Sound static analyses for static programming languages such as C and Java are now widespread. The sound and precise analysis of increasingly popular dynamic programming languages like JavaScript and Python remains a challenge. This work studies the variation of static analyses of Python – in precision, time and memory usage – by adapting independent parameters: (i) the value sensitivity, (ii) the allocation sensitivity and (iii) the activation of an abstract garbage collector. It is not clear yet, for these languages, which level of sensitivity constitutes a sweet spot in terms of precision versus efficiency to achieve a meaningful analysis. We thus perform an experimental evaluation using a prototype static analyzer, on benchmarks a few thousand lines long.