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This makes part of the data structure into a ring, causing naive code to loop forever. While most infinite loops can be found by close inspection of the code, there is no general method to determine whether a given program will ever halt or will run forever; this is the undecidability of the halting problem. [8]
Executing a set of statements only if some condition is met (choice - i.e., conditional branch) Executing a set of statements zero or more times, until some condition is met (i.e., loop - the same as conditional branch) Executing a set of distant statements, after which the flow of control usually returns (subroutines, coroutines, and ...
A generator expression may be used in Python versions >= 2.4 which gives lazy evaluation over its input, and can be used with generators to iterate over 'infinite' input such as the count generator function which returns successive integers:
[52] [53] While Python 2.7 and older versions are officially unsupported, a different unofficial Python implementation, PyPy, continues to support Python 2, i.e. "2.7.18+" (plus 3.10), with the plus meaning (at least some) "backported security updates". [54] Python 3.0 was released on 3 December 2008, with some new semantics and changed syntax.
A conditional loop has the potential to become an infinite loop when nothing in the loop's body can affect the outcome of the loop's conditional statement. However, infinite loops can sometimes be used purposely, often with an exit from the loop built into the loop implementation for every computer language , but many share the same basic ...
In computer science, a for-loop or for loop is a control flow statement for specifying iteration. Specifically, a for-loop functions by running a section of code repeatedly until a certain condition has been satisfied. For-loops have two parts: a header and a body. The header defines the iteration and the body is the code executed once per ...
This allows for many radical things to be done syntactically within Python. A new method resolution order for multiple inheritance was also adopted with Python 2.3. It is also possible to run custom code while accessing or setting attributes, though the details of those techniques have evolved between Python versions.
Coroutines are well-suited for implementing familiar program components such as cooperative tasks, exceptions, event loops, iterators, infinite lists and pipes. They have been described as "functions whose execution you can pause". [1] Melvin Conway coined the term coroutine in 1958 when he applied it to the construction of an assembly program. [2]