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Server Restarted

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Asked Jul/27/2023 ago
Modified Aug/5/2023 ago
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What is the purpose of the "yield" keyword in Python, and how does it work?

I'm trying to grasp the concept of the "yield" keyword in Python by analyzing the following code snippet:

def _get_similar_candidates(self, similarity, min_similarity, max_similarity):
    if self._left_child and similarity - max_similarity < self._median:
        yield self._left_child
    if self._right_child and similarity + max_similarity >= self._median:
        yield self._right_child

This code is part of a larger program where there's a method called _get_similar_candidates defined within a class. The purpose of this method is to identify and return candidate nodes that meet certain similarity criteria based on the given input parameters similarity, min_similarity, and max_similarity.

Now, the caller code looks like this:

result, candidates = [], [self]
while candidates:
    node = candidates.pop()
    similarity = node._get_similarity(target_object)
    if min_similarity <= similarity <= max_similarity:
        result.extend(node._values)
    candidates.extend(node._get_similar_candidates(similarity, min_similarity, max_similarity))
return result

In this caller code, an initial list called candidates is created with the current object self as its single element. The code then enters a loop, where it repeatedly pops elements from the candidates list and examines their similarity to the target_object. If the similarity of a node falls within the specified range (min_similarity and max_similarity), the node's values are added to the result list.

Now, let's focus on the critical part of this process - the _get_similar_candidates method. When this method is called, it performs some checks on its own node (self) to determine whether it satisfies the similarity conditions based on the given similarity, min_similarity, and max_similarity values. If a certain condition is met, the method utilizes the yield keyword to create an iterator and yield the left child and/or right child nodes as candidate results.

Here's how it works:

The method checks if the left child exists self._left_child. If it does and meets the similarity criteria, it yields the left child as a candidate.

Similarly, the method checks if the right child exists self._right_child. If it does and meets the similarity criteria, it yields the right child as another candidate.

By using the yield keyword, the _get_similar_candidates method creates a generator function, which means that it doesn't return an ordinary list containing the candidate nodes. Instead, it returns an iterator that generates candidate nodes one by one, as they are needed. This makes it memory-efficient as it doesn't create a large list all at once.

The caller code iterates through this generator and extends the candidates list with the yielded candidate nodes. The loop continues until all nodes that satisfy the similarity conditions have been processed. Each time the method is called again, it picks up from where it left off, allowing the iteration to continue until there are no more candidate nodes to yield.

So, to summarize, the _get_similar_candidates method returns a generator that yields candidate nodes meeting the specified similarity conditions. The method is called repeatedly until all eligible candidates are processed, and subsequent calls stop once there are no more candidates left to yield.
pythonyieldselfsimilarityexampleexplainedSave Post
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Asked 27 Jul 2023 21:33
Ghost Together
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Use comments to ask for more information or to suggest improvements to the question. Avoid answering questions in the comments. If you have an accurate answer, it's best to post an answer instead. Ghost Together 28 Jul 2023 04:47 AM
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