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-# `mdpoly` Multidimensional Polynomials
-
-Work in progress!
-
-## Quick Start
-
-There is still a big part of the API missing but the snipped below works enough
-to give an overview.
-
-```python
-from mdpoly import State, Variable, Parameter
-from mdpoly.representations import SparseRepr
-
-# Construct an expression
-x, y = Variable.from_names("x, y") # or just Variable("x")
-k = Parameter("k")
-
-p = (x + 2 * y) ** 3 + y ** 2 + k
-print(f"{p = }")
-
-# Make a concrete representation
-state = State(parameters={k: 3.14}) # try to replace with empty dict
-sparse, state = p.to_repr(SparseRepr, state)
-
-# Look inside the representation
-for entry in sparse.entries():
-    print(f"at (row, col) = {entry.row, entry.col} there is a polynomial:")
-    for term in sparse.terms(entry):
-        monomial_str = ""
-        for idx in term:
-            var = state.from_index(idx.var_idx)
-            monomial_str += f"{var.name}^{idx.power} "
-
-        # Get the coefficient
-        coeff = sparse.at(entry, term)
-        print(" - the monomial", monomial_str, "has coefficient", coeff)
-
-# You can also simply iterate over it
-for entry, term, coeff in sparse:
-    print(entry, term, coeff)
-```
-
-There is some advanced stuff that is still broken but the idea is that it will
-work soon (TM)
-
-```
-from mdpoly import Variable, MatrixVariable
-from mdpoly.types import Shape
-
-x = Variable("x")
-V = MatrixVariable("Q", Shape.column(3))
-
-print(x.shape, V.shape)
-
-z = x + V # error
-scalar = V.T @ V # no error (TODO)
-```