Earlier this month, I had the opportunity to attend PyCon — the annual conference for the Python programming language, held in Santa Clara, California.
PyCon aims to be different from other major IT conferences by keeping a strong focus on community, and accessibility to that community. The admission fee to PyCon is only a small fraction of what other conferences charge — allowing virtually anyone to attend. On top of the our rooms of scheduled speakers, organizers offered several reserved rooms that could be used for attendees to create their own ad hoc talk or meeting at any time of the day (or night).
I met a wide variety of people at the conference, from students still in school and recent graduates working their first job, to entrepreneurs eager to talk about their startups and IT veterans. Their job backgrounds were just as diverse: non-profits, government, start-ups, and corporate employees. This illustrates just how flexible a programming language and tool Python is.
The PyCon sessions were split into two groups: talks related to the Python programming language itself, and how to actually use and applying Python in different fields. As a systems administrator — although familiar with programming — I was more interested in the latter discussions. From this group, topics included standard and real-time web applications, databases, message queuing, data analysis, and robotics.
The topic I found most impressive was data analysis. Python has a large suite of tools that both novice and expert programmers can use to analyze various data sets. For example, Philadelphia-based geographer Dana Bauer, and Jacqueline Kazil of the US Library of Congress, described how Python can be used to analyze government open data sets.
Later on, Maksim Tsvetovat and Alex Kouznetsov, authors of “Social Network Analysis for Startups”, gave this talk on how to do basic social analysis with Python. During the session, they demonstrated how Twitter users, such as Darth Vader, are proving to be just as influential as official outlets such as CNN when it comes to spreading news, as they discovered by parsing and analyzing a data set of tweets related to a recent earthquake.
Unfortunately, some sessions did not go as well as planned. I attended one talk on using coroutines to create a real-time web-based chat application. The author of the core Python module that was to be used during this session had just released a new version prior to the session, which broke all of the example code that was to be used. The result was 90 minutes of apologies and scrambling to get something working on the fly. This served as a good example of how, even though Open Source software is used for brand new technologies, it can still be unstable and volatile.
My week at PyCon was exhausting but enjoyable. It was impossible for me to attend every talk — even all of the ones I was most interested in — but fortunately, I have been able to catch up on them all on the PyCon site.
I could have stayed home and waited until the videos were published publicly, but by attending PyCon, I was able to see first-hand how diverse the language and community is. Python and its programmers are at the forefront of web and cloud development as well as data analysis, and I am excited to see what will come next.