Implementing a decorator for thread synchronisation.
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Using multithreading in Python applications? Interested in complex use cases for decorators and context managers? This talk will describe how the Java programming language "synchronized" keyword, for handling synchronisation in multithread applications, can be implemented in Python.
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Implementing a decorator for thread synchronisation.
- 1. Implementing a decorator for thread synchronisation Graham Dumpleton Graham.Dumpleton@gmail.com @GrahamDumpleton
- 2. Parallel execution using threads Create threads Wait to finish Task to run
- 3. Manipulating a counter value Aiya!!!
- 4. Synchronisation using a lock Hooray Acquire lock
- 6. Can we achieve this in Python? Decorator
- 7. Lock object required Need argument
- 8. Requires lock be a class attribute Create lock Locks across all classes :-(
- 9. Store lock as an instance attribute Create lock if necessary Argument for self in wrapper
- 10. Lock is automatically created No argument
- 11. Only works for instance methods
- 12. Switch to the wrapt decorator package
- 13. Basic decorator with wrapt
- 14. Implementing a universal decorator
- 15. Rewrite decorator using wrapt Choose context where lock created
- 16. Works on normal function Locked on function
- 17. Works on instance methods Locked on instance
- 18. Verify no lock on class Fails as expected
- 19. What about static methods? Locked on static method
- 20. And class methods? Not a dict
- 21. Extra trickery required Use our own lock Can't use setdefault()
- 22. Test class method again Locked on class
- 23. Verify no lock on class method Fails as expected
- 24. Calling both instance and class methods
- 25. Verify separate locks for instance and class Different Did not accidentally fall through to using lock on the class
- 26. Locking based on context used
- 27. Locking on code blocks in Java
- 28. Could we also do this? Use as a context manager
- 29. Type created by a decorator Function is replaced with instance of FunctionWrapper
- 30. What the decorator did Decorator is a fancy way of doing this
- 31. Rewrite to use function wrapper class Create lock if necessary Acquire lock Wrap function
- 32. Extend to be a context manager Release lock Acquire lock
- 33. Synchronise across instance methods Lock only for code where is required
- 34. Synchronise access to class attributes Supply class instead of the instance Can be used in synchronised instance method
- 35. Explicitly sharing a lock
- 36. Detecting a resource lock Detect when lock object has been passed Can use a simple decorator
- 37. What about context manager? Could just use lock itself but makes it look consistent
- 38. Wrap with callable object proxy Intercept when used as context manager
- 39. Not all necessary but looks nice
- 40. Reuse, don't reimplement Use it from wrapt
- 41. Don't write decorators from scratch either https://pypi.org/project/wrapt/ http://wrapt.readthedocs.org/ https://github.com/GrahamDumpleton/wrapt