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This appears to be the primary discussion: https://github.com/samuelcolvin/pydantic/issues/2678
But there are things you can do to even in Python. Without knowing much about your problem, you should look into https://github.com/jemalloc/jemalloc and using fork if you have large amounts of shared objects. All processes share the same memory content when you call fork, so provided you treat the shared data as read only, you shouldn't see an memory growth, and you can fork as many times as you have spare CPUs. jemalloc is a fancy malloc replacement that can reduce memory fragmentation and can help bring down memory usage.
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