It is an order of magnitude slower and not less memory efficient. Also, for me it is never easier to understand what is going on when named tuples are used ins

It is an order of magnitude slower and not less memory efficient. Also, for me it is never easier to understand what is going on when named tuples are used instead of dicts Proof: def make_dicts(): res = [] for i in range(1000000): res.append({'x': i, 'y': i}) return res def make_tuples(): templ = namedtuple('Point', ('x', 'y')) res = [] for i in range(1000000): res.append(templ(i, i)) return res from ipython_memory_usage import ipython_memory_usage as imu imu.start_watching_memory() used 0.2305 MiB RAM in 4.00s, peaked 0.00 MiB above current, total RAM usage 86.41 MiB %time tuples = make_tuples() CPU times: user 780 ms, sys: 32 ms, total: 812 ms Wall time: 816 ms used 109.0625 MiB RAM in 0.92s, peaked 0.00 MiB above current, total RAM usage 195.47 MiB %time dicts = make_dicts() CPU times: user 160 ms, sys: 32 ms, total: 192 ms Wall time: 194 ms used 99.5117 MiB RAM in 0.30s, peaked 0.00 MiB above current, total RAM usage 524.33 MiB