For some reason Comic Sans did not make the cut: http://bancomicsans.com/main/.

Thus, the world primary energy consumption in 2010 was, according to the BP Energy report, 12,000 Mtoe / 476 quads / 15.9 TWyear / 576 EJ.

In less than 50 lines, you can have a short script that outputs the current horizontal coordinates/rise times of the different planets for a custom location. I have posted an example here.

Rare earths are not really that scarce, and in their case it is a combination of lack of concentrated ores and politics what limits their supply. The figure below shows the crustal abundance of the different naturally occurring elements, as taken from the Handbook of Chemistry and Physics. Other elements such as selenium or tellurium, key in thin film photovoltaics, are less abundant than rare earths.

The plot below shows the relative contribution of different sources to electricity generation by the electric power sector in 2009 and those predicted for 2035 by the reference model (no major changes). The renewable contribution would increase from 10% in 2009 to around 12.5% by 2035. A similar increase from 23 to 29% is predicted for end-use generation.

The reference case predicts a healthy annual growth of 13% for solar photovoltaic. However, since in 2009 the PV contribution to the electric power sector was a mere 40 million kWh  (compared to more than 2.5 trillion kWh from fossil fuels), the almost 50-fold increase in electricity generation from 2009 to 2035 barely makes a dent. Hydropower and wind get the lion’s share, accounting for 82% of the renewable generation in 2035. By that year, solar thermal and solar photovoltaic are predicted to contribute 0.5% and 0.2% to the renewable mixture.

Not surprisingly, most of the oil use goes to transportation, while coal and nuclear are mainly used for generating electricity.

I focused on creating an interface for a subset of python based on declarations. Both variables and functions (using the lambda statement) could be declared. Whenever a variable is assigned, all dependencies should automatically be updated. In a way, this is equivalent to constraining python to a sort of first order functional programming language with automatic recalculation. On top of it, because I wanted to do something useful with it, I allowed for import statements.

The key for having automatic recalculation is to create and update a dependency tree. The simplest implementation I thought of was using a dictionary that lists the dependencies for each variable. When a value is changed it triggers a traversal of the dependency tree. I used cmd for the command line interface, tokenize for extracting the tokens, verifying that the input is of the var = expr form and getting the variable name and its dependencies. The assignments are evaluated using exec() in its own execution context. The simplest version, without exception handling, takes less than 100 lines of code. You can have a look at it here.