What I meant was that - in the time after it was created for sysadmin tasks - but before it found it’s new home in data-science - Python was often used as a beginners’ language as a more modern and expressive alternative to BASIC - which led to its “toy” reputation - an undeserved reputation that it has successfully shed.
It is hard for me to accept that historical interpretation as I started using Python back in the 1990s, when it was already making in-roads in steering high-performance computing codes. NumPy's roots date from that era.
In 2002 it seemed that half the attendees of the Python conference were there because of Zope.
I was programming full-time by 1999.
So for me Python was well-established in several areas far before its wide-spread use in computer programming education or its use in data science.
I never had any exposure to HPC, scientific or numerical computing, even through university and in my career - that world is still comparatively silo'd off from the wider dev ecosystem IME; I know you are correct in what you say, but I imagine Millennials like myself (who were still in middle-school when you were using Python professionally) only ever saw Python in less serious applications.
What I meant was that - in the time after it was created for sysadmin tasks - but before it found it’s new home in data-science - Python was often used as a beginners’ language as a more modern and expressive alternative to BASIC - which led to its “toy” reputation - an undeserved reputation that it has successfully shed.