Sessions at PyCon US 2012 matching your filters

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Thursday 8th March 2012

  • High Performance Python I

    by Ian Ozsvald

    At EuroPython 2011 I ran a very hands-on tutorial for High Performance Python techniques. This updated tutorial will cover profiling, PyPy, Cython, numpy, NumExpr, ShedSkin, multiprocessing, ParallelPython and pyCUDA. Here's a 55 page PDF write-up of the EuroPython material: http://ianozsvald.com/2011/07/25...

    At EuroPython 2011 I ran a very hands-on tutorial for High Performance Python techniques. This updated tutorial will cover:

    • profiling with cProfile, run_snake and line_profiler
    • PyPy
    • Cython
    • numpy with and without vectors
    • NumExpr
    • ShedSkin Py->C++ compiler
    • multiprocessing for multi-core
    • ParallelPython for multi-machine
    • pyCUDA demos

    I plan to expand the original material and to maybe also cover other tools like execnet and PyPy-numpy.

    At 9:00am to 12:20pm, Thursday 8th March

    In D2, Santa Clara Convention Center

  • Optimize Performance and Scalability with Parallelism and Concurrency

    by Robert Hancock

    From how the operating system handles your requests through design principles on how to use concurrency and parallelism to optimize your program's performance and scalability. We will cover processes, threads, generators, coroutines, non-blocking IO, and the gevent library.

    How processes, threads, coroutines, and non-blocking IO work from the operating system through code implementation and design principles to optimize Python programs. The difference between parallelism and concurrency and when to use each.

    The premise is that to make an informed decision you need to know what is happening under the hood. Once you understand the low level functionality, you can make the correct decision in the design phase.

    The emphasis is on practical application to solve real world problems.


    • How the operating system handles traps and interrupts
    • Scheduling
    • Processes
    • Threads
    • The GIL
    • Generators
    • What is a coroutine?
    • What is a Python coroutine?
    • Blocking/Non-blocking I/O.
    • Parallelism versus Concurrency
    • How do these work with CPython, Pypy, and Stackless
    • Greenlets and libevent (gevent)
    • Design principles
    • Example networked application
    • Performance results
    • What are other the other options?

    At 9:00am to 12:20pm, Thursday 8th March

    In F2, Santa Clara Convention Center

Saturday 10th March 2012

  • Web Server Bottlenecks And Performance Tuning

    by Graham Dumpleton

    New Python web developers seem to love running benchmarks on WSGI servers. Reality is that they often have no idea what they are doing or what to look at. This talk will look at a range of factors which can influence the performance of your Python web application. This includes the impact of using threads vs processes, number of processors, memory available, the GIL and slow HTTP clients.

    A benchmark of a hello world application is often what developers use to make the all important decision of what web hosting infrastructure they use. Worse is that in many cases this is the only sort of performance testing or monitoring they will ever do. When it comes to their production applications they are usually flying blind and have no idea of how it is performing and what they need to do to tune their web application stack.

    This talk will discuss different limiting factors or bottlenecks within your WSGI server stack and system that can affect the performance of your Python web application. It will illustrate the impacts of these by looking at typical configurations for the more popular WSGI hosting mechanisms of Apache/mod_wsgi, gunicorn and uWSGI, seeing how they perform under various types of traffic and request loads and then tweaking the configurations to see whether they perform better or worse.

    Such factors that will be discussed will include:

    Use of threads vs processes.
    Number of processors available.
    Python global interpreter lock (GIL)
    Amount of memory available.
    Slow HTTP browsers/clients.
    Browser keep alive connections.
    Need to handle static assets.
    From this an attempt will be made to provide some general guidelines of what is a good configuration/architecture to use for different types of Python web applications. The importance of continuous production monitoring will also be covered to ensure that you know when the performance of your system is dropping off due to changing traffic patterns as well as code changes you have made in your actual web application.

    At 1:35pm to 2:15pm, Saturday 10th March

    In E4, Santa Clara Convention Center