How to use the geopandas.array.from_shapely function in geopandas

sg.LineString([(0, 0), (1, 1)]), None, sg.LineString([(1, 1), (2, 2)])
    ])

    gp_rings = gp.array.from_shapely([
        sg.LineString([(0, 0), (1, 1), (0, 0)]),
        None,
        sg.LineString([(1, 1), (2, 2), (1, 1)]),
    ])

    gp_multilines = gp.array.from_shapely([
        None,
        sg.MultiLineString([[(0, 0), (1, 1)]]),
        sg.MultiLineString([[(1, 1), (2, 2)]])
    ])

    gp_polygons = gp.array.from_shapely([
        None,
        sg.Polygon([(0, 0), (1, 1), (0, 1)]),
        sg.Polygon([(1, 1), (2, 2), (1, 0)])
    ])

    gp_multipolygons = gp.array.from_shapely([
        sg.MultiPolygon([sg.Polygon([(0, 0), (1, 1), (0, 1)])]),
        sg.MultiPolygon([sg.Polygon([(1, 1), (2, 2), (1, 0)])]),
        None
    ])

    gpdf = gp.GeoDataFrame({
        'a': [1, 2, 3],
        'point': gp_points,
        'b': [3, 4, 5],
        'line': gp_lines,

def test_drop_geometry_column():
    gp_points = gp.array.from_shapely([
        sg.Point([0, 0]), sg.Point(1, 1)
    ])

    gp_lines = gp.array.from_shapely([
        sg.LineString([(0, 0), (1, 1)]), sg.LineString([(1, 1), (2, 2)])
    ])

    gpdf = gp.GeoDataFrame({
        'a': [1, 2],
        'point': gp_points,
        'b': [3, 4],
        'line1': gp_lines,
        'line2': gp_lines
    }, geometry='line2')

    # Import with no geometry column set

def st_point_array(draw, min_size=0, max_size=30, geoseries=False):
    n = draw(st.integers(min_size, max_size))
    points = []
    for i in range(n):
        x_mid = draw(st.floats(-50, 50))
        y_mid = draw(st.floats(-50, 50))
        point = (np.random.rand(2) - 0.5) * 5
        point[0] = point[0] + x_mid
        point[1] = point[1] + y_mid
        points.append(sg.Point(point))

    result = from_shapely(points)
    if geoseries:
        result = GeoSeries(result)
    return result

def test_import_geopandas_with_none():
    # Construct geopandas dataframe with column for each geometry type that includes
    # Nones
    gp_points = gp.array.from_shapely([
        sg.Point([0, 0]), sg.Point(1, 1), None
    ])

    gp_lines = gp.array.from_shapely([
        sg.LineString([(0, 0), (1, 1)]), None, sg.LineString([(1, 1), (2, 2)])
    ])

    gp_rings = gp.array.from_shapely([
        sg.LineString([(0, 0), (1, 1), (0, 0)]),
        None,
        sg.LineString([(1, 1), (2, 2), (1, 1)]),
    ])

    gp_multilines = gp.array.from_shapely([
        None,
        sg.MultiLineString([[(0, 0), (1, 1)]]),
        sg.MultiLineString([[(1, 1), (2, 2)]])
    ])

    gp_polygons = gp.array.from_shapely([
        None,
        sg.Polygon([(0, 0), (1, 1), (0, 1)]),
        sg.Polygon([(1, 1), (2, 2), (1, 0)])
    ])

def test_import_geopandas_with_none():
    # Construct geopandas dataframe with column for each geometry type that includes
    # Nones
    gp_points = gp.array.from_shapely([
        sg.Point([0, 0]), sg.Point(1, 1), None
    ])

    gp_lines = gp.array.from_shapely([
        sg.LineString([(0, 0), (1, 1)]), None, sg.LineString([(1, 1), (2, 2)])
    ])

    gp_rings = gp.array.from_shapely([
        sg.LineString([(0, 0), (1, 1), (0, 0)]),
        None,
        sg.LineString([(1, 1), (2, 2), (1, 1)]),
    ])

    gp_multilines = gp.array.from_shapely([
        None,
        sg.MultiLineString([[(0, 0), (1, 1)]]),
        sg.MultiLineString([[(1, 1), (2, 2)]])
    ])

    gp_polygons = gp.array.from_shapely([

def _ensure_geometry(data):
    """
    Ensure the data is of geometry dtype or converted to it.

    If input is a (Geo)Series, output is a GeoSeries, otherwise output
    is GeometryArray.
    """
    if is_geometry_type(data):
        if isinstance(data, Series):
            return GeoSeries(data)
        return data
    else:
        if isinstance(data, Series):
            out = from_shapely(np.asarray(data))
            return GeoSeries(out, index=data.index, name=data.name)
        else:
            out = from_shapely(data)
            return out

# if data is None and dtype is specified (eg from empty overlay
            # test), specifying dtype raises an error:
            # https://github.com/pandas-dev/pandas/issues/26469
            kwargs.pop("dtype", None)
            # Use Series constructor to handle input data
            s = pd.Series(data, index=index, name=name, **kwargs)
            # prevent trying to convert non-geometry objects
            if s.dtype != object:
                if s.empty:
                    s = s.astype(object)
                else:
                    warnings.warn(_SERIES_WARNING_MSG, FutureWarning, stacklevel=2)
                    return s
            # try to convert to GeometryArray, if fails return plain Series
            try:
                data = from_shapely(s.values)
            except TypeError:
                warnings.warn(_SERIES_WARNING_MSG, FutureWarning, stacklevel=2)
                return s
            index = s.index
            name = s.name

        self = super(GeoSeries, cls).__new__(cls)
        super(GeoSeries, self).__init__(data, index=index, name=name, **kwargs)
        self.crs = crs
        self._invalidate_sindex()
        return self

"""
    Ensure the data is of geometry dtype or converted to it.

    If input is a (Geo)Series, output is a GeoSeries, otherwise output
    is GeometryArray.
    """
    if is_geometry_type(data):
        if isinstance(data, Series):
            return GeoSeries(data)
        return data
    else:
        if isinstance(data, Series):
            out = from_shapely(np.asarray(data))
            return GeoSeries(out, index=data.index, name=data.name)
        else:
            out = from_shapely(data)
            return out

def to_geopandas(self):
        """
        Convert a spatialpandas geometry array into a geopandas GeometryArray

        Returns:
            geopandas GeometryArray
        """
        from geopandas.array import from_shapely
        return from_shapely([el.to_shapely() for el in self])