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Anyway to get rid of `math.floor` for positive odd integers with `sympy.simplify`?

I'm trying to simplify some expressions of positive odd integers with sympy. But sympy refuses to expand floor, making the simplification hard to proceed.
To be specific, x is a positive odd integer (actually in my particular use case, the constraint is even stricter. But sympy can only do odd and positive, which is fine). x // 2 should be always equal to (x - 1) / 2. Example code here:
from sympy import Symbol, simplify
x = Symbol('x', odd=True, positive=True)
expr = x // 2 - (x - 1) / 2
print(simplify(expr))
prints -x/2 + floor(x/2) + 1/2. Ideally it should print 0.
What I've tried so far:
Simplify (x - 1) // 2 - (x - 1) / 2. Turns out to be 0.
Multiply the whole thing by 2: 2 * (x // 2 - (x - 1) / 2). Gives me: -x + 2*floor(x/2) + 1.
Try to put more weights on the FLOOR op by customizing the measure. No luck.
Use sympy.core.evaluate(False) context when creating the expression. Nuh.
Tune other parameters like ratio, rational, and play with other function like expand, factor, collect. Doesn't work either.
EDIT: Wolfram alpha can do this.
I tried to look like the assumptions of x along with some expressions. It surprises me that (x - 1) / 2).is_integer returns None, which means unknown.
I'm running out of clues. I'm even looking for alternativese of sympy. Any ideas guys?

I fail to see why sympy can't simplify that.
But, on another hand, I've discovered the existence of odd parameter just now, with your question.
What I would have done, without the knowledge of odd is
k = Symbol('k', positive=True, integer=True)
x = 2*k-1
expr = x // 2 - (x - 1) / 2
Then, expr is 0, without even the need to simplify.
So, can't say why you way doesn't work (and why that odd parameter exists if it is not used correctly to guess that x-1 is even, and therefore (x-1)/2 integer). But, in the meantime, my way of defining an odd integer x works.

There is some reluctance to make too much automatic in SymPy, but this seems like a case that could be addressed (since (x-1)/2 is simpler than floor(x/2). Until then, however, you can run a replacement on your expression which makes this transformation for you.
Let's define a preferred version of floor:
def _floor(x):
n, d = x.as_numer_denom()
if d == 2:
if n.is_odd:
return (n - 1)/2
if n.is_even:
return n/2
return floor(x)
When you have an expression with floor that you want to evaluate, replace floor with _floor:
>>> x = Symbol('x', odd=True)
>>> eq=x // 2 - (x - 1) / 2
>>> eq.replace(floor, _floor)
0

While solving a cubic equation, how do I divide a cubic polynomial by a linear one (Python 3)?

I'm making a solver of cubic equations in Python that includes division of polynomials.
from sympy import symbols
# Coefficients
a = int(input("1st coef: "))
b = int(input("2nd coef: "))
c = int(input("3rd coef: "))
d = int(input("Const: "))
# Polynomial of x
def P(x):
return a*x**3 + b*x**2 + c*x + d
x = symbols('x')
# Find 1 root by Cardano
R = (3*a*c - b**2) / (9*a**2)
Q = (3*b**3 - 9*a*b*c + 27*a**2*d) / (54*a**3)
Delta = R**3 + Q**2
y = (-Q + sqrt(Delta))**(1/3) + (-Q - sqrt(Delta))**(1/3)
x_1 = y - b/(3*a)
# Division
P(x) / (x - x_1) = p(x)
print(p(x)) # Just a placeholder
The program returns an error: "cannot assign to operator" and highlights the P(x) after the # Division comment (worded poorly, yes, but I'm from Russia so idc).
What I tried doing was to assign a variable to a polynomial and then dividing:
z = P(x)
w = x - x_1
p = z / w
print(p)
But alas: it just returns a plain old quotient (a = 1, b = 4, c = -9, d = -36):
(x**3 + 4*x**2 - 9*x - 36)/(x - 2.94254537742264)
Does anyone out here knows what to do in this situation (not to mention the non-exact value of x_1: the roots of x^3+4x^2-9x-36=0 are 3, -4, and -3, no floaty-irrational-messy-ugly things in sight)?
tl;dr: Polynomial division confusion and non-exact roots

I am not sure what exactly your question is but here is an attempt at an answer
The line
P(x) / (x - x_1) = p(x)
is problematic for multiple reasons. First of all it's important to know that the = operator in python (and a lot of other modern programming languages) is an assignment operator. You seem to come from more of a math background, so consider it to be something like the := operator. The direction of this is always fixed, i.e. with a = b you are always assigning the value of b to the variable a. In your case you are basically assigning an expression the value of p which does not make much sense:
Python can't assign anything to an expression (At least not as far as I know)
p(x) is not yet defined
The second problem is that you are mixing python functions with math functions.
A python function looks something like this:
def some_function(some_parameter)
print("Some important Thing!: ", some_parameter)
some_return_value = 42
return some_return_value
It (can) take some variable(s) as input, do a bunch of things with them, and then (can) return something else. They are generally called with the bracket operator (). I.e. some_function(42) translates to execute some_function and substitute the first parameter with the value 42. An expression in sympy however is as far as python is concerned just an object/variable.
So basically you could have just written P = a*x**3 + b*x**2 + c*x + d. What your P(x) function is doing is basically taking the expression a*x**3 + b*x**2 + c*x + d, substituting x for whatever you have put in the brackets, and then giving it back in as a sympy expression. (It's important to understand, that the x in your P python function has nothing to do with the x you define later! Because of that, one usually tries to avoid such "false friends" in coding)
Also, a math function in sympy is really just an expression formed from sympy symbols. As far as sympy is concerned, the return value of the P function is a (mathematical) function of the symbols a,b,c,d and the symbol you put into the brackets. This is why, whenever you want to integrate or differentiate, you will need to specify by which symbol to do that.
So the line should have looked something like this.
p = P(x) / (x - x_1)
Or you leave replace the P(x) function with P = a*x**3 + b*x**2 + c*x + d and end up with
p = P / (x - x_1)
Thirdly if you would like to have the expression simplified you should take a look here (https://docs.sympy.org/latest/tutorial/simplification.html). There are multiple ways here of simplifying expressions, depending on what sort of expression you want as a result. To make for faster code sympy will only simplify your expression if you specifically ask for it.
You might however be disappointed with the results, as the line
y = (-Q + sqrt(Delta))**(1/3) + (-Q - sqrt(Delta))**(1/3)
will do an implicit conversion to floating point numbers, and you are going to end up with rounding problems. To blame is the (1/3) part which will evaluate to 0.33333333 before ever seeing sympy. One possible fix for this would be
y = (-Q + sqrt(Delta))**(sympy.Rational(1,3)) + (-Q - sqrt(Delta))**(sympy.Rational(1,3))
(You might need to add import sympy at the top)
Generally, it might be worth learning a bit more about python. It's a language that mostly tries to get out of your way with annoying technical details. This unfortunately however also means that things can get very confusing when using libraries like sympy, that heavily rely on stuff like classes and operator overloading. Learning a bit more python might give you a better idea about what's going on under the hood, and might make the distinction between python stuff and sympy specific stuff easier. Basically, you want to make sure to read and understand this (https://docs.sympy.org/latest/gotchas.html).
Let me know if you have any questions, or need some resources :)

(Python) Solving an equation with an unknown number, find that number with an equation

I making a code (for fun and practice) to balance chemical equations. I want to try and balance N + A so it = Z
N = 2
A = 2
Z = 6
if N + A != Z:
print('X')
balancer = ???
The balancer should be 3 so that if I make an equation e.g (balancer x N) + A = Z it would be true. How would I make the balancer be three with out directly inputing it.
Thanks :)

You can to do the basic algebra by hand:
(balancer * N) + A = Z
(balancer * N) = Z - A # subtract A from both sides
balancer = (Z - A) / N # divide both sides by N
… and then it's trivial to turn that into code—that last line actually is the valid Python code, with no changes.
Or, if you want Python to do this for you, just by specifying (balancer * N) + A = Z as an equation… Python doesn't have anything built in to do that, but there are algebra libraries like SymPy to do.
You'll really want to work through the whole tutorial, but briefly…
First, you have to first tell it that your variables are variables:
>>> from sympy import symbols, solve, Eq
>>> A, N, Z, balancer = symbols('A N Z balancer')
Then, build an equation. The left side can just be (balancer * N) + a and Z, but you can't just put an = or == between them; you have to use Eq:
>>> equation = Eq((balancer * N) + A, Z)
Now you can substitute in the values for your variables:
>>> equation.subs(dict(N=2, A=2, Z=6))
Eq(2*balancer + 2, 6)
And finally, solve for valid solutions:
>>> solve(equation.subs(dict(N=2, A=2, Z=6))
[2]
Or, if you'd prefer to solve it algebraically and then substitute, instead of the other way around:
>>> solve(equation, 'balancer')
[(-A + Z)/N]
>>> [s.subs(dict(N=2, A=2, Z=6)) for s in solve(equation, 'balancer')]
[2]

You need a condition to test whether the left side, N + A, is greater than or less than than the right side, Z. You could use (N + A) - Z, yielding -2, which tells you that you're missing two atoms. From there you'll need to write some logic to determine which atoms it is that you're missing.
With simple variables pointing to integers, there's no way to intuitively predict which atoms you'll need to add. Presumably you're working from an equation, though, so I'd suggest you look into a regex solution to that parse that. Something like this:
>>> import re
>>> m = re.findall('(\d*)((?:[A-Z][a-z]?\d*)+)', '2CH4 + O2')
>>> for n, molecule in m:
... print(n or 1, molecule)
...
2 CH4
1 O2
And then parse the atoms similarly from there.

Comparing a Sympy expression with variable exponent to zero

I am wondering if there is a way to have SymPy recognize that expressions such as Pow(positive, variable) will always be greater than zero (assuming real numbers).
from sympy import *
init_session()
StictLessThan(0, 1) # returns desired output
>>> False
StrictLessThan(0, x) # returns desired output
>>> 0 < x
StrictLessThan(0, 2**x) # returns undesired output, but not surprising
>>> 0 < 2**x
(2**x).is_comparable # From this I assume that I would have to define my own function
>>> False
some_function(0, 2**x) # does this exist built into the SymPy package?
>>> True
I am aware that I can make my own function to do this, but I am curious as to the built-in capabilities and limitations of SymPy.
def is_positive_exponential(exponential):
base, exponent = exponential.as_base_exp()
return True if base > 0 else False

Consider that when x = pi*I/log(2) (a complex number), the expression 2**x evaluates to -1 which is not positive.
If you tell SymPy that x is a real number, it will know that 2**x is positive.
x = Symbol('x', real=True)
StrictLessThan(0, 2**x) # returns True
See the list of possible assumptions. By default, Symbol('x') is assumed "commutative" but nothing else is assumed about it.

What is this operator *= -1

I'm going through some Python activities and was given example code with this operator: y *= -1
I had a look through the relevant Python docs, to no avail.
I know y += 1, for example, is short for y = y + 1. So is this y = y * -1 y equals y times -1 maybe?
Closest thing in Python docs I could find is this: x * y: product of x and y
Is this it?

In the vast majority of the cases
y *= <expr>
is the same as
y = y * <expr>
but in the general case, it is interpreted as:
y = imul(y, <expr>)
which is then equivalent to:
y = y.__imul__(<expr>)
if y's type overrides __imul__.
This means that if y's type overrides the inplace multiplication operator, y*=<expr> is performed inplace, while y=y*<expr> is not.
EDIT
It might not be immediately clear why the assignment is needed, i.e. why it is intrepreted as y = imul(y, <expr>), and not just imul(y, <expr>).
The reason is that it makes a lot of sense for the following two scenarios to give the same result:
c = a * b
and
c = a
c *= b
Now, this of course works if a and b are of the same type (e.g. floats, numpy arrays, etc.), but if they aren't, it is possible for the result of the operation to have the type of b, in which case the operation cannot be an inplace operation of a, thus the result needs to be assigned to a, in order to achieve the correct behavior.
For example, this works, thanks to the assignment:
from numpy import arange
a = 2
a *= arange(3)
a
=> array([0, 2, 4])
Whereas if the assignment is dropped, a remains unchanged:
a = 2
imul(a, arange(3))
=> array([0, 2, 4])
a
=> 2

Yes that's correct. It just means multiply the left-hand value by negative the right-hand value. They're both arithmetic operators that differ simply by operation and expression binding, so I believe +/* are parallel everywhere else in overloads.
y = y * -1