I always feel like there is a big misunderstanding of what it means to “write a program in some language” in these types of comparisons.
For example, saying that Python uses much more energy is a foolish thing to say. The “same” algorithm written in pure Python is a very semantically different thing. It involves allocation of flexible objects that obey certain attribute lookup protocols, operator protocols, dynamic attribute mutation / creation, iteration protocols, etc. It is presumed that if you wrote in pure Python, you need this dynamism and ability to introspect at runtime, modify data structure layout arbitrarily, utilize an automatic garbage collector, etc. So you’d need a benchmark test that requires all that functionality before it could possibly make sense to test Python. Otherwise you’re penalizing Python for a bunch of expensive overhead, which is totally unfair and foolish because the whole point is that such overhead exists for use cases where either the costs are negligible or the flexibility that necessitates that overhead in any language happens to be a desired and important part, such that to write the same functionality in other languages would first require building all the protocols, garbage collection, etc. machinery that essentially defines Python.
If instead you have some benchmark problem that can be solved in e.g. C or Rust without needing any runtime dynamism or heavy machinery of certain protocols or garbage collection, then to write it in Python you would just write it in Cython or as a hand-made C extension module to specifically bypass the overhead of the interpreter or Python protocols / dynamic lookups / etc.
Basically, it never makes sense to compare Python and C on a benchmark that doesn’t require reimplementing most of Python in C first. Because to solve that problem in Python, the ubiquitous, basic, Python 101 way to do it would be to use Cython or numba or write your own extension module.
Python is basically a special C language DSL for dynamic types, garbage collection, and a set of conventions and protocols.
“Pure Python” is a linguistic trick for saying “a huge ton of tools that make C-level polymorphic structs easy to use.”