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In Python, a generator can be thought of as an iterator that contains a frozen stack frame. Whenever next() is called on the iterator, Python resumes the frozen frame, which executes normally until the next yield statement is reached. The generator's frame is then frozen again, and the yielded value is returned to the caller.
Cascading can be implemented in terms of chaining by having the methods return the target object (receiver, this, self).However, this requires that the method be implemented this way already – or the original object be wrapped in another object that does this – and that the method not return some other, potentially useful value (or nothing if that would be more appropriate, as in setters).
It's a free compiler, though it also has commercial add-ons (e.g. for hiding source code). Numba is used from Python, as a tool (enabled by adding a decorator to relevant Python code), a JIT compiler that translates a subset of Python and NumPy code into fast machine code. Pythran compiles a subset of Python 3 to C++ . [160]
When code generation occurs at runtime, as in just-in-time compilation (JIT), it is important that the entire process be efficient with respect to space and time. For example, when regular expressions are interpreted and used to generate code at runtime, a non-deterministic finite-state machine is often generated instead of a deterministic one, because usually the former can be created more ...
There are subtle differences and distinctions in the use of the terms "generator" and "iterator", which vary between authors and languages. [5] In Python, a generator is an iterator constructor: a function that returns an iterator. An example of a Python generator returning an iterator for the Fibonacci numbers using Python's yield statement ...
A snippet of Python code with keywords highlighted in bold yellow font. The syntax of the Python programming language is the set of rules that defines how a Python program will be written and interpreted (by both the runtime system and by human readers). The Python language has many similarities to Perl, C, and Java. However, there are some ...
A call graph generated for a simple computer program in Python. A call graph (also known as a call multigraph [1] [2]) is a control-flow graph, [3] which represents calling relationships between subroutines in a computer program.
Loop-carried dependencies and loop independent dependencies are determined by the relationships between statements in iterations of a loop. When a statement in one iteration of a loop depends in some way on a statement in a different iteration of the same loop, a loop-carried dependence exists.