JuliaPy / JuliaPy/PythonCall.jl
reducing allocations when checking python coroutines
- 主要語言
- Julia
- 星號
- 1.1k
- 分支
- 86
- 平均合併
- 1 天 22 小時
- 30 天內合併 PR
- 3
描述
If I do:
```julia
while !Bool(fut.done())
sleep(0.01)
end
```
where `fut` is a future created like:
```julia
aio = pyimport("asyncio")
coro = aio.sleep(1)
loop = aio.Runner().get_loop()
aio.run_coroutine_threadsafe(coro, loop)
```
It allocates linearly the more you sleep.
I tried using a global julia vector `[true]` and updating it in place when the future is done, but it doesn't reduce allocations that much, is there a better way?
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研究方向
No repository file or test is named. Reproduce the polling example using asyncio Future.done(), Runner().get_loop(), run_coroutine_threadsafe(), and Julia sleep(), then measure allocations. Done means finding a supported approach whose allocations do not grow linearly with repeated sleeps and documenting or testing that behavior.
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評估
- 技術堆疊
- julia, python
- 領域
- backend
- Issue 類型
- 缺陷
- 難度
- 3/5
- 預估耗時
- 1-2 天
- 活躍度
- 停滯
- 描述清晰度
- 需要釐清
- 新手友好度
- 35/100