Peak Python Julia Ascendant

Well I guess the clue is in the title!

Python has been a good alternative programming language to me over the years. When I want to skip a compile cycle and need something more than Bash but less mind bending than R Python is there.

However with the emergence of Julia, another language with strong numerical foundations, it’s getting hard to see how Python will remain choice #1 for data science.

There are a number of factors playing into this switcheroo.

  1. Without any prior experience of Python or Julia and within the limited scope of language design you would be preparing for a passing opportunity if you dedicated time to Python.
  2. Community change. The rumblings are there. Julia for ML, Julia for plotting, Julia for new projects in general.
  3. Julia makes it trivial to call out to GPU resources: https://blogs.technet.microsoft.com/machinelearning/2017/01/31/julia-a-fresh-approach-to-numerical-computing/
  4. Google is interested:

https://medium.com/syncedreview/google-cloud-tpus-now-speak-julia-cefd15a2a060

https://twitter.com/jeffdean/status/1054951415339192321?lang=en-gb

Having said that of course Python will be with us for many happy years to come and a swallow does not a summer make but I know where my picnic blanket lies.