Cycle duration is a critical variable for many iterative processes like software development. The faster you can cycle, the faster you can process new information or let your natural flow of thoughts proceed. Slow cycles can limit efficiency because it stalls the flow of thoughts and produces idle time. This idle time is often too small of a chunk to be usable for something else productively.
So we propably want to minimize our cycle time. How do we do it? One very simple approach is to measure the time you spend on using specific tools in your iteration cycle. Then we try to minimize this time.
If you include all relevant tools in the cycle and assume that they are executed sequentially, you end up with a time sum T. T represents the optimal cycle duration currently achievable using your tools.
For instance, a programmer will propably run her compiler and linker (and possibly further targets in her build system) in every cycle and the necessary time for running these can very well (for larger projects) dominate the total cycle duration.
pyinterval helps you to measure the time spent in specific tools by offering you a simple client-server-application. The server runs locally on your machine and simply handles a sequence of events. The client is meant to be used for instrumenting your tools.
alias make='pyinterval_instrument "make $*"'
TODO