Pycon 2011
- 2. 2010 attendance: ~1100 -> 2011 attendance: ~1500
- 3. Many sponsorsPyCon 2011Python UniverseWeb Development
- 5. Networking
- 9. This talk focuses on the web development and sciencey aspects of Python PyCon 2011Why Use Python?Elegant and concise syntax
- 11. Large standard lib
- 12. Tons of high quality 3rd party libraries
- 13. Useful collection of built-in data types
- 15. lambdas, list comprehensions, generators, properties, decorators
- 17. Namespaced
- 18. Everything is an object
- 19. Strong typing with no implicit or explicit casting
- 20. Runtime error on undefined variables
- 21. Error handling is consistent: runtime errors are always exceptionsPyCon 2011Python 2 vs 3Python 2.7 is last version in 2 branch (for now…)
- 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
- 26. 2 branch is still standard for application developmentPyCon 2011Interpreter (VM) StatusCPython: Reference implementation
- 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
- 35. Possibly losing support for MicrosoftPyCon 2011Web DevelopmentDjango is becoming the de-facto standard for Python web development
- 36. Huge community
- 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
- 45. Celery plugin used for executing background tasksPyCon 2011Scientific ComputingBiology, physics, chemistry
- 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
- 49. Rapid prototyping of scientific algorithms and statistical computationsPyCon 2011Parallel ComputingCelery: distributed job queue
- 50. Write tasks in Python
- 51. Tasks are executed on local or remote slaves
- 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
- 59. Submit jobs to Amazon Elastic MapReducePyCon 2011SessionsSession videos online at blip.tv (hopefully a less crappy site soon…)
- 60. Session descriptions at PyCon siteSessions I attended:Distributed Tasks with Celery
- 61. Javascript for people who know Python
- 62. Supporting All Versions of Python All the Time with Tox
- 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
- 70. Genetic Programming in Python
- 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