Scoping in Python 'for' Loops: Understanding the Design Philosophy
While Python's scoping rules for 'for' loops are generally understood, the reasoning behind them has remained a mystery. This article investigates the rationale behind the design decisions that have led to the current scoping behavior.
Consider the following Python code:
for foo in xrange(10): bar = 2 print(foo, bar)
When executed, this code will print (9, 2). This behavior is surprising because 'foo' is only used to control the loop iteration, and 'bar' is defined within the loop. Logically, it would seem unnecessary for 'bar' to be accessible outside the loop and for the loop control variable 'foo' to remain in scope after the loop exits.
The most plausible explanation for this design choice is simplicity. By keeping the scoping rules straightforward, Python maintains a clear and concise grammar. This decision has not hindered adoption, and the feature has been widely accepted by the community. Assigning variables within loop constructs does not require explicit scope disambiguation. Additionally, the global keyword provides a means to assign variables to a global scope.
A thorough discussion on Python's scoping rules can be found on the Python Ideas mailing list. One notable argument is that existing code often relies on loop variables retaining their values after exiting a loop, which is considered a desirable feature.
In conclusion, Python's design philosophy for scoping in 'for' loops prioritizes simplicity, with the goal of maintaining a clear and concise syntax. This approach has proven popular within the Python community, despite some potential downsides regarding cluttered global namespaces and error tracing.
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