How Does Python's `yield` Keyword Create and Manage Generators?

What does the "yield" Keyword Do in Python?

Introduction

Understanding the yield keyword in Python requires familiarity with iterables and generators.

Iterables

Iterables are objects like lists and strings that can be iterated over one element at a time.

Generators

Generators are iterators that produce values one at a time without storing the entire sequence in memory.

Yield

The yield keyword functions like a return statement in a generator function. However, instead of ending the function, it pauses execution and returns a value. When the iterator resumes, execution continues from where it paused.

Your Code Explained

Generator:

def _get_child_candidates(self, distance, min_dist, max_dist):
    # Check if a left child exists and the distance is within range
    if self._leftchild and distance - max_dist < self._median:
        yield self._leftchild

    # Check if a right child exists and the distance is within range
    if self._rightchild and distance + max_dist >= self._median:
        yield self._rightchild

This generator function returns child nodes within the specified distance range.

Caller:

result, candidates = [], [self]  # Initialize empty result and candidates list

while candidates:  # Iterate while candidates are available
    node = candidates.pop()
    distance = node._get_dist(obj)
    
    if distance <= max_dist and distance >= min_dist:  # Check distance range
        result.extend(node._values)

    candidates.extend(node._get_child_candidates(distance, min_dist, max_dist))  # Add children to candidates list

return result

The caller initializes and iterates through a list of candidate nodes, using the generator function to expand the candidates list while looping. It checks the distance range and adds child nodes if appropriate.

Advanced Generator Use

The yield keyword enables control over generator exhaustion. By setting a flag to stop iteration, you can pause and resume access to generator values.

Itertools

The itertools module provides functions to manipulate iterables. For example, you can create permutations of a list easily.

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