The conference provided a great opportunity to learn about the various ways Python is used in scientific applications. As a newcomer to this field, I was overwhelmed by the diverse and incredibly active Open Source community. Several of the conference attendees had new and innovative ways to incorporate Python into their work, and I spent the majority of the breaks and lunches learning about the impressive accomplishments of my fellow conference attendees.Even more exciting than the tutorials were the presentations held on the final two days of the conference. While all were interesting and informative, my personal favorite was the NetworkX presentation. NetworkX is tool that analyzes networks by manipulating basic graph and data structures, and performing numerous computations on the analyses. One of the applications of NetworkX is the prediction of disease outbreaks, and since I am a total epidemiology geek, I was fascinated.Furthermore, several members of the Pygr project were on hand that week, which provided an ample opportunity for the project team to discuss the successes of my summer project, review code, and plan for the future. It was wonderful to finally put faces to names, and my Google Summer of Code project was presented to the group. As I am the least skilled member of the Pygr clan, I benefited tremendously from observing my fellow developers demonstrate and explain the most efficient ways to improve and utilize Pygr. I plan to continue working on Pygr despite the conclusion of my project, and the sprint helped me to find tasks to focus on in the future.While SciPy has long been over, the conference had an unexpected impact on me. Once school started back up, as my research advisor assigned me a new bioinformatics computing project, which clearly needs some NumPy love. Luckily, I’ve had just the introduction I need to dive right in!