "os" Python library then I called the "getlogin" function within that library.

when you invoke a function , it is termed 'calling' a function .
For eg , suppose you've defined a function that finds the average of two numbers like this-
def avgg(a,b) :
return (a+b)/2;
now, to call the function , you do like this .
x=avgg(4,6)
print x
value of x will be 5 .

Modules and variable scopes

I'm not an expert at python, so bear with me while I try to understand the nuances of variable scopes.
As a simple example that describes the problem I'm facing, say I have the following three files.
The first file is outside_code.py. Due to certain restrictions I cannot modify this file. It must be taken as is. It contains some code that runs an eval at some point (yes, I know that eval is the spawn of satan but that's a discussion for a later day). For example, let's say that it contains the following lines of code:
def eval_string(x):
return eval(x)
The second file is a set of user defined functions. Let's call it functions.py. It contains some unknown number of function definitions, for example, let's say that functions.py contains one function, defined below:
def foo(x):
print("Your number is {}!".format(x))
Now I write a third file, let's call it main.py. Which contains the following code:
import outside_code
from functions import *
outside_code.eval_string("foo(4)")
I import all of the function definitions from functions.py with a *, so they should be accessible by main.py without needing to do something like functions.foo(). I also import outside_code.py so I can access its core functionality, the code that contains an eval. Finally I call the function in outside_code.py, passing a string that is related to a function defined in functions.py.
In the simplified example, I want the code to print out "Your number is 4!". However, I get an error stating that 'foo' is not defined. This obviously means that the code in outside_code.py cannot access the same foo function that exists in main.py. So somehow I need to make foo accessible to it. Could anyone tell me exactly what the scope of foo currently is, and how I could extend it to cover the space that I actually want to use it in? What is the best way to solve my problem?

You'd have to add those names to the scope of outside_code. If outside_code is a regular Python module, you can do so directly:
import outside_code
import functions
for name in getattr(functions, '__all__', (n for n in vars(functions) if not n[0] == '_')):
setattr(outside_code, name, getattr(functions, name))
This takes all names functions exports (which you'd import with from functions import *) and adds a reference to the corresponding object to outside_code so that eval() inside outside_code.eval_string() can find them.
You could use the ast.parse() function to produce a parse tree from the expression before passing it to eval_function() and then extract all global names from the expression and only add those names to outside_code to limit the damage, so to speak, but you'd still be clobbering the other module namespace to make this work.
Mind you, this is almost as evil as using eval() in the first place, but it's your only choice if you can't tell eval() in that other module to take a namespace parameter. That's because by default, eval() uses the global namespace of the module it is run in as the namespace.
If, however, your eval_string() function actually accepts more parameters, look for a namespace or globals option. If that exists, the function probably looks more like this:
def eval_string(x, namespace=None):
return eval(x, globals=namespace)
after which you could just do:
outside_code.eval_string('foo(4)', vars(functions))
where vars(functions) gives you the namespace of the functions module.

foo has been imported into main.py; its scope is restricted to that file (and to the file where it was originally defined, of course). It does not exist within outside_code.py.
The real eval function accepts locals and globals dicts to allow you to add elements to the namespace of the evaluted code. But you can't do anything if your eval_string doesn't already pass those on.

The relevant documentation: https://docs.python.org/3.5/library/functions.html#eval
eval takes an optional dictionary mapping global names to values
eval('foo(4)', {'foo': foo})
Will do what you need. It is mapping the string 'foo' to the function object foo.
EDIT
Rereading your question, it looks like this won't work for you. My only other thought is to try
eval_str('eval("foo(4)", {"foo": lambda x: print("Your number is {}!".format(x))})')
But that's a very hackish solution and doesn't scale well to functions that don't fit in lambdas.

Python arguments- how do you use them? [duplicate]

What are [function] arguments? What are they used for?
I started learning Python very recently; I'm new to programming and I apologize for this basic question.
In every Python tutorial I go through they talk about arguments. I have looked for the answer to this question and have found many answers but they are just a little too hard for me to understatnd. I may just be missing some conceptual background.
So... when I define a function, what are the things in parenthesis used for?
Example:
def hi( This is the part that i dont get):
print 'hi'
Edit:
Two follow-up questions related to this one were later closed and merged here, hence the partial out-of-context trait of some of the answers.
The follow-up questions were: [paraphrased]
Can arguments only be used for input ?
what are other examples of the use of arguments ?
Why use arguments, rather than having the function call raw_input ?
Why is the concept of argument passing described as such a powerful thing? it seems to me we're merely using them to replace stuff the user could have type on the keyboard.

In a few words, they're data that gets "passed into" the function to tell it what to do. Wikipedia has details.
http://en.wikipedia.org/wiki/Function_argument
For instance, your hi() function might need to know who to say hello to:
def hi(person):
print "Hi there " + person + ", how are you?"
Or a mathematical function might need a value to operate on:
def square(x):
return x * x

This is not a Python question, but rather a generic programming question. A very basic one.
Before answering the question about arguments, and in view of the other questions you asked, it is useful to discuss the concept of variables.
A variable is a named piece of memory where information of interest to the underlying program can be stored and retrieved. In other words, it is a symbolic name, chosen by the programmer, that is associated to its contents. Using various language constructs generally known as assignments, the programmer can read or write the contents of a variable.
It is important to note that the value (i.e. the content) of a variable needn't be defined when the program is written. It is only necessary at run-time. This allows the program to describe actions to be performed on symbolic elements without knowing exactly the value these elements have. Consider this snippet, part of a bigger program:
# ... some logic above
ball_volume = 4.0 / 3 * math.pi * ball_radius
if ball_volume > 200:
print ("Man, that's a big ball")
# ... more logic below
At the time the program is written one doesn't need to know the actual value of ball_radius; yet, with the assumption that this variable will contain the numeric value of some hypothetical ball, the snippet is capable of describing how to compute the ball's volume. In this fashion, when the program is running, and somehow (more on this later) the ball_radius variable has been initialized with some appropriate value, the variable ball_volume can too be initialized and used, here in the conditional statement (if), and possibly below. (At some point the variable may go out-of-scope, but this concept which controls when particular variables are accessible to the program is well beyond this primer).
In some languages the type of data that may be associated with a particular variable needs to be explicitly defined and cannot change. For example some variables could hold only integer values, other variables string values (text) etc. In Python there is no such restriction, a variable can be assigned and re-assigned to any type of data, but of course, the programmer needs to keep track of this for example to avoid passing some text data to a mathematical function.
The data stored inside variable may come from very different sources. Many of the examples provided in tutorials and introductory documentation have this data coming from keyboard input (as when using raw_input as mentioned in some of your questions). That is because it allows interactive tests by the people trying out these tutorial snippets. But the usefulness of programs would be rather limited if variables only get their data from interactive user input. There are many other sources and this is what makes programming so powerful: variables can be initialized with data from:
databases
text files or files various text-base formats (XML, JSON, CSV..)
binary files with various formats
internet connections
physical devices: cameras, temperature sensors...
In a nutshell, Arguments, also called Parameters, are variables passed to the function which [typically] are used to provide different output and behavior from the function. For example:
>>> def say_hello(my_name):
... print("Hello,", my_name, "!")
>>> say_hello("Sam")
Hello, Sam !
>>> customer_name = "Mr Peter Clark" #imagine this info came from a database
>>> # ...
>>> say_hello(customer_name)
Hello, Mr Peter Clark !
>>>
In the example above, my_name is just like any local variable of the say_hello function; this allows the function to define what it will do with the underlying value when the function is called, at run-time.
At run-time, the function can be called with an immediate value (a value that is "hard-coded" in the logic, such as "Sam" in the example), or with [the value of] another variable (such as customer_name). In both cases the value of the function's my_name variable gets assigned some value, "Sam" and "Mr Peter Clark" respectively. In the latter case, this value is whatever the customer_name variable contains. Note that the names of the variables used inside the function (my_name) and when the function is called (customer_name) do not need to be the same. (these are called the "formal parameter(s)" and the "actual parameters" respectively)
Note that while typically most arguments as passed as input to a function, in some conditions, they can be used as output, i.e. to provide new/modified values at the level of the logic which called the function. Doing so requires using, implicitly or explicitly, the proper calling convention specification (See Argument passing conventions below)
Now... beyond this very basic understanding of the purpose of parameters, things get a little more complicated than that (but not much). I'll discuss these additional concepts in general and illustrate them as they apply to Python.
Default values for arguments (aka "optional" arguments)
When the function is declared it may specify the default value for some parameters. These values are used for the parameters which are not specified when the function is called. For obvious reasons these optional parameters are found at the end of the parameter list (otherwise the language compiler/interpreter may have difficulty figuring out which parameter is which...)
>>> def say_hello(dude = "Sir"):
... print("Hello,", dude, "!")
...
>>> say_hello()
Hello, Sir !
>>> say_hello("William Gates")
Hello, Bill ! #just kidding ;-)
Hello, William Gates ! # but indeed. works as the original function when param
# is specified
Variable number of parameters
In some cases it may be handy to define a function so that it may accept a variable number of parameters. While such lists of parameter values ultimately get passed in some kind of container (list, array, collection...) various languages offers convenient ways of accessing such parameter values.
>>> def add_many(operand1, *operands):
... Sum = operand1
... for op in operands:
... Sum += op
... return Sum
...
>>> add_many(1, 3, 5, 7, 20)
36
>>> add_many(1, 3)
4
Named Arguments (Keyword Arguments)
With Python and a few other languages, it is possible to explicitly name the arguments when calling the function. Whereby argument passing is by default based a positional basis ("1st argument, 2nd argument etc.), Python will let you name the arguments and pass them in any order. This is mostly a syntactic nicety, but can be useful, in combination with default arguments for functions that accept very many arguments. It is also a nice self-documenting feature.
>>> def do_greetings(greeting, person):
... print (greeting, "dear", person, "!")
...
>>> do_greetings(person="Jack", greeting="Good evening")
Good evening dear Jack !
In Python, you can even pass a dictionary in lieu of several named arguments for example, with do_greetingsas-is, imagine you have a dictionary like:
>>> my_param_dict = {"greeting":"Aloha", "person":"Alan"}
>>> do_greetings(**my_param_dict)
Aloha dear Alan !
In closing, and while the fancy ways of passing arguments, and the capability for methods to handle variable number of arguments are useful features of various languages, two key concepts need to be mentioned:
Argument passing convention : by value or by reference
So far all the functions we used didn't alter the value of the parameters passed to them. We can imagine however many instances when functions may want to do this, either to perform some conversion or computation on the said values, for its own internal use, or to effectively change the value of the variable so that the changes are reflected at the level of logic which called the function. That's where argument passing conventions come handy...
arguments which are passed by value may be altered by the function for its own internal computations but are not changed at the level of the calling method.
arguments which are passed by reference will reflect changes made to them, at the level of the calling method.
Each language specifies the ways that arguments are passed. A typical convention is to pass integers, numberic values and other basic types by value and to pass objects by reference. Most language also offer keyword that allow altering their default convention.
In python all arguments are passed by reference. However a few variables types are immutable (numbers, strings, tuples...) and they can therefore not be altered by the function.
Implicit "self" or "this" argument of class methods
In object oriented languages, methods (i.e. functions within a class) receive an extra argument that is the value of underlying object (the instance of the class), allowing the method to use various properties members of the class in its computation and/or to alter the value of some of these properties.
in Python, this argument is declared at the level of the method definition, but is passed implicitly. Being declared, it may be named most anything one wishes, although by convention this is typically called self.
>>> class Accumulator:
... def __init__(self, initialValue = 0):
... self.CurValue = initialValue
... def Add(self, x):
... self.CurValue += x
... return self.CurValue
...
>>> my_accu = Accumulator(10)
>>> my_accu.Add(5)
15
>>> my_accu.Add(3)
18

In that case for using arguments, it is simply a demo on how to use them, not the most effective perhaps as you demonstrated. Functions are very useful. for example if i wanted to add two numbers:
def add(num1, num2):
x = num1 + num2
return x
add(1,3)
Functions are useful for performing repetitive tasks, let's say in your example you had to say hello to hundreds of names, instead of having to do a loop of that raw_input() function to read their name and add some text to it you could simply call a function to perform the task and pass arguments (the persons name to it).
Per your second question, arguments are just variables passed to the function, so whatever variable you pass to it from the outside, for example I pass numbers 1 and 3 to my function add on the inside of that function they are simply referred to as num1 num2.
In your case with passing too many arguments would yield this:
>>> add(1,2)
3
>>> add(1,2,3)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: add() takes exactly 2 arguments (3 given)
>>>
Best of luck! and feel free to shoot me an email if you need further help (sbrichards (at) mit.edu)

The stuff in the parentheses are called arguments. Basically these are variables that you want the function to work with. For example, say you have a function, and you want it to print a word when you call it. With arguments, you can define what that word will be. Here is an example:
def hi(word):
print word
now, if I do something like this:
hi('Hello!')
it will print:
'Hello!'
hi() gets passed 'Hello!' as a variable called word, and then it prints that word.

In your example they are not used.
If your function needs to behave differently depending on what arguments you give it, then what's arguments are for.
def hi_name(name):
print 'Hi ' + name
hi_name("John doe")
This prints "Hi John Doe".
Now back to the basics about functions.

An argument is a special variable that exists only in that function.
In your example you have a function that takes 2 arguments:
def add(num1,num2):
x = num1 + num2
return x
When I call this function with add(), I have to add in the parentheses what I want num1 and num2 to be. In your case, you have 1 and 3, so you call it like this add(1,3).
What you're saying there is that you want to call add() and you want the first argument, num1 to be equal to 1, and the second argument, num2, to be equal to 3.

def main(a, b):
print(a)
print(b)
main(3, 5)
This is a basic example of a function with parameters, check for more information here.
output:
3
5

Functions would be useless if you can't give them information they should handle.
Arguments are such information.
def GiveMeANumberAndIDuplicateIt(x):
return x * 2
def DontGiveMeAnythingAtAll():
return None

does python 2.5 have an equivalent to Tcl's uplevel command?

Does python have an equivalent to Tcl's uplevel command? For those who don't know, the "uplevel" command lets you run code in the context of the caller. Here's how it might look in python:
def foo():
answer = 0
print "answer is", answer # should print 0
bar()
print "answer is", answer # should print 42
def bar():
uplevel("answer = 42")
It's more than just setting variables, however, so I'm not looking for a solution that merely alters a dictionary. I want to be able to execute any code.

In general, what you ask is not possible (with the results you no doubt expect). E.g., imagine the "any code" is x = 23. Will this add a new variable x to your caller's set of local variables, assuming you do find a black-magical way to execute this code "in the caller"? No it won't -- the crucial optimization performed by the Python compiler is to define once and for all, when def executes, the exact set of local variables (all the barenames that get assigned, or otherwise bound, in the function's body), and turn every access and setting to those barenames into very fast indexing into the stackframe. (You could systematically defeat that crucial optimization e.g. by having an exec '' at the start of every possible caller -- and see your system's performance crash through the floor in consequence).
Except for assigning to the caller's local barenames, exec thecode in thelocals, theglobals may do roughly what you want, and the inspect module lets you get the locals and globals of the caller in a semi-reasonable way (in as far as deep black magic -- which would make me go postal on any coworker suggesting it be perpetrated in production code -- can ever be honored with the undeserved praise of calling it "semi-reasonable", that is;-).
But you do specify "I want to be able to execute any code." and the only solution to that unambiguous specification (and thanks for being so precise, as it makes answering easier!) is: then, use a different programming language.

Is the third party library written in Python? If yes, you could rewrite and rebind the function "foo" at runtime with your own implementation. Like so:
import third_party
original_foo = third_party.foo
def my_foo(*args, **kwds):
# do your magic...
original_foo(*args, **kwds)
third_party.foo = my_foo
I guess monkey-patching is slighly better than rewriting frame locals. ;)

How to avoid excessive parameter passing?

I am developing a medium size program in python spread across 5 modules. The program accepts command line arguments using OptionParser in the main module e.g. main.py. These options are later used to determine how methods in other modules behave (e.g. a.py, b.py). As I extend the ability for the user to customise the behaviour or the program I find that I end up requiring this user-defined parameter in a method in a.py that is not directly called by main.py, but is instead called by another method in a.py:
main.py:
import a
p = some_command_line_argument_value
a.meth1(p)
a.py:
meth1(p):
# some code
res = meth2(p)
# some more code w/ res
meth2(p):
# do something with p
This excessive parameter passing seems wasteful and wrong, but has hard as I try I cannot think of a design pattern that solves this problem. While I had some formal CS education (minor in CS during my B.Sc.), I've only really come to appreciate good coding practices since I started using python. Please help me become a better programmer!

Create objects of types relevant to your program, and store the command line options relevant to each in them. Example:
import WidgetFrobnosticator
f = WidgetFrobnosticator()
f.allow_oncave_widgets = option_allow_concave_widgets
f.respect_weasel_pins = option_respect_weasel_pins
# Now the methods of WidgetFrobnosticator have access to your command-line parameters,
# in a way that's not dependent on the input format.
import PlatypusFactory
p = PlatypusFactory()
p.allow_parthenogenesis = option_allow_parthenogenesis
p.max_population = option_max_population
# The platypus factory knows about its own options, but not those of the WidgetFrobnosticator
# or vice versa. This makes each class easier to read and implement.

Maybe you should organize your code more into classes and objects? As I was writing this, Jimmy showed a class-instance based answer, so here is a pure class-based answer. This would be most useful if you only ever wanted a single behavior; if there is any chance at all you might want different defaults some of the time, you should use ordinary object-oriented programming in Python, i.e. pass around class instances with the property p set in the instance, not the class.
class Aclass(object):
p = None
#classmethod
def init_p(cls, value):
p = value
#classmethod
def meth1(cls):
# some code
res = cls.meth2()
# some more code w/ res
#classmethod
def meth2(cls):
# do something with p
pass
from a import Aclass as ac
ac.init_p(some_command_line_argument_value)
ac.meth1()
ac.meth2()

If "a" is a real object and not just a set of independent helper methods, you can create an "p" member variable in "a" and set it when you instantiate an "a" object. Then your main class will not need to pass "p" into meth1 and meth2 once "a" has been instantiated.

[Caution: my answer isn't specific to python.]
I remember that Code Complete called this kind of parameter a "tramp parameter". Googling for "tramp parameter" doesn't return many results, however.
Some alternatives to tramp parameters might include:
Put the data in a global variable
Put the data in a static variable of a class (similar to global data)
Put the data in an instance variable of a class
Pseudo-global variable: hidden behind a singleton, or some dependency injection mechanism
Personally, I don't mind a tramp parameter as long as there's no more than one; i.e. your example is OK for me, but I wouldn't like ...
import a
p1 = some_command_line_argument_value
p2 = another_command_line_argument_value
p3 = a_further_command_line_argument_value
a.meth1(p1, p2, p3)
... instead I'd prefer ...
import a
p = several_command_line_argument_values
a.meth1(p)
... because if meth2 decides that it wants more data than before, I'd prefer if it could extract this extra data from the original parameter which it's already being passed, so that I don't need to edit meth1.

With objects, parameter lists should normally be very small, since most appropriate information is a property of the object itself. The standard way to handle this is to configure the object properties and then call the appropriate methods of that object. In this case set p as an attribute of a. Your meth2 should also complain if p is not set.

Your example is reminiscent of the code smell Message Chains. You may find the corresponding refactoring, Hide Delegate, informative.