Statsmodels seasonal_decompose - what is naive about it?
I made some (aehm...naive) researches, and, according to the reference, it seems that StatsModels uses the classic moving average method to detect trends and apply seasonal decomposition (you can check more here, specifically about Moving Average and Classical Decomposition).
However, other advanced seasonal decomposition techniques are available, such as STL decomposition, which also has some Python implementations. (UPDATE - 11/04/2019 as pointed out in the comments by @squarespiral, such implementations appear to have been merged in the master branch of StatsModels).
At the above links, you can find a complete reference on the advantages and disadvantages of each one of the proposed methods.
Hope it helps!