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3_objects.html

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@@ -915,7 +915,7 @@ <h2><span class="section-number">3.6. </span>Exercises<a class="headerlink" href
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<span class="proof-type">Exercise 3.4</span>
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</div><div class="proof-content">
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<p>Define a function <code class="xref py py-obj docutils literal notranslate"><span class="pre">derivative</span></code> in <code class="file docutils literal notranslate"><span class="pre">polynomial.py</span></code> which takes a
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<p>Define a function <code class="xref py py-obj docutils literal notranslate"><span class="pre">derivative</span></code> in <code class="file docutils literal notranslate"><span class="pre">polynomials.py</span></code> which takes a
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<code class="xref py py-class docutils literal notranslate"><span class="pre">Polynomial</span></code> and returns a new <code class="xref py py-class docutils literal notranslate"><span class="pre">Polynomial</span></code> which is its
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derivative. Also define a <code class="xref py py-meth docutils literal notranslate"><span class="pre">dx()</span></code> method on the <code class="xref py py-class docutils literal notranslate"><span class="pre">Polynomial</span></code> class
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which returns the derivative of that <code class="xref py py-class docutils literal notranslate"><span class="pre">Polynomial</span></code>. Rather than

5_abstract_data_types.html

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@@ -1140,7 +1140,7 @@ <h2><span class="section-number">5.9. </span>Exercises<a class="headerlink" href
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</div>
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</div>
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</div>
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<p>Obtain the <a class="reference internal" href="not_released.html"><span class="doc">skeleton code for these exercises from GitHub classroom</span></a>.</p>
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<p>Obtain the <a class="reference external" href="https://classroom.github.com/a/eHigwP_C">skeleton code for these exercises from GitHub classroom</a>. You will also need to install the pytest-timeout package.</p>
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<div class="proof proof-type-exercise" id="id17">
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<div class="proof-title">
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</div><div class="proof-content">
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<p>In this week’s skeleton repository, create a <a class="reference internal" href="2_programs_in_files.html#term-package"><span class="xref std std-term">package</span></a> called
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<code class="xref py py-mod docutils literal notranslate"><span class="pre">adt_examples</span></code> with a <a class="reference internal" href="2_programs_in_files.html#term-module"><span class="xref std std-term">module</span></a> called
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<code class="xref py py-mod docutils literal notranslate"><span class="pre">adt_examples.fibonacci</span></code>. Create a class <code class="xref py py-class docutils literal notranslate"><span class="pre">Fib</span></code> implementing the
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iterator protocol which returns the Fibonacci numbers. In other words, the
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following code should print the <code class="xref py py-obj docutils literal notranslate"><span class="pre">Fibonacci</span></code> numbers under 100:</p>
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<code class="xref py py-mod docutils literal notranslate"><span class="pre">adt_examples.fibonacci</span></code>. Make the package installable and install in
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editable mode. Create a class <code class="xref py py-class docutils literal notranslate"><span class="pre">Fib</span></code> implementing the iterator
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protocol which returns the Fibonacci numbers. In other words, the following
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code should print the <code class="xref py py-obj docutils literal notranslate"><span class="pre">Fibonacci</span></code> numbers under 100:</p>
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<div class="highlight-python3 notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">adt_examples.fibonacci</span> <span class="kn">import</span> <span class="n">Fib</span>
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<span class="k">for</span> <span class="n">n</span> <span class="ow">in</span> <span class="n">Fib</span><span class="p">():</span>

6_exceptions.html

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iteration should fail if <span class="math notranslate nohighlight">\(n\)</span> exceeds a user-specified number of
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iterations.</p>
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<p>The skeleton code for this week contains a function
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<code class="xref py py-func docutils literal notranslate"><span class="pre">nonlinear_solvers.solvers.newton-raphson()</span></code> which takes as arguments a
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<code class="xref py py-func docutils literal notranslate"><span class="pre">nonlinear_solvers.solvers.newton_raphson()</span></code> which takes as arguments a
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function, its derivative and a starting point for the iteration. It can also
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optionally be passed a value for <span class="math notranslate nohighlight">\(\epsilon\)</span> and a maximum number of
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iterations to execute. Implement this function. If the iteration succeeds

_sources/3_objects.rst.txt

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@@ -919,7 +919,7 @@ the :class:`Polynomial` class.
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.. proof:exercise::
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Define a function `derivative` in :file:`polynomial.py` which takes a
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Define a function `derivative` in :file:`polynomials.py` which takes a
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:class:`Polynomial` and returns a new :class:`Polynomial` which is its
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derivative. Also define a :meth:`dx` method on the :class:`Polynomial` class
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which returns the derivative of that :class:`Polynomial`. Rather than

_sources/5_abstract_data_types.rst.txt

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:classes: stretched-link
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Obtain the :doc:`skeleton code for these exercises from GitHub classroom <not_released>`.
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Obtain the `skeleton code for these exercises from GitHub classroom
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<https://classroom.github.com/a/eHigwP_C>`__. You will also need to install the pytest-timeout package.
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.. proof:exercise::
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In this week's skeleton repository, create a :term:`package` called
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:mod:`adt_examples` with a :term:`module` called
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:mod:`adt_examples.fibonacci`. Create a class :class:`Fib` implementing the
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iterator protocol which returns the Fibonacci numbers. In other words, the
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following code should print the `Fibonacci` numbers under 100:
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:mod:`adt_examples.fibonacci`. Make the package installable and install in
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editable mode. Create a class :class:`Fib` implementing the iterator
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protocol which returns the Fibonacci numbers. In other words, the following
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code should print the `Fibonacci` numbers under 100:
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.. code-block:: python3
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_sources/6_exceptions.rst.txt

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iterations.
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The skeleton code for this week contains a function
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:func:`nonlinear_solvers.solvers.newton-raphson` which takes as arguments a
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:func:`nonlinear_solvers.solvers.newton_raphson` which takes as arguments a
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function, its derivative and a starting point for the iteration. It can also
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optionally be passed a value for :math:`\epsilon` and a maximum number of
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iterations to execute. Implement this function. If the iteration succeeds

searchindex.js

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