def _get_space()

in gym3/libenv.py [0:0]
41 lines of code
10 McCabe index (conditional complexity)

    def _get_space(self, c_name: Any) -> Tuple[types.DictType, List[Spec]]:
        """
        Get a c space and convert to a gym space
        """
        count = self._c_lib.libenv_get_tensortypes(self._c_env, c_name, self._ffi.NULL)
        if count == 0:
            return types.DictType(), []

        c_tensortypes = self._ffi.new("struct libenv_tensortype[%d]" % count)
        self._c_lib.libenv_get_tensortypes(self._c_env, c_name, c_tensortypes)

        # convert to gym3 types
        name_to_tensortype = {}
        specs = []
        for i in range(count):
            c_tt = c_tensortypes[i]

            name = self._ffi.string(c_tt.name).decode("utf8")
            shape = tuple(c_tt.shape[j] for j in range(c_tt.ndim))

            if c_tt.scalar_type == self._c_lib.LIBENV_SCALAR_TYPE_REAL:
                if c_tt.dtype == self._c_lib.LIBENV_DTYPE_FLOAT32:
                    dtype = np.dtype("float32")
                    low = c_tt.low.float32
                    high = c_tt.high.float32
                else:
                    assert False, "unrecognized dtype for real"
                tensortype = types.TensorType(eltype=types.Real(), shape=shape)
            elif c_tt.scalar_type == self._c_lib.LIBENV_SCALAR_TYPE_DISCRETE:
                if c_tt.dtype == self._c_lib.LIBENV_DTYPE_UINT8:
                    dtype = np.dtype("uint8")
                    low = c_tt.low.uint8
                    high = c_tt.high.uint8
                elif c_tt.dtype == self._c_lib.LIBENV_DTYPE_INT32:
                    dtype = np.dtype("int32")
                    low = c_tt.low.int32
                    high = c_tt.high.int32
                else:
                    assert False, "unrecognized dtype for discrete"
                assert low == 0 and high >= 0, "discrete low/high bounds are incorrect"
                tensortype = types.TensorType(
                    eltype=types.Discrete(n=high + 1, dtype_name=dtype.name),
                    shape=shape,
                )
            else:
                assert False, "unknown space type"
            name_to_tensortype[name] = tensortype
            specs.append(Spec(name=name, shape=tensortype.shape, dtype=dtype))
        return types.DictType(**name_to_tensortype), specs