# Path: formulaic/formula.py
# class Formula:
#     @classmethod
#     def from_spec(cls, spec, parser=None):
#         if isinstance(spec, Formula):
#             return spec
#         return cls(spec, parser=parser)
# 
#     def __init__(self, formula, parser=None):
#         parser = parser or FormulaParser()
#         if isinstance(formula, str):
#             terms = parser.get_terms(formula, sort=True)
#         elif isinstance(formula, (list, set)):
#             terms = [
#                 term
#                 for value in formula
#                 for term in (
#                     parser.get_terms(value, include_intercept=False)
#                     if isinstance(value, str)
#                     else [value]
#                 )
#             ]
#         elif isinstance(formula, tuple):
#             terms = tuple(
#                 Formula.from_spec(group, parser=parser).terms for group in formula
#             )
#         else:
#             raise FormulaInvalidError(
#                 f"Unrecognized formula specification: {repr(formula)}."
#             )
#         self.terms = terms
# 
#     @property
#     def terms(self):
#         return self._terms
# 
#     @terms.setter
#     def terms(self, terms):
#         self.__check_terms(terms)
#         self._terms = terms
# 
#     @classmethod
#     def __check_terms(cls, terms, depth=0):
#         if depth == 0 and isinstance(terms, tuple):
#             for termset in terms:
#                 cls.__check_terms(termset, depth=depth + 1)
#         else:
#             for term in terms:
#                 if not isinstance(term, Term):
#                     raise FormulaInvalidError(
#                         f"All terms in formula should be instances of `formulaic.parser.types.Term`; received term {repr(term)} of type `{type(term)}`."
#                     )
# 
#     def get_model_matrix(
#         self, data, context=None, materializer=None, ensure_full_rank=True, **kwargs
#     ):
#         if materializer is None:
#             materializer = FormulaMaterializer.for_data(data)
#         else:
#             materializer = FormulaMaterializer.for_materializer(materializer)
#         if not inspect.isclass(materializer) or not issubclass(
#             materializer, FormulaMaterializer
#         ):
#             raise FormulaMaterializerInvalidError(
#                 "Materializers must be subclasses of `formulaic.materializers.FormulaMaterializer`."
#             )
#         return materializer(data, context=context or {}).get_model_matrix(
#             self, ensure_full_rank=ensure_full_rank, **kwargs
#         )
# 
#     def differentiate(self, *vars, use_sympy=False):
#         return Formula(
#             [differentiate_term(term, vars, use_sympy=use_sympy) for term in self.terms]
#         )
# 
#     def __str__(self):
#         if isinstance(self.terms, tuple):
#             return " ~ ".join(
#                 " + ".join(str(term) for term in terms) for terms in self._terms
#             )
#         return " + ".join(str(term) for term in self.terms)
# 
#     def __eq__(self, other):
#         if isinstance(other, Formula):
#             return self.terms == other.terms
#         return NotImplemented
# 
#     def __repr__(self):
#         return str(self)


from collections import OrderedDict
from formulaic import Formula
import pytest
import pandas


class TestModelSpec:
    @pytest.fixture
    def data(self):
        return pandas.DataFrame(
            {
                "A": ["a", "b", "c"],
                "a": [0, 0, 1],
            }
        )

    @pytest.fixture
    def data2(self):
        return pandas.DataFrame(
            {
                "A": ["a", "a", "a"],
                "a": [0, 0, 1],
            }
        )

    @pytest.fixture
    def formula(self):
        return Formula("a + A + a:A")

    @pytest.fixture
    def model_spec(self, formula, data):
        return formula.get_model_matrix(data).model_spec

    def test_attributes(self, model_spec):

# Path: formulaic/formula.py
# class Formula:
#     @classmethod
#     def from_spec(cls, spec, parser=None):
#         if isinstance(spec, Formula):
#             return spec
#         return cls(spec, parser=parser)
# 
#     def __init__(self, formula, parser=None):
#         parser = parser or FormulaParser()
#         if isinstance(formula, str):
#             terms = parser.get_terms(formula, sort=True)
#         elif isinstance(formula, (list, set)):
#             terms = [
#                 term
#                 for value in formula
#                 for term in (
#                     parser.get_terms(value, include_intercept=False)
#                     if isinstance(value, str)
#                     else [value]
#                 )
#             ]
#         elif isinstance(formula, tuple):
#             terms = tuple(
#                 Formula.from_spec(group, parser=parser).terms for group in formula
#             )
#         else:
#             raise FormulaInvalidError(
#                 f"Unrecognized formula specification: {repr(formula)}."
#             )
#         self.terms = terms
# 
#     @property
#     def terms(self):
#         return self._terms
# 
#     @terms.setter
#     def terms(self, terms):
#         self.__check_terms(terms)
#         self._terms = terms
# 
#     @classmethod
#     def __check_terms(cls, terms, depth=0):
#         if depth == 0 and isinstance(terms, tuple):
#             for termset in terms:
#                 cls.__check_terms(termset, depth=depth + 1)
#         else:
#             for term in terms:
#                 if not isinstance(term, Term):
#                     raise FormulaInvalidError(
#                         f"All terms in formula should be instances of `formulaic.parser.types.Term`; received term {repr(term)} of type `{type(term)}`."
#                     )
# 
#     def get_model_matrix(
#         self, data, context=None, materializer=None, ensure_full_rank=True, **kwargs
#     ):
#         if materializer is None:
#             materializer = FormulaMaterializer.for_data(data)
#         else:
#             materializer = FormulaMaterializer.for_materializer(materializer)
#         if not inspect.isclass(materializer) or not issubclass(
#             materializer, FormulaMaterializer
#         ):
#             raise FormulaMaterializerInvalidError(
#                 "Materializers must be subclasses of `formulaic.materializers.FormulaMaterializer`."
#             )
#         return materializer(data, context=context or {}).get_model_matrix(
#             self, ensure_full_rank=ensure_full_rank, **kwargs
#         )
# 
#     def differentiate(self, *vars, use_sympy=False):
#         return Formula(
#             [differentiate_term(term, vars, use_sympy=use_sympy) for term in self.terms]
#         )
# 
#     def __str__(self):
#         if isinstance(self.terms, tuple):
#             return " ~ ".join(
#                 " + ".join(str(term) for term in terms) for terms in self._terms
#             )
#         return " + ".join(str(term) for term in self.terms)
# 
#     def __eq__(self, other):
#         if isinstance(other, Formula):
#             return self.terms == other.terms
#         return NotImplemented
# 
#     def __repr__(self):
#         return str(self)


# Path: tests/test_model_spec.py
from collections import OrderedDict
from formulaic import Formula
import pytest
import pandas



class TestModelSpec:
    @pytest.fixture
    def data(self):
        return pandas.DataFrame(
            {
                "A": ["a", "b", "c"],
                "a": [0, 0, 1],
            }
        )

    @pytest.fixture
    def data2(self):
        return pandas.DataFrame(
            {
                "A": ["a", "a", "a"],
                "a": [0, 0, 1],
            }
        )

    @pytest.fixture
    def formula(self):
        return Formula("a + A + a:A")

    @pytest.fixture
    def model_spec(self, formula, data):
        return formula.get_model_matrix(data).model_spec

    def test_attributes(self, model_spec):

        assert model_spec.formula == Formula("a + A + a:A")