asyncio-taskpool/usage/USAGE.md

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# Using `asyncio-taskpool`
## Simple example
The minimum required setup is a "worker" coroutine function that can do something asynchronously, a main coroutine function that sets up the `TaskPool` and starts/stops the tasks as desired, eventually awaiting them all.
The following demo code enables full log output first for additional clarity. It is complete and should work as is.
### Code
```python
import logging
import asyncio
from asyncio_taskpool.pool import TaskPool
logging.getLogger().setLevel(logging.NOTSET)
logging.getLogger('asyncio_taskpool').addHandler(logging.StreamHandler())
async def work(n: int) -> None:
"""
Pseudo-worker function.
Counts up to an integer with a second of sleep before each iteration.
In a real-world use case, a worker function should probably have access
to some synchronisation primitive or shared resource to distribute work
between an arbitrary number of workers.
"""
for i in range(n):
await asyncio.sleep(1)
print("did", i)
async def main() -> None:
pool = TaskPool(work, (5,)) # initializes the pool; no work is being done yet
pool.start(3) # launches work tasks 0, 1, and 2
await asyncio.sleep(1.5) # lets the tasks work for a bit
pool.start() # launches work task 3
await asyncio.sleep(1.5) # lets the tasks work for a bit
pool.stop(2) # cancels tasks 3 and 2
await pool.close() # awaits all tasks, then flushes the pool
if __name__ == '__main__':
asyncio.run(main())
```
### Output
Additional comments indicated with `<--`
```
Started work_pool_task_0
Started work_pool_task_1
Started work_pool_task_2
did 0
did 0
did 0
Started work_pool_task_3
did 1
did 1
did 1
did 0 <-- notice that the newly created task begins counting at 0
did 2
did 2 <-- two taks were stopped; only tasks 0 and 1 continue "working"
Cancelling work_pool_task_2 ...
Cancelled work_pool_task_2
Exiting work_pool_task_2
Cancelling work_pool_task_3 ...
Cancelled work_pool_task_3
Exiting work_pool_task_3
did 3
did 3
Exiting work_pool_task_0
Exiting work_pool_task_1
did 4
did 4
```
## Advanced example
...