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43 lines
1.2 KiB
Markdown
43 lines
1.2 KiB
Markdown
---
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title: "Quick Python: Concurrent Futures"
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date: 2020-04-11T20:40:28-04:00
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draft: false
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tags: ["Python"]
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medium_enabled: true
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---
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Another way to perform concurrency in python is to use the `concurrent.futures` module.
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```python
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from concurrent.futures import ThreadPoolExecutor, ProcessPoolExecutor
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def add(x, y):
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return x + y
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with ThreadPoolExecutor(max_workers=4) as executor:
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future = executor.submit(add, 1, 2)
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result = future.result(timeout=30) # unit: seconds
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```
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If `max_workers=None` then it will default to the number of processors on the machine multiplied by 5.
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If `timeout=None` then there is no time limit applied.
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You can also apply a function to a list or iterables
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```python
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def double(x):
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return 2 * x
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with ThreadPoolExecutor() as executor:
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future = executor.map(function_handle, [1, 2, 3])
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result = future.result()
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```
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Instead of threads, it is also possible to spawn processes to side-step the global interpreter lock. The documentation warns that only picklable objects can be executed and returned though.
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```python
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def add(x, y):
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return x + y
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with ProcessPoolExecutor() as executor:
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future = executor.submit(add, 1, 2)
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result = future.result()
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```
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