Globals are not commonly used except in retrofit cases of legacy code or in beginner code.
I haven’t seen or used a global more than once in my 20 years of writing Python.
I haven’t seen or used a global more than once in my 20 years of writing Python.
Web services in Python that want to handle multiple comcurrent requests in the same interpreter should be using a web framework that is designed around that expectation and don't use a global request context object, such as FastAPI.
Because literally every import, class definition, or function definition that you make at top-level is a global.
Now some people do in fact do all those things inside a function, too, and then call that function as the only thing that actually happens globally. And I've done such hacks myself to squeeze the last few % of perf out of CPython on the very rare occasions where you need to do that but dropping into C is not an option. But that's certainly not idiomatic Python.
I have not been seeing good Python code, for sure. Hopefully it's not a majority. But it's very far from non-existent.
def f():
l = [0]
for i in range(100000000):
l += [2]
return l
x = f()
print(x[0])
3.9: 8.6s
3.14: 8.7s
3.14 (free-threading): 11.6s
3.9: 2.78
3.14: 3.86
3.14t: 3.91
This is a silly benchmark though. Look at pyperformance if you want something that might represent real script/application performance. Generally 3.14t is about 0.9x the performance of the default build. That depends on a lot of things though.
This benchmark demonstrates that global variables are not needed to find severe regressions.
If you don't want to use global variables just add the result of f to x and stop using the global variable, i.e.
x += f()Variables always start with a lowercase letter in idiomatic Python unless they're constants or types.
Using single-letter uppercase for variables is not unusual in ML Python code, but that also happens to be one of the worst ecosystems when it comes to idiomatic Python and general code quality.