Pycon 2012 What Python can learn from Java
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Python can learn from Java's approach to concurrency, garbage collection, and collections. Java offers more optimized and specialized collection types than Python for performance-critical applications. It also provides better tools for profiling, debugging, and managing shared mutable state in a concurrent environment without relying on global interpreter locks. While rewriting core Python functionality in C is challenging, projects like PyPy and RPython show promise in growing Python into a more performant and "growable" language like Java.
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![The GIL
✤ The GIL offers negligible help writing concurrent code
✤ Consider this trivial race condition:
if d[k] == v1:
d[k] = v2](https://image.slidesharecdn.com/pycon2012whatjavacanlearnfrompython-120314092357-phpapp01/85/Pycon-2012-What-Python-can-learn-from-Java-23-320.jpg)
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Artificial Intelligence is rapidly integrating into every aspect of technology. While the neural processing unit (NPU) often receives the majority of the spotlight as the ultimate AI problem solver, it is essential to recognize that not all AI workloads can be efficiently executed on an NPU and that neural network architectures are evolving rapidly. To create efficient chips and systems with market longevity, designers must plan for diverse AI workloads that include networks yet to be invented.
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Pycon 2012 What Python can learn from Java
- 1. What Python can learn from Java Jonathan Ellis / @spyced Pycon 2012
- 3. (Not a web development perspective)
- 4. The power of tools
- 5. Remote debugging ✤ -Xdebug -Xrunjdwp:transport=dt_socket,server=y,suspend=n,address=1044 ✤ 11 steps: “(6) install Wing IDE on the machine on which you plan to run your debug program... (8) copy wingdbstub.py into the same directory as your source files and import it in your Python source ... (10) In wingdbstub.py on your debug host, set kWingHostPort ... try setting kLogFile variable in wingdbstub.py for log additional diagnostic information.”
- 6. JMX
- 7. Triton
- 9. GC in a nutshell ✤ Mark ✤ Sweep ✤ Compact
- 10. Aside: reference counting ✤ Only good when allocation + assignment are relatively infrequent operations
- 11. In short ✤ Python has a terrible GC story ✤ Poor instrumentation makes it worse
- 13. Runtime profiling ✤ https://github.com/foursquare/heapaudit ✤ https://github.com/mariusaeriksen/heapster ✤ Commercial: AppDynamics, DynaTrace, others
- 14. Building blocks ✤ -javaagent ✤ ASM: http://asm.ow2.org/
- 16. Collections ✤ Less one-size-fits-all the more you care about performance ✤ HashMap ✤ ImmutableMap ✤ ImmutableSortedMap ✤ TreeMap ✤ ConcurrentSkipListMap ✤ ConcurrentLinkedHashMap ✤ SnapTreeMap ✤ NonBlockingHashMap ✤ Not to mention BiMap, Multimap, ...
- 17. Lists? ✤ ArrayList ✤ CopyOnWriteArrayList ✤ ArrayBlockingDeque ✤ LinkedBlockingDeque ✤ PriorityQueue, PriorityBlockingQueue ✤ SynchronousQueue ✤ TransferQueue (Java7)
- 18. Where are these in Python? ✤ Python developers want to write Python, not C ✤ Similar question: “Why not Cassandra in Python?” ✤ PyPy to the rescue? ✤ RPython extension methods
- 19. Growing a language (1998) ✤ Guy Steele: “I should not design a small language, and I should not design a large one. I need to design a language that can grow.” ✤ http://www.cs.virginia.edu/~evans/cs655/readings/steele.pdf ✤ Currently, Python is not a growable language
- 20. Concurrency ✤ ExecutorService, ThreadPoolExecutor ✤ FutureTask ✤ Also: ScheduledThreadPoolExecutor ✤ ForkJoinPool
- 21. Concurrency ✤ For CPU-bound applications, copies are the enemy ✤ Useful but dangerous: ✤ List.subList, NavigableMap.subMap ✤ Corollary: you need to support threads + shared state ✤ Twisted ✤ Actor model ✤ Multi-process + sysv ✤ Local and remote computation: one size does not fit all
- 22. Copies are bad ✤ Copies of large things are especially bad ✤ Remember fragmentation? ✤ Iterators (generators) are good ✤ Java: ByteBuffer ✤ Python: memoryview
- 23. The GIL ✤ The GIL offers negligible help writing concurrent code ✤ Consider this trivial race condition: if d[k] == v1: d[k] = v2
- 24. More subtle problems ✤ Which of these is threadsafe? ✤ L.append(x) ✤ x = x + 1 ✤ x += 1
- 25. More subtle problems ✤ Which of these is threadsafe? ✤ L.append(x) ✤ x = x + 1 ✤ x += 1 ✤ “The thread safety of python operations depends on the compilation of python statements into byte-codes, which is an implementation detail and should not be relied upon.”
- 26. Are we stuck with explicit locks? ✤ ConcurrentMap ✤ boolean replace(key, oldValue, newValue) ✤ NonBlockingHashMap ✤ BlockingQueue ✤ CopyOnWriteArrayList
- 27. Shared state good, Mutable state bad ✤ final: most under-appreciated language feature? ✤ guava: Immutable collections ✤ http://code.google.com/p/guava-libraries/ ✤ Persistent collections ✤ (More accurately, “What Python can learn from Haskell”) ✤ http://code.google.com/p/pcollections/ ✤ SnapTreeMap
- 28. Final thoughts ✤ JRuby is the most advanced Ruby implementation ✤ Jython is less popular, but I’d rather write Java than C ✤ Once you can write Python libraries that rival native ones for speed, things will get much more interesting