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quadratic complexity

The in nums test is expensive, linear with the size of nums. It would be appropriate to keep a set() on the side, in order to more rapidly determine if we just rolled a duplicate number, if we want to produce significantly more than 10 distinct integers.

helper

Please do break out a def roll_distinct_ints() helper function. Leaving the logic at the module's top-level means that you, or a subsequent maintenance engineer who works on this project, cannot conveniently write automated unit tests for that functionality.

permutation

10 appears to be a "large" or "significant" fraction of 50. If that pattern holds when you scale up to a larger list, you might consider simply doing an assignment like

xs = list(range(50))

Then use the standard random.shuffle() library routine to produce a random permutation of the list. At that point you could conveniently slice off an xs[:10] result of the required size. By construction, both the original list and its permutation contain only distinct integers, satisfying your requirements.

f-string

 memory.append(str(str(a)+" <-- "+str(b)) +str(nums))

Prefer f"{a} <-- {b} {nums}".

dead store

Twice we conditionally assign null = 0. But nothing ever reads that variable, so just elide the relevant else: clauses.