Generate sample coordinates inside a Polygon
Style Nitpicks

Put spaces after commas / Keep Lines within 120 Chars

poly = Polygon([(141.4378366,-25.95915986), (165.4279876,-29.43400298), (163.1382942,-47.65345814), (133.1675418,-42.99807751)])


becomes

poly = Polygon([(141.4378366, -25.95915986), (165.4279876, -29.43400298), (163.1382942, -47.65345814),
                (133.1675418, -42.99807751)])


Use Pythonic Underscores

minx, miny, maxx, maxy = poly.bounds 


becomes

min_x, min_y, max_x, max_y = poly.bounds


Eschew Semicolons (Personal Opinion)

You can use semicolons like this:

longs = np.arange(minx, maxx, 0.002); lats = np.arange(miny, maxy, 0.002)


But personally, I just wouldn't in Python. Eww.

An Alternative Algorithm

EDIT: Having read @MrE's and @MartinR's comments, I now propose this rejection sampling method. Although, this could miss frequently in a polygon with a large bounding box relative to its area; .e.g. an 8-point Christmas star with a small inner circle. 

def random_points_within(poly, num_points):
    min_x, min_y, max_x, max_y = poly.bounds

    points = []

    while len(points) &lt; num_points:
        random_point = Point([random.uniform(min_x, max_x), random.uniform(min_y, max_y)])
        if (random_point.within(poly)):
            points.append(random_point)

    return points


Another alternative that never misses, but may not be well distributed.

This was my original idea, but it didn't look so good in the morning.

Firstly, work out how to select one point within a polygon.

def random_point_within(poly):
    min_x, min_y, max_x, max_y = poly.bounds

    x = random.uniform(min_x, max_x)
    x_line = LineString([(x, min_y), (x, max_y)])
    x_line_intercept_min, x_line_intercept_max = x_line.intersection(poly).xy[1].tolist()
    y = random.uniform(x_line_intercept_min, x_line_intercept_max)

    return Point([x, y])


Then simply call that in a list comprehension to generate however many points you desire.

points = [random_point_within(poly) for i in range(5)]
checks = [point.within(poly) for point in points]


My approach is to select x randomly within the polygon, then constrain y. 

This approach doesn't require NumPy and always produces a point within the polygon.