OpenStack is an innovative open source project written in Python, backed by Rackspace Hosting and NASA, building a massively-scalable and reliable cloud computing platform.
The first part of this talk will clarify the place of OpenStack in the general "cloud" landscape and explain why a fully open cloud infrastructure stack is necessary to avoid vendor lock-in. We'll then focus on the OpenStack project goals, its developer community, its open design and release processes, and the developer tools it chose.
The second part of the talk will present into more technical details the different components of OpenStack: Nova (compute) and Swift (storage), including the Python libraries that are used (libvirt, SQLAlchemy, eventlet...). A Q&A session at the end of the talk will give the audience a chance to clear any remaining dark area.
The main problem with reports generated in Python is how to separate the content from the style using ReportLab library, because all informations should be saved in a single source file that, by example, is impossible to understand for your graphic designer.
So the solution: just modularizes all components you need and identify simple container formats for your data input (JSON) and document template (ReportLab RML).
Now with the power of Genshi and XInclude we will create dynamic templates that include specific snippets (e.g., to generate on the fly a decent graph with matplotlib or cairoplot to fill some lacks of ReportLab) and we will detach the stylesheet from the template structure.
And at the end you can also have the internationalization service in the PDF report generation!
Python is an accepted high-level scripting language with a growing community in academia and industry. It is used in a lot of scientific applications in many different scientific fields and in more and more industries, for example, in engineering or life science). In all fields, the use of Python for high-performance and parallel computing is increasing. Several organizations and companies are providing tools or support for Python development. This includes libraries for scientific computing, parallel computing, and MPI. Python is also used on many core architectures and GPUs, for which specific Python interpreters are being developed. A related topic is the performance of the various interpreter and compiler implementations for Python.
The talk gives an overview of Python’s use in HPC and Scientific Computing and gives information on many topics, such as Python on massively parallel systems, GPU programming with Python, scientific libraries in Python, and Python interpreter performance issues. The talk will include examples for scientific codes and applications from many domains.
The "sqlmap" is one of the largest, widely used and most active Python projects in the IT security community (more than 2000 commits in one year period with community of over 100 active testers). It combines it's developers' strong security knowledge together with analytical, mathematical and Python development skills to provide IT professionals with vibrant features.
Talk would be consisted of several parts: short introduction to project and developers, developing and testing environment, programming cycle, program's workflow, technologies used, common pitfalls and how we've circumvent them, usage of mathematical models, optimizations, project's future goals.
The significant part of this talk would be the immediate insight into the developing process of probably the world's most advanced open-source Python IT security project today.
Teaser for http://lanyrd.com/2011/europytho...
A pervasive elitism hovers in the background of collaborative software development: everyone secretly wants to be seen as a genius. I'll cover how to avoid this trap and gracefully exchange personal ego for personal growth and super-charged collaboration. I'll also examine how software tools affect social behaviors, and how to successfully manage the growth of new ideas.
20th–26th June 2011