大型python dict中的数据结构的性能损失

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当python dict存储元素过多时，无论是insert还是query都会体验到明显的性能下降（理论上是O(1)，实际上并不完全是）

原因大概是哈希碰撞：🔗 [Why can a Python dict have multiple keys with the same hash? - Stack Overflow] https://stackoverflow.com/questions/9010222/why-can-a-python-dict-have-multiple-keys-with-the-same-hash

性能下降的时机可能和dict存储的key的类型有关，（猜测）结构复杂的key更容易提前引发性能下降，和python dict的hash计算方式有关：🔗 [data structures - How are Python's Built In Dictionaries Implemented? - Stack Overflow] https://stackoverflow.com/questions/327311/how-are-pythons-built-in-dictionaries-implemented/9022835

写了个小程序验证，其中dict的key是这种格式的：

dict['1000->1001'] = value

实际验证下来，存储100万个元素时，query的速度下降了1～2倍。insert的速度应该也是更慢的，但就没写代码去测试了。