The summary.
PYTHON DOMINATES DATA WORK BECAUSE THE LIBRARIES ARE THERE AND MATURE
Its numerical performance comes from work happening outside Python, in lower-level libraries it directs.
Use separate processes for computation, since threads do not execute code simultaneously.
ALWAYS USE A VIRTUAL ENVIRONMENT PER PROJECT
Otherwise projects needing different library versions conflict.
THE PYTHON TRAP THAT CATCHES EVERYONE ONCE
Mutable default arguments, created once and shared across calls.
RUBY'S FLEXIBILITY IS ITS STRENGTH AND ITS RISK
Modifying existing classes at runtime is powerful and easily abused. Agree conventions limiting it.
PERL'S REPUTATION FOR WRITE-ONLY CODE COMES FROM CONCISENESS WITHOUT DISCIPLINE
You will meet it maintaining existing systems. Enable strict and warning modes before changing anything.
LUA IS LEARNED BECAUSE SOMETHING YOU USE EMBEDS IT
Tables are the entire data model, and indices conventionally start at one.
ACROSS ALL OF THESE, ADD TYPE ANNOTATIONS AND CHECKING AS PROJECTS GROW
Dynamic typing is comfortable until a codebase becomes large enough that nobody remembers what a function expects.
