Moderately colossal roadside somewhat adjacent koala

trippler at PyConAU

I was thrilled to be back for my second PyCon AU – with a wonderfully diverse and inclusive group of technologists – presenting on trippler in a talk titled An EV Trip Planner for Australia.

I got a great feedback, including a suggestion to incorporate the many very (but not uniquely) Australian BIG things we might encounter on road trips. As per the product framework I shared in the talk, the main question to resolve here is the viability of sourcing the data!

Watch the out the video of the talk in the 2025 PyCon AU playlist. Below I’ve also included the outline, drawn from existing electric vehicle posts.

Outline

Context

Define the problem

  • Optimal plans assume one best plan, robust, accurate data, and perfect execution in an environment of abundance
  • Resilient plans assume many good-enough plans, sensitive, messy data, and variable execution in an environment of scarcity

Trippler build phases

  • Desirable, feasible, viable = user need, analytical technique, data curation
  • Phased delivery to manage risk

Demo

What I learned

  • Things that were cactus and things that were apples
  • Lots of amazing Python libraries and open services

What’s next?

  • Incremental improvements (like charger hopping)
  • Stoppler
  • Future development options
  • Related problems in transport electrification
  • Or network resilience improves sufficiently … to make charger anxiety and trip planning redundant!


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