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        content="Chapter 10 of Python Zero to Hero: master Python’s iterators, generators, and comprehensions for efficient looping and data processing."/>
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        content="Python, iterators, iteration protocol, generators, yield, comprehensions, list comprehension, dict comprehension, set comprehension"/>
  <meta name="author" content="Luca Bocaletto"/>
  <title>Chapter 10 – Iterators, Generators & Comprehensions | Python Zero to Hero</title>

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      <h1 class="display-6">Chapter 10: Iterators, Generators &amp; Comprehensions</h1>
      <p class="text-muted">
        Dive deep into Python’s iteration protocol, build generators for lazy evaluation, and use comprehensions for concise data transformations.
      </p>
      <a href="src/chapter10.py" download class="btn btn-outline-primary btn-sm btn-py">
        Download <code>chapter10.py</code>
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    <!-- Objectives -->
    <section id="objectives" class="mb-5">
      <h2>Objectives</h2>
      <ul>
        <li>Understand the iterator protocol: <code>__iter__()</code> &amp; <code>__next__()</code>.</li>
        <li>Use built-in iterators with <code>iter()</code> and <code>next()</code>.</li>
        <li>Create custom iterator classes.</li>
        <li>Write generator functions with <code>yield</code>.</li>
        <li>Use generator expressions.</li>
        <li>Build list, dict and set comprehensions.</li>
      </ul>
    </section>

    <!-- 1. Iterators -->
    <section id="iterators" class="mb-5">
      <h2>1. Iterators &amp; The Iteration Protocol</h2>
      <p>Any object implementing <code>__iter__()</code> and <code>__next__()</code> is an iterator:</p>
      <pre><code class="python"># list is iterable, not iterator
lst = [1,2,3]
it = iter(lst)         # get iterator
print(next(it))        # 1
print(next(it))        # 2
# StopIteration when exhausted
</code></pre>
      <p>Custom iterator class:</p>
      <pre><code class="python">class Counter:
    def __init__(self, limit):
        self.limit = limit
        self.current = 0
    def __iter__(self):
        return self
    def __next__(self):
        if self.current >= self.limit:
            raise StopIteration
        val = self.current
        self.current += 1
        return val

for i in Counter(3):
    print(i)  # 0,1,2
</code></pre>
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    <!-- 2. Generators -->
    <section id="generators" class="mb-5">
      <h2>2. Generator Functions</h2>
      <p>Use <code>yield</code> to produce a sequence lazily:</p>
      <pre><code class="python">def fib(n):
    a, b = 0, 1
    for _ in range(n):
        yield a
        a, b = b, a + b

for num in fib(5):
    print(num)  # 0,1,1,2,3
</code></pre>
      <p>Generators maintain state automatically and raise <code>StopIteration</code> when done.</p>
    </section>

    <!-- 3. Generator Expressions -->
    <section id="genexpr" class="mb-5">
      <h2>3. Generator Expressions</h2>
      <p>Compact syntax for generators:</p>
      <pre><code class="python"># squares generator
squares = (x*x for x in range(10))
print(next(squares))   # 0
for sq in squares:
    print(sq)
</code></pre>
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      <h2>4. Comprehensions</h2>
      <h3>a) List Comprehensions</h3>
      <pre><code class="python"># even squares 0–9
even_squares = [x*x for x in range(10) if x % 2 == 0]
</code></pre>
      <h3>b) Dict Comprehensions</h3>
      <pre><code class="python"># map to square
sq_map = {x: x*x for x in range(5)}
</code></pre>
      <h3>c) Set Comprehensions</h3>
      <pre><code class="python"># unique first letters
names = ["Alice","Bob","Anna"]
first_letters = {name[0] for name in names}
</code></pre>
    </section>

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      <h2>Exercises</h2>
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        <li>Implement an iterator class <code>Fibonacci</code> that yields Fibonacci numbers up to <code>n</code>.</li>
        <li>Write a generator <code>primes()</code> that yields prime numbers indefinitely.</li>
        <li>Use a generator expression to compute the sum of squares of numbers 1–100 lazily.</li>
        <li>Flatten a nested list (e.g., <code>[[1,2],[3,4]]</code>) using a nested list comprehension.</li>
        <li>Given a dict mapping, write a dict comprehension to invert keys and values.</li>
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