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‎doc/source/0_preface.rst‎

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Preface
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=======
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Computers have revolutionised mathematics, as well as the many scientific,
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engineering and economic fields in which mathematics is applied. In
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the applications of mathematics the role of computation has long been obvious
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and prominent. Now, the development of theorem proving software is increasing
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the prominence of computing in pure mathematics. What this means is that
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the ability to write computer programs is an indispensible part of the toolkit
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of a 21st century mathematician and, indeed, scientist or engineer.
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Regrettably, university courses in mathematics and its sibling disciplines have
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often failed to reflect this revolution in the way that mathematics is
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practised. Far too often the sum total of programming education in an
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undergraduate degree is a computational methods module in which students are
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shown elementary programming constructs such as functions, loops, and perhaps
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plotting. These are introduced in the context of solving particular
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computational mathematics or statistics problems, and the programming
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constructs introduced are driven by what is needed to solve those problems.
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The assumptions underpinning this approach seem to be some combination of a
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belief that maths degrees should only teach maths, as well a feeling that the
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mathematical algorithms are some how the difficult part and that programming is
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a mere technical skill that students will somehow pick up along the way. The
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regrettable consequence of this approach is that many maths students and
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graduates end up without the programming, software development, and debugging
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skills that they need to make effective use of computers in their further
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studies or working careers.
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What is this book for?
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----------------------
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This book is the result of a significant change in the mathematics curriculum
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at Imperial College London. Rather than assume that students will somehow
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acquire programming skills along the way, we have introduced first and second
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year courses with the sole objective of teaching students to programme well.
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This book is the text for the second of these courses. Named "Principles of
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Programming", the course aims to take students with a knowledge of basic Python
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programming (functions, loops, plotting and so forth) and introduce them to
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higher level programming concepts. The course has also been taught to masters
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The objective of this course is to graduate better programmers, so material on
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new programming constructs and concepts is accompanied by chapters on good
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programming style, so that students learn how to write code that they and
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others can understand, and on errors, exceptions and debugging, so that
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students learn how to get themselves out of trouble.
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An underlying theme throughout this book is that programming has strong
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connections with mathematics. In particular, both mathematics and programming
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depend on building higher level, more abstract objects which encapsulate and
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hide the underlying complexity of operations. It is in taking this mathematical
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approach to programming that this book is "for mathematicians".
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The examples are chosen from across mathematics. For example, it appears to be
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traditional in object oriented programming books to use a telephone directory
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as the initial example of classes. We eschew this in favour of a class
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implementing polynomials. This provides the opportunity to introduce
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encapsulation and operator overloading for a familiar mathematical object. In
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contrast to the traditional computational methods courses, the examples are
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chosen to illustrate and explain the programming concepts we study rather than
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the converse.
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Who is this book for?
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---------------------
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This book is for anyone with mathematical, scientific, or engineering interests
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who would like to learn to be a more capable programmer. The mathematical
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examples assume that you know how to differentiate functions of one variable,
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but very little beyond that. This is not an introduction to basic Python: it's
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assumed that the reader knows the sort of basic Python usually covered in a
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first programming or computational methods course. In particular the reader
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will be assumed to be familiar with writing functions, variable assignments,
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loops, and list comprehensions. The reader is also assumed to have used numeric
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and string data values, as well as dictionaries, lists, and tuples.
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Many introductory Python courses exclusively use Jupyter notebooks, so nothing
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beyond that is assumed. Getting set up with a working Python installation is
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covered in :numref:`introduction` while the Python command line and using a
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text editor to create programmes in files are introduced from scratch in
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:numref:`programs_files`.
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How to use this book
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--------------------
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You can, of course, simply sit down and read this book from cover to cover, or
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dip in to see what it has to say on particular subjects. However, reading a
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book about programming will not teach you to program. For that, you need to get
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your hands dirty writing code and debugging your mistakes. To help with this
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there is a book website at:
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`https://object-oriented-programming.github.io
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<https://object-oriented-programming.github.io>`__
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As well as a web version of the full text of the book, the website contains
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videos and the code needed to do the programming exercises at the end of each
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chapter.
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The videos
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..........
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The videos were created to accompany the course at Imperial College London.
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They're not primarily lecture videos but are instead practical demonstrations
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of the programming concepts being introduced at the relevant point. Usually
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it's better to watch the video *after* reading the relevant section.
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.. only:: latex
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The videos are marked in the text by a blue box at the right hand side,
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containing the video number. This corresponds to the list of links at:
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`https://object-oriented-programming.github.io/edition1/videos.html
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<https://object-oriented-programming.github.io/edition1/videos.html>`__
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The exercises
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.............
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At the end of each chapter are exercises. These usually depend on a skeleton
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code which is available on GitHub. Sometimes you might be asked to complete a piece of code while on other
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occasions you'll need to write a whole Python module from scratch. Each set of
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exercises will come with a matching set of tests. These are small programs which
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check whether your code produces the correct responses to a range of inputs.
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Tests like this provide immediate feedback and enable you to know how you are
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doing. Links to the skeleton code for each chapter are provided at:
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`https://object-oriented-programming.github.io/edition1/exercises.html
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<https://object-oriented-programming.github.io/edition1/exercises.html>`__
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The mechanism for accessing the exercises will be covered in
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:numref:`introduction`.
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Conventions employed
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--------------------
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Each chapter starts by introducing new material, supported by the videos and
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exercises. At the end of each chapter is a glossary containing many of the key
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concepts introduced in that chapter. Terms to be found in a glossary are given
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*in italics* and can be looked up in the index.
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.. only:: not book
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Python has excellent `official online documentation
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<https://docs.python.org/3/>`_, and we link to that throughout the text.
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External links show up in orange while :ref:`internal links to other parts
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of the notes <introduction>` are red.
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The text sometimes introduces counterexamples: illustrations of code errors or
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bad implementation ideas. These will be flagged with a big red cross:
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.. container:: badcode
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.. code-block:: python3
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print "Hello World"
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Conversely, if it's necessary in context to highlight which approach is the
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correct one, the code will come with a big green tick:
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.. container:: goodcode
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.. code-block:: python3
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print("Hello World")
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Teaching this course elsewhere
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------------------------------
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The course of which this book forms the text has been given to master's
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students at the University of Oxford, as well as to undergraduate students at
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Imperial College London. Instructors are welcome to use this material to teach
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elsewhere, and are encouraged to contact the author for assistance with access
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to materials.
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Acknowledgements
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----------------
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The course Principles of Programming, and the notes on which this book is
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based, were first delivered in spring 2020, when university teaching was
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completely online during the COVID pandemic. I'd like to thank teaching fellow
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Dr Matthew Woolway who worked tirelessly with me on the module and who put
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together many of the tests on the exercies, and the graduate teaching
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assistants Miguel Boland, Sophia Vorderwuelbecke and Connor Ward whose
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professionalism in delivering the course in very complex circumstances was
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outstanding. Pulling out all the stops to deliver the written and video
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materials for online learning meant a lot of evenings and weekends. I am
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exceptionally grateful to my wife Gebina Ham for disproportionately picking up
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our childcare responsibilities in that period in order to make this possible.
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This is a textbook about programming in Python, so it would be remiss of me not
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to also thank the developers of the Python language, its CPython reference
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implementation, and all the third party packages which on which this book
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depends. In that regard, the developers of Numpy, Flake8, Pytest, PDB++ and
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IPython deserve particular mention.
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This book is typeset using the Sphinx documentation system. Among other things
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this facilitates generating the web, PDF, and print versions of the book from a
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single source. Thanks are due to its authors as well as those of the underlying
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LaTeX and TeX typesetting systems.

‎doc/source/index.rst‎

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\frontmatter
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.. toctree::
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:maxdepth: 2
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0_preface
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.. raw:: latex
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\mainmatter
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.. only:: html
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This is the online textbook for MATH50009 Principles of Programming, a second
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year object oriented programming module offered to mathematics undergraduates at
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Imperial College London. Read the introductory chapter for information on how to
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go about doing the module week by week.
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This is the online textbook for MATH50009 Principles of Programming, a
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second year object oriented programming module offered to mathematics
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undergraduates at Imperial College London. Read the introductory chapter for
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information on how to go about doing the module week by week.
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If you're not taking the module at Imperial, you should nonetheless feel free to
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use this material to learn object-oriented programming in Python. I would be
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very interested to hear from anyone interested in using it to teach.
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If you're not taking the module at Imperial, you should nonetheless feel
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free to use this material to learn object-oriented programming in Python. I
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would be very interested to hear from anyone interested in using it to
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teach.
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.. toctree::
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:maxdepth: 2
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a1_help
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.. :numbered:
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.. :maxdepth: 1

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