This session will cover the challenges of creating a production application performance monitoring system for Python. It includes an overview of the architecture of the system, as well as how it hooks into Django and captures details about web transactions, database transactions, memcache requests, exceptions and much more.
This session provides a technical review of the challenges associated with instrumenting Python for production monitoring. How do you place monitoring hooks into code that cannot be modified directly in order to collect meaningful performance data? Concepts covered in this session will include:
The talk includes real-world examples of how these mechanisms have been used to add instrumentation to the Django web framework in order to collect actionable performance data.
Over the course of 6 years of Python development at NASA, Revsys, and Eldarion; Daniel Greenfeld has picked up a lot of easy tricks stolen from the best and brightest in the Python community that make him look good in front of his peers and clients. And now, at great risk to his career and reputation, he is going to show you how he does it.
Highlights:
by Issac Kelly
Inevitably you're going to run into somebody who wants to learn Django, or maybe both Python and Django. This talk will help you make it less painful for them.
20 months ago, Issac started learning Django and Python on his own. He got miserably stuck and did lots of things poorly. With a load of help from the community, 6 months later he was competent, and confident enough to use Django for his clients.
Later that year, his company hired it's first employee, who also, didn't previously know Python or Django, and this summer, they hired an intern... who knew some Python, and no Django.
Come see what we did to accelerate the process of going from 0 to $ in Django.
by Carl Meyer
Dependency management sucks. Pip provides some options for making it suck a bit less, but not all of them are immediately obvious. This talk will cover a number of strategies for making your deployments faster and more reliable, and demonstrate how to implement them in practice.
Areas we'll cover:
- Easy wins: requirements files, version-pinning, virtualenv, PyPI mirrors.
- One single point of failure is bad, multiple single points of failure are worse: kick your PyPI addiction with find-links, bundling sdists, "vendoring", or your own package index. We'll go over how each of these looks in a real project, and the tradeoffs with each.
This talk will assume basic knowledge of pip and requirements files; we'll be covering intermediate and advanced usage.
Love or hate them, the top python scraping libraries have some hidden gems and tricks that you can use to enhance, update and diversify your Django models. This talk will teach you more advanced techniques to aggregate content from RSS feeds, Twitter, Tumblr and normal old web sites for your Django projects.
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