The moment a project fails

The moment you realize a project you have been developing does not deliver can take different forms. It might even be accidental. For me the reality check was a tall de carrers sign in the streets of Barcelona.

A keen and slow runner, in the last few months I have been developing a tool to crawl and keep up to date running events for RaceBase World. The project was a mix of AWS Lambda, Scrapy and Python, able to collect over 25K races around the world and keep them up to date. Not an easy task.

The goal was simple: sometime you are lucky enough to plan your holidays around a marathon abroad, possibly one of the largest events around the world.  More often you plan your vacations or business trips and then you simply wonder if there is a running event in the area.

I have now been in Barcelona for a few weeks, I have been looking for what I believed was an unlikely road race in summer and my lovely crawler could not find any. And Runner’s World Spain could not find one too. 

Still a sign on the door of the building where I live is telling me that up to 5 thousand runners are going to run in Barcelona next Sunday for la Cursa Barça. No better way to prove that my global database is inefficient.

You can of course try to collect million races worldwide, something that is very hard to achieve and will anyway generate too much noise for the end user. But having only a few thousand events globally will include only the large races (the ones a runner can find without any help from RaceBase World or any other website) and a few local random ones.

And the moment I cannot trust my own project to find a race, I can consider it a failure. But before working on a new idea or a new (local) approach to discover new races, it is time to join la Cursa Barça and forget Python.