# Python big integer vs. Julia big integer arithmetic

**URL:** <https://discourse.julialang.org/t/python-big-integer-vs-julia-big-integer-arithmetic/115777>\
**Category:** Performance\
**Tags:** python\
**Created:** [June 17, 2024, 9:39pm UTC](https://discourse.julialang.org/t/python-big-integer-vs-julia-big-integer-arithmetic/115777 "2024-06-17T21:39:43Z")\
**Posts on this page:** 1\
**Showing post:** 24

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**Author:** ![stevengj](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/stevengj/32/71_2.png) [@stevengj](https://discourse.julialang.org/u/stevengj)\
**Post date:** [June 19, 2024, 4:27pm UTC](https://discourse.julialang.org/t/python-big-integer-vs-julia-big-integer-arithmetic/115777/24 "2024-06-19T16:27:58Z")

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> [@oOosys](#):
>
> If I see it the right way **Julia could spawn Maxima on this one instead of itself to get the result faster** instead of calculating it by itself - or is there something wrong with this conclusion?

Spawning `julia` is slow, so **spawning Julia to do a _single_ small arithmetic calculation** will be inefficient. If that’s how you want to use Julia, you are better off with `bc`.

That’s not how other people typically use, Julia, however—or, for that matter, how they use most other programming languages, including Python. They spawn Julia (or whatever program) _once_ and then do lots of calculations. For this pattern, tools like `@btime` and `timeit` are more useful and revealing, because they measure the **marginal cost** of a single small operation.

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