Hello Montreal! PyCon 2014 underway!

So as many of you know I went to Montreal to attend PyCon 2014! As a up and coming “Pythonista,” this is very exciting. This is the first time I have travelled internationally, and also this is my first “major” conference! Looking to take in as much information as possible in these seven short days. Overall, Montreal is a great city. Everyone thus far is very nice, helpful, and understanding; despite my ability to speak the native tongue French. The weather is similar to that of Chicago, so not much to complain there 🙂

In terms of tutorials, I have attended the following thus far. I will give a title, a general overview, how I might apply it, and general reference links. I believe all the talks are recorded, I will share this as soon as I find out more information.

 

Topic: mrjob: Snakes on a Hadoop

Speaker: Jim Blomo

General Overview:

Essentially we walked through various examples, talking about MapReduce functions. We talked about how to orchestrate our logs in a manner that provides as much information in a single line vs multiple lines; Makes writing your jobs SO much easier. Essentially, Map and Reduce should be stateless; we are looking at an individual log line at a time, and the framework will merge values back together.

Essentially:

  • map(key1,value) -> list[key2,value2]
  • reduce(key2, list[value2]) -> list[value3]

We didn’t work with a direct Hadoop instance, but rather we worked in a simulated mode, where we had all the data locally. This was smart due to the possible instability of the wifi. (which if I might add has been kick ass! Great job PyCon team!) We worked through simple page visit MapReduce, to more complex multi step MapReduce jobs (get a list of users and their businesses reviewed, and convert it back to a match users together based on Jaccard Similarity). At the end, Jim talked about how to hook it up to a AWS instance of Hadoop and how to properly schedule your jobs. The nice advantage to AWS is that its easily scalable and takes a lot of the heavy lifting of getting Hadoop setup off your plate. Also if you need to spin up extra nodes, its just a nominal fee instead of having to possibly re architecture your own. Probably the biggest talk of the day for me because I am in a position to get more comfortable with Hadoop now. Before it just looked like a big scary elephant 🙂

Plan:

Now while I don’t have TB of data on my personal machine….there are tons of big data possibilities at work! Looking to see if I can take some of this back to the office, and write some MapReduce jobs on a lot of our data logs. With all this being said, the more efficient your logs are the better results you can get (or at least the easier it is to interpret). So I think this is going to become a bigger project soon. Glad I took this course. Very informative and broke the initial “scary” barrier of big data. BRING IT ON!

Links:

 

Topic: Build your own PiDoorbell!

Speakers: http://www.codechix.org/

General Overview:

In short, we took a Raspberry Pi (a small microcomputer) and wired it to a breadboard using the GPIO pins on the board. By doing this, we can have all sorts of fun with the circuits and program some cool things. We setup some sample led’s, but I finally got the Pi to snap this picture! 🙂

visitor-photo-2014:4:9-19:52

Plan:

So I plan on installing my PiDoorbell on my home’s door whenever someone gets closer than 24 inches away. This will allow me to snap and view a video stream of who is at the door before I get my lazy butt off my third floor apartment. (Remember, developers are supposed to be lazy ;)) The implementation in class only took a phone, and uploaded to Dropbox and set a SMS via Twilio. My plan is to tweak it to use the Google Drive API, and continue to get SMS or at least email alerts to my phone. This way, I can see when packages are delivered, or stolen O_O, even when I am not home. Long term, I want to add some way to interface with the person at the door; LED bar saying “I am on my way.” or “GO AWAY!” 🙂

Links:

 

Anyways that’s all I got for now! Looking forward to tomorrow’s tutorials on Flask and Intermediate Python! As always, learning all the time 🙂

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