When dealing with geospatial data it is sometimes useful to have a grid at hand that represents the given data. One way to create a grid like this is to use GeoHashes. GeoHashes are a hierarchical spatial data structure which subdivides space into buckets of grid shape, which is one of the many applications of what is known as a Z-order curve, and generally space-filling curves. A geohash is an encoded character string that is computed from geographic coordinates.
After three great days at the PyCon US 2017 in Portland, OR Hendrik and I decided to participate in the development sprints succeeding the conferece. The code sprints are an essential part of PyCon, and a chance to meet some of the maintainers and contributors of various open source projects. For us it was the first time attending a code sprint. The day before the sprint there was a session helping people to set up Git, Python (including virtual environments) and getting familiar with version control.
The first step of my plan, building a Raspberry Pi based photovoltaic monitoring solution, is finished. I created a python package that works with the Kostal Piko 5.5 inverter (and theoretically should work with other Kostal inverters as well) and offers a clean interface for accessing the data: import pikopy #create a new piko instance p = Piko('host', 'username', 'password') #get current power print p.get_current_power() #get voltage from string 1 print p.
A couple of years ago I was on a trip to Budapest with a couple of friends. While roaming the streets we were passing by a casino and my friend insisted that there was a perfect strategy that would only lead to winning at roulette tables. Curious as I was I had him explain his theory. The system basically works as follows: First, you place a coin on red. If red wins, take your winning and start over.