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How to create a repeating loop in python with sympy, without changing one variable in the loop

so basically I have encountered a problem where I have made my loop, but since one of the variables is defined before the actual assignment, the code stops working. the code.
Another thing is that I'm working in Spyder, and I don't know why, but if I try to code so that the program collect variables initially (which is essential for this purpose), the program encounters an internal issue. Any ideas on how to ask for user input in Spyder?
Thanks to everyone in advance
Basically, what I want this to do is to differentiate functions, and the with these derivatives create a maclaurin series. When the actual error ((r-j)/r) is smaller than the stopping variable s, I want the program to stop and display the result, but I don't know what is wrong.
The second thing I want to achieve is to get to know how to gain input from the user in the program.

So, here is, in text form, your code (sorry, plagiarism argument is not valid around here)
q = sympy.Function('q')
q = sympy.diff(f)
def main():
a = sympy.Function('a')
a = sympy.diff(q)
j = sympy.function
j = 1+(1/sympy.factorial(count))*q
r = sympy.Function('r')
r = j+(1/sympy.factorial(count+1))*a
if ((r-j)/r)>s:
count = count + 1
q = sympy.diff(a)
j = r+(1/sympy.factorial(count))*q
r = j+(1/sympy.factorial(count+1))*a
main()
else:
print(f"Answer{r}")
In the middle of an obviously very confused code, and even more confused situation with that "plagiarism" stuff (don't worry, if you have a working code at the end of your effort, there is no way it will look similar enough to your original to be detected as plagiarism because I've posted it here:D) there is actually a good question, and I remember that I while ago I had to scratch my head to understand what was happening in a similar situation.
The problem you have here, is that you can't compute sympy.diff(q) in main function, before assigning something to q in that same function later.
Because of the line q = sympy.diff(a) that you have later, q has to be a local variable (unless you say otherwise, see later). That's default behavior in python: a variable that you assign in a function is a local variable.
But because you are reading this variable before, in the previous line (the one that triggers the error) a = sympy.diff(q), then python has a problem: the local variable a doesn't exist yet.
Without the future q = sympy.diff(a), q would have been "read-only" inside main, and python would have done what you probably expect: read the global variable q.
So, your real problem is not really that line. Your real problem is the line q = sympy.diff(a).
Because even without the current error, that line would not do what you expect it to do. You probably expect it to alter q so that in the subsequent recursive call of main, q has this new value for now on. Not to create a local value q, and have the next call of main start over with the global value of q.
You have several options here.
One would be to declare q has global. Just add line global q at the beginning of your main, and q is now the global variable.
A cleaner way would be to pass q as an argument to main.
Note that you'll have probably the same problem with count. You should also either declare it as global, or, neater way, pass it to main.
Note also that this would solve only syntax errors (well, not even all. j=sympy.function is meaningless for example). But there are many other errors here. The least serious being your strange habit to create a Function and immediately delete it by overwriting it by another function or expression.

Python, Explain Return Within a Function, (Amateur Programmer)

I am an amateur Python coder learning in school. We recently went over functions and did some work at home. I am confused on the point/meaning of the return statement. Our goal was to simply turn a letter into its ASCII counter part using ord(). My code works as intended however what is the use of the return statement, and how can it be used in this situation to take this function further?
Letter = input("What is your letter? ")
def ordfunction ( x ):
x=ord(x)
print(x)
return[x]
ordfunction(Letter) x

Whenever we write a function it perform some task, on basis of execution it provide some result. Now we have lot of options to use this result.
One we can print/display that result on console. for which we use print to show o/p. Here is use:-
Letter = input("What is your letter? ")
def ordfunction ( x ):
x=ord(x)
print(x)
ordfunction(Letter)
So it will display output on console apart from this it dosn't perform any things. We can use this output to store in a file or send on any device.
Further other way is to use return to provide result of function. Here we can hold this value to use further in any kind of calculation like:-
Letter = input("What is your letter? ")
def ordfunction ( x ):
x=ord(x)
return x
a = ordfunction(Letter)
print (a+100)
So return with provide use result of execution to use it further throughout program.
Further you can refer:-
Why would you use the return statement in Python?

There are basically two things that a method/function can do: change some kind of state or give the caller some kind of information.
For example, if you write something to the console, you've changed something about the system state. This is sometimes called a side effect.
The second thing a method can do is give its caller some kind of information. return is a way to pass data back to the caller - it's the "result" of the method. (In many programming languages, you can also use it to exit a method immediately, but that's a different topic).
Think about a common function: 2 + 3. Most people aren't used to thinking of + as a function, but it is. (If it helps, you can think of this as plus(2, 3)). In this case, the plus function "returns" five - that's the result of the operation, the information you were looking for when you "called" it to begin with.
Hopefully, this clarifies things a little bit - if not please feel free to comment and I can edit.

Quoting definition of a math function:
In mathematics, a function is a relation between a set of inputs and a
set of permissible outputs with the property that each input is
related to exactly one output.
In short, the return is the output. Think about a math function f(x) = x + 100.
x is the input
x + 100 is the implementation of the function
The return is the output of the function, which is the result of x + 100
Equivalent python function:
def f_of_x(x):
result = x + 100
return result

Return is your answer to one statement; example: is it raining? Yes, it's raining
Your answer is returned to your question.
Simple

I also had trouble understanding the difference between return and print. After you return a function you should:
print(ordfunction(Letter))
To see your function. Print is just made for humans to see what is going on. We usually don't need the print function.

Alternative to exec

I'm currently trying to code a Python (3.4.4) GUI with tkinter which should allow to fit an arbitrary function to some datapoints. To start easy, I'd like to create some input-function and evaluate it. Later, I would like to plot and fit it using curve_fit from scipy.
In order to do so, I would like to create a dynamic (fitting) function from a user-input-string. I found and read about exec, but people say that (1) it is not safe to use and (2) there is always a better alternative (e.g. here and in many other places). So, I was wondering what would be the alternative in this case?
Here is some example code with two nested functions which works but it's not dynamic:
def buttonfit_press():
def f(x):
return x+1
return f
print(buttonfit_press()(4))
And here is some code that gives rise to NameError: name 'f' is not defined before I can even start to use xval:
def buttonfit_press2(xval):
actfitfunc = "f(x)=x+1"
execstr = "def {}:\n return {}\n".format(actfitfunc.split("=")[0], actfitfunc.split("=")[1])
exec(execstr)
return f
print(buttonfit_press2(4))
An alternative approach with types.FunctionType discussed here (10303248) wasn't successful either...
So, my question is: Is there a good alternative I could use for this scenario? Or if not, how can I make the code with exec run?
I hope it's understandable and not too vague. Thanks in advance for your ideas and input.
#Gábor Erdős:
Either I don't understand or I disagree. If I code the same segment in the mainloop, it recognizes f and I can execute the code segment from execstr:
actfitfunc = "f(x)=x+1"
execstr = "def {}:\n return {}\n".format(actfitfunc.split("=")[0], actfitfunc.split("=")[1])
exec(execstr)
print(f(4))
>>> 5
#Łukasz Rogalski:
Printing execstr seems fine to me:
def f(x):
return x+1
Indentation error is unlikely due to my editor, but I double-checked - it's fine.
Introducing my_locals, calling it in exec and printing in afterwards shows:
{'f': <function f at 0x000000000348D8C8>}
However, I still get NameError: name 'f' is not defined.
#user3691475:
Your example is very similar to my first example. But this is not "dynamic" in my understanding, i.e. one can not change the output of the function while the code is running.
#Dunes:
I think this is going in the right direction, thanks. However, I don't understand yet how I can evaluate and use this function in the next step? What I mean is: in order to be able to fit it, I have to extract fitting variables (i.e. a in f(x)=a*x+b) or evaluate the function at various x-values (i.e. print(f(3.14))).

The problem with exec/eval, is that they can execute arbitrary code. So to use exec or eval you need to either carefully parse the code fragment to ensure it doesn't contain malicious code (an incredibly hard task), or be sure that the source of the code can be trusted. If you're making a small program for personal use then that's fine. A big program that's responsible for sensitive data or money, definitely not. It would seem your use case counts as having a trusted source.
If all you want is to create an arbitrary function at runtime, then just use a combination of the lambda expression and eval. eg.
func_str = "lambda x: x + 1" # equates to f(x)=x+1
func = eval(func_str)
assert func(4) == 5
The reason why your attempt isn't working is that locals(), in the context of a function, creates a copy of the local namespace. Mutations to the resulting dictionary do not effect the current local namespace. You would need to do something like:
def g():
src = """
def f(x):
return x + 1
"""
exec_namespace = {} # exec will place the function f in this dictionary
exec(src, exec_namespace)
return exec_namespace['f'] # retrieve f

I'm not sure what exactly are you trying to do, i.e. what functions are allowed, what operations are permitted, etc.
Here is an example of a function generator with one dynamic parameter:
>>> def generator(n):
def f(x):
return x+n
return f
>>> plus_one=generator(1)
>>> print(plus_one(4))
5

Is it pointless to receive a parameter/argument and do nothing with it?

I'm learning python from a textbook. This code is for the game Tic-Tac-Toe.
The full source code for the problem:
http://pastebin.com/Tf4KQpnk
The following function confuses me:
def human_move(board, human):
""" Get human move."""
legal = legal_moves(board)
move = None
while move not in legal:
move = ask_number("Where will you move? (0 - 8): ", 0, NUM_SQUARES)
if move not in legal: print "\nThat square is already taken. Choose another.\n"
print "Fine..."
return move
I do not know why the function receives 'human' parameter. It appears to do nothing with it.
def human_move(board, human):
How would I know to send 'human' to this function if I were to write this game from scratch? Because I can't see why it is sent to this function if it isn't used or returned.

The answer: it depends. In your example it seems useless to me, but I haven't checked it in depth.
If you create a function to be used only from your code, it is in fact useless.
def calculate_money(bank_name, my_dog_name):
return Bank(bank_name).money
money = calculate_money('Deutsche bank', 'Ralph')
But if you are working with some kind of API/Contract, the callbacks you specify might accept arguments that are not needed for a certain implementation, but for some others, are necessary.
For instance, imagine that the following function is used in some kind of framework, and you want the framework to show a pop up when the operation is finished. It could look something like this:
def my_cool_callback(names, accounts, context):
# do something blablab
context.show_message('operation finished')
But what if you don't really need the context object in your callback? you have to speficy it anyway for the signature to match... You can't call it pointless because that parameter is used sometimes.
EDIT
Another situation in which it could be useful, would be to loop through a list of functions that have almost the same signature. In that case could be ok also to have extra arguments as "garbage placeholders". Let's say all your functions need 3 arguments in general, but one needs only 2.

Can I be warned when I used a generator function by accident

I was working with generator functions and private functions of a class. I am wondering
Why when yielding (which in my one case was by accident) in __someFunc that this function just appears not to be called from within __someGenerator. Also what is the terminology I want to use when referring to these aspects of the language?
Can the python interpreter warn of such instances?
Below is an example snippet of my scenario.
class someClass():
def __init__(self):
pass
#Copy and paste mistake where yield ended up in a regular function
def __someFunc(self):
print "hello"
#yield True #if yielding in this function it isn't called
def __someGenerator (self):
for i in range(0, 10):
self.__someFunc()
yield True
yield False
def someMethod(self):
func = self.__someGenerator()
while func.next():
print "next"
sc = someClass()
sc.someMethod()
I got burned on this and spent some time trying to figure out why a function just wasn't getting called. I finally discovered I was yielding in function I didn't want to in.

A "generator" isn't so much a language feature, as a name for functions that "yield." Yielding is pretty much always legal. There's not really any way for Python to know that you didn't "mean" to yield from some function.
This PEP http://www.python.org/dev/peps/pep-0255/ talks about generators, and may help you understand the background better.
I sympathize with your experience, but compilers can't figure out what you "meant for them to do", only what you actually told them to do.

I'll try to answer the first of your questions.
A regular function, when called like this:
val = func()
executes its inside statements until it ends or a return statement is reached. Then the return value of the function is assigned to val.
If a compiler recognizes the function to actually be a generator and not a regular function (it does that by looking for yield statements inside the function -- if there's at least one, it's a generator), the scenario when calling it the same way as above has different consequences. Upon calling func(), no code inside the function is executed, and a special <generator> value is assigned to val. Then, the first time you call val.next(), the actual statements of func are being executed until a yield or return is encountered, upon which the execution of the function stops, value yielded is returned and generator waits for another call to val.next().
That's why, in your example, function __someFunc didn't print "hello" -- its statements were not executed, because you haven't called self.__someFunc().next(), but only self.__someFunc().
Unfortunately, I'm pretty sure there's no built-in warning mechanism for programming errors like yours.

Python doesn't know whether you want to create a generator object for later iteration or call a function. But python isn't your only tool for seeing what's going on with your code. If you're using an editor or IDE that allows customized syntax highlighting, you can tell it to give the yield keyword a different color, or even a bright background, which will help you find your errors more quickly, at least. In vim, for example, you might do:
:syntax keyword Yield yield
:highlight yield ctermbg=yellow guibg=yellow ctermfg=blue guifg=blue
Those are horrendous colors, by the way. I recommend picking something better. Another option, if your editor or IDE won't cooperate, is to set up a custom rule in a code checker like pylint. An example from pylint's source tarball:
from pylint.interfaces import IRawChecker
from pylint.checkers import BaseChecker
class MyRawChecker(BaseChecker):
"""check for line continuations with '\' instead of using triple
quoted string or parenthesis
"""
__implements__ = IRawChecker
name = 'custom_raw'
msgs = {'W9901': ('use \\ for line continuation',
('Used when a \\ is used for a line continuation instead'
' of using triple quoted string or parenthesis.')),
}
options = ()
def process_module(self, stream):
"""process a module
the module's content is accessible via the stream object
"""
for (lineno, line) in enumerate(stream):
if line.rstrip().endswith('\\'):
self.add_message('W9901', line=lineno)
def register(linter):
"""required method to auto register this checker"""
linter.register_checker(MyRawChecker(linter))
The pylint manual is available here: http://www.logilab.org/card/pylint_manual
And vim's syntax documentation is here: http://www.vim.org/htmldoc/syntax.html

Because the return keyword is applicable in both generator functions and regular functions, there's nothing you could possibly check (as #Christopher mentions). The return keyword in a generator indicates that a StopIteration exception should be raised.
If you try to return with a value from within a generator (which doesn't make sense, since return just means "stop iteration"), the compiler will complain at compile-time -- this may catch some copy-and-paste mistakes:
>>> def foo():
... yield 12
... return 15
...
File "<stdin>", line 3
SyntaxError: 'return' with argument inside generator
I personally just advise against copy and paste programming. :-)
From the PEP:
Note that return means "I'm done, and have nothing interesting to
return", for both generator functions and non-generator functions.

We do this.
Generators have names with "generate" or "gen" in their name. It will have a yield statement in the body. Pretty easy to check visually, since no method is much over 20 lines of code.
Other methods don't have "gen" in their name.
Also, we do not every use __ (double underscore) names under any circumstances. 32,000 lines of code. Non __ names.
The "generator vs. non-generator" method function is entirely a design question. What did the programmer "intend" to happen. The compiler can't easily validate your intent, it can only validate what you actually typed.