python features (broad) actually used inside 2 Wall St ibanks

If a python project takes 1 man-year, then the number of python features used would be 2 man-weeks, because python is an easy-learning language. In such a project you probably won’t need fancy features like threading, decorators… Most of the work would be mundane.

After the initial weeks of exciting learning curve, you may feel bored. (c# took me months/years). You may feel your peers are deepening their expertise in c++ or wpf …

The tech quiz would be mostly on syntax.

========= the features =========
? lambda, closure, apply()
Everyday operations on list/dict/tuple, str, file object
** for-loop, conversion, filter(), map(), aggregation, argument passing,
Filesystem, input/output
Basics of module import (no advanced features needed)
command line processing + env vars
create functions –composite argument passing
config files and environment config like PYTHON_PATH

———a bit advanced and less used———
creating classes? fewer than functions, and usually simple classes only
list comprehension, generator expressions
basic platform-specific issues. Mostly unix
inheritance, overriding
threading
spawn new processes
decorators
* Python calling C, not the other way round. In financial analytics, heavy lifting is probably done in C/C++ [1], so what’s doable in python? I guess the domain models (market models, instrument models, contract models …) are probably expressed in python as graph-aware python objects.

[1] I have a book on option pricing using things like Finite Element Method. It seems to use many c++ language features (template etc) but I’m not sure if java or python can meet the requirements.

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