Report of PyCon 2011 sessions.

2. 2010 attendance: ~1100 -> 2011 attendance: ~1500

4. Scientific Computing

5. Networking

6. System Administration

7. Rapid Prototyping

8. Systems Testing

10. Great documentation

11. Large standard lib

12. Tons of high quality 3rd party libraries

13. Useful collection of built-in data types

14. Cool features:

15. lambdas, list comprehensions, generators, properties, decorators

16. Avoids pitfalls of other dynamic languages:

17. Namespaced

18. Everything is an object

19. Strong typing with no implicit or explicit casting

20. Runtime error on undefined variables

22. Python 3.2 was released in February

23. Many 1st level dependencies have been ported to 3

24. Expect more rapid adoption as the number of 3rd party packages grows

25. PSF is providing funding for open source projects to port

27. 2.7 – 3.2

28. PyPy (the new hotness): Pure python implementation

29. Uses a JIT to get better performance than CPython

30. Supports 2.7

31. Jython: Python on JVM

32. Supports 2.5

33. IronPython: Python on CLR

34. Supports 2.7

36. Huge community

37. Reusable application modules

38. Runs on GAE

39. PostgreSQL, SQLite, and MySQL still popular database options

40. MongoDB and CouchDB are popular NoSQL options

41. Memcache or Varnish for caching

42. Apache with mod_wsgi for server

43. JSON for AJAX

44. Pip and virtualenv used for dependency management

46. Large scale parallelized simulations

47. 90% Python, computationally intensive parts in C or Fortran

48. File handling, process management, networking, gui, data visualization, testing

50. Write tasks in Python

51. Tasks are executed on local or remote slaves

52. Handle results asynchronously

53. Integrates with Django

54. mpi4py: Python interface for MPI

55. Used at Argonne National Laboratory on 100K node machine

56. MPI is still around

57. mrjob: Python interface to Hadoop

58. Write map/reduce functions in Python

61. Javascript for people who know Python

62. Supporting All Versions of Python All the Time with Tox

63. Linguistics of Twitter

64. Mrjob: Distributed Computing for Everyone

65. Extreme Network Programming with Python and Linux

66. Rapid Python used on Big Data to Discover Human Genetic Variation

67. Python for High Performance Computing

68. The Data Structures of Python

69. Documentation Driven Development

70. Genetic Programming in Python

71. Exhibition of Atrocity

72. API Design: Lessons Learned

73. What would you do with an ast?

74. Through the Side Channel: Timing and Implementation Attacks in Python

75. An outsider’s look at co-routines

76. Best Practices for Impossible Deadlines