It 210 Week 4 Assignment Pseudocode Generator

Python and Unix for Bioinformaticians - #27610

10 points course, Spring 2018

This is the old teaching site. Go to the new one at

IMPORTANT - do preparation for the course.

DTU's Studies Handbook about #27610

Time: Course starts January 30, 2016 and runs Mondays 13.00 - 17.00 and Thursdays 9.00-12.00
Module: F2-A and F2-B
Place: Aud. 142/148 in building 210, both days
Language: English
Evaluation form:Exercises during the course 25%. Project during the course 25%. 4 hour written examination 50%, no books or notes allowed, but some pages of abbreviated python will be available.
Exam date: 9.00 - 13.00, May 16, 2017
Exam location: Building 308, room 127, 117, 109, and 101
Teacher: Peter Wad Sackett,
Signing up: "Normal" DTU students sign up the normal way. other students check here, and/or ask the study administration. Signing up for a course has nothing to do with the teacher and everything to do with the DTU study administration.
Tools: See top link: Preparation for the course. A more general guide is Optional software for the course for your own computer. MobaXterm or VirtualBox with a linux installation is strongly recommended, if you dont have a Mac or Linux already.
Textbooks: There are no text books for the course. I will make do with powerpoints and references to online resources. You can find the material under the individual lessons.

  • Clean Code by Lukasz Dynowski. An amazing read that is mandatory. Read it once around lesson 4 and once more around lesson 8.
  • Coursera course: Programming for Everybody is a beginner course in Python. Everyone who wants to prepare for course 27610 can start here. Just get far enough so you understand what programming is and how it works. That will benefit you a lot as a newbie. Coursera textbook.
  • Learning Python, 5th ed. by Mark Lutz (O'Reilly) ISBN: 978-1-449-35573-9
    This is the best Python book I have read. It covers all the basics and then some. All from the perspective of being a novice programmer. However, it is a brick; big, heavy and unwieldy. If you only want one Python book, then this should be the one. The course will not be taught from this book, but it could be good to have if you really want to do something with Python. Again, you can always find info on the net.
Some online Unix/Python resources:
Online tutorial on unix
Python for Non-Programmers
Official Python 3 tutorial
Python 3 reference manual
Python 3 standard library
A fun read: Top 12 reasons you know you are a Big Data biologist
Lesson for the beginner: How programming and your life is similar
What most schools don't teach: But you are taught in this course

Go to China for Msc: powerpoint and document

How the exam is conducted

Exercises has to uploaded to "DTU inside - Assignments" Saturday before the next lesson on Monday or before. Word or pdf documents are NOT accepted - use only simple .txt or .py As stated the exercises count as a part of the final evaluation. Exercises which are given in after the solutions are published on CampusNet, are voided and will not count in the evaulation, no matter the reason for being late. The difficulty of the exam is such that in order to be able to pass you probably have to get a average score of 70% or better in the exercises. The course is a hands-on course in programming with a focus on "Learning by doing". So if you are not doing (exercises) you are not learning anything and can not pass the exam.
Purple exercises has to be done in pseudo code before you start implementing them in Python. The pseudo code is part of the hand-in for these exercises. So - make first pseudocode AND then real python programs for purple exercises.
Red exercises are part of the peer evaluation. They must be uploaded here, BUT they are also to be handed in together with the other exercises.
Exercise Delivery Status for Course Participants

Solutions to exercises
Solutions to each week's exercises are published before the next lesson on DTU inside (file sharing for this course).

Peer evaluation
Every week you should upload your solution to one of the weeks exercises. The exercise is the red one - there can be no mistake. No red excercise - no upload. In the following week the class will vote for the best solution. Both the upload and the voting are anonymous but tracked.
Doing this is actually one of the learning objectives of the course; Learning to read other peoples code, and write good understandable code yourself.
See the peer evaluation page.

Reading ahead and using not yet covered techniques
Sometimes people read ahead in the text book or the net and discover some techniques, that makes solving the exercises much easier. While you should learn whatever you can, then there is a reason for why the exercises are as they are, and the learning material (powerpoint) is a it is. A very important part of the course is to learn how program, how to think "programming", how to analyse a problem, how to formulate a strategy/workflow/algorithm that will solve the problem. If you just pull a magic rabbit out of the hat, then you are not learning that, and you will be doing yourself an enormous disservice.
By not thinking - structuring the code more logically - gaining insight in the natural flow of problem solving, you will lack those skills - that mindset - when you really need it to solve more difficult exercises and/or problems.
Python is full of rabbits, so it is rather tempting, but damaging to use them during the course. You will have plenty of opportunity later in the project to show techniques and skills.

Everybody has to do an individual project during the course. See the list here.

and who should make cake.

  1. 30/01 UNIX Teachers
  2. 02/02 Python Basics
    03/02 Voluntary extra time for exercises and questions, 10.30 - 14.30, aud 062, build 208
  3. 06/02 Python Simple file reading Sule, Alexander Kruh??ffer, Line Andresen
    09/02 Pseudocode and comments - Powerpoint here
  4. 13/02 Python I/O Sanne, Annie, Anna Henius
    16/02 Continuing lesson
  5. 20/02 Exceptions and Bug Handling Alexander Pil, Taner, Leo
    23/02 Stateful parsing
  6. 27/02 Lists/Sequences Katrine, Joachim, Niels
    02/03 Midterm evaluation, part 1
  7. 06/03 Pattern Matching and Regular Expressions Natasha, Ole, Ida
    09/03 Midterm evaluation, part 2
  8. 13/03 Sets and Dictionaries Alvaro, Aimilla, Annette
    16/03 How to python and Project Intro
  9. 20/03 Python Functions and start of Project Hans-Christian, Nicoline, Alejandro
    23/03 Continuing lesson
  10. 27/03 Python and Advanced Data Structures Caroline, Xiaochen, Rasa
    30/03 Random numbers
  11. 03/04 Comprehension and Generators Eirini, Xenia, Anna Pors
    06/04 Continuing lesson
    20/04 Runtime evaluation of algorithms (Thursday)
  12. 24/04 Useful Functions and Methods Kirstine, Veronika, Maria
    27/04 Continuing lesson
  13. 01/05 Q/A Session
    04/05 Repetition and Project work.
  14. 08/05 The project is given in at 15.00 on Campusnet

So in this course, you and

when we ask you to do the programming part you will be writing the code in Python.

However, you will notice that when I'm describing algorithms or

when there are questions about algorithms the mathematical algorithms on

the homework, you'll see that I will be using or requiring the use of a,

of a certain program or language that we call pseudo code.


So we have this notion of pseudo-code.

[SOUND] Okay.

So what is pseudo-code and why do we want to use and

why not just stick to Python?

So pseudo-code is a language that is very powerful for describing algorithms.

It is somewhere between a formal programming language that

has exact syntax that you have to use, and English or any other natural language,

in the sense that it is not as formal as a programming language.

It gives you wiggle room for using structures or using English in them, but

is not like English that it is ambiguous or not structured.


So pseudo-code is very important,

you are going to be seeing it throughout the course.

We are going to be using it and

it's very important that you feel comfortable with reading pseudo-code.


There are going to be on the website some notes about syntax that

we use for pseudo-code.

Of course, the syntax is going to be not very formal because you

might ask me why don't we formalize pseudo-code?

But if we formalize pseudo-code, what did we get ourselves into?

We have defined yet another programming language.

All right? So

we cannot formalize the syntax of pseudo-code perfectly because otherwise,

we have again created another programming language.

So pseudo-code, you know,

when we use a certain notation, doesn't mean that this is universal notation.

If you look at different algorithms textbook,

you might see differences in the pseudo-code that the authors use.

Usually, it reflect the programming language that the author has been using.


So for example the sign for assignment, how do I assign the value five to x.

You might see some book saying, x equal five.


You might see some book saying, x colon equal five.

You might see some text books saying, x left arrow five.


And all of them this is assignment, right?

Of course, if you are using Python you have to use one specific symbol

for assignment.

If you are using C Plus Plus, you have to use one specific symbol for assignment.

In, in pseudo-code, it's not that this is right and these are wrong.

Or this is right and these are wrong.

No, you will see these all these ones in different text books.


Now every text book tries to be consistent, so

if a text book is using this for

assignment, you will see that the textbook is using this throughout the book.


But it's very important to keep in mind that we are not going to be

compiling the code, we are not going to be really running the pseudo-code in the so

it doesn't matter if it was this or this or this as long as we are consistent.

For example, in this course,

we are going to be using this notation, x left arrow five.

It means, I am assigning the value five to x.


So, you might be asking, why am I, am I using pseudo-code again and not python.

Okay? Python is in some sense is

a high level language.


The one of the major issues of, or the rationale behind using pseudo-code is

that pseudo-code tells us what we want to do.

It tells us what we want to do in terms of the algorithm,

not necessarily how we want to do it.


And when I am describing the algorithm to you,

it's very important that I tell you what I want you to do.

These are the steps that I want you to follow to, to, to achieve the, the task.

Now, how you want to do each one of these steps?

Again, it's very important sometimes to leave room for the, for the user or

the programmer to implement them the way they feel comfortable or

the way they find them to be more efficient.


Let me illustrate.

Suppose I'm in, I'm writing an algorithm or a piece of program and somewhere there,

I want, I have a list, L and I want to find the minimum element in that list.

Okay? The smallest element or

a smallest element in that list.

So here's one way I would write it in pseudo-code.

Let say, x is the smallest [SOUND]

element [SOUND] of L.


So this is one way that I can describe this in pseudo-code.

Notice, I'm using English, I'm using some mathematical symbols.

But it is basically telling me that I am assigning to x the smallest element of L.

Now, I have told you what I want to be assign,

to assign to x, the smallest element in L.

Okay? Or

a smallest in case there are multiple ones.

Now, no, contrast this to the following.

So this is a part of code that says, initialize x to infinity very

large number, then loop throughout all the elements of L.

Here I'm assuming that the list is index trans zero to n

minus one if it has n elements.

And for every element of L, i is smaller is x,

if the first one is smaller than x I'm going to replace x by that one.

And I repeat, if the second element is smaller than x,

I'm going to put an x the second element and so on.

What does this code do?

This code is identical to this.

This is going to actually find the smallest element in L and say that,

and put it in x.

Now, is this telling us anything more than this about what we want to do?

The answer is no.

I would argue that this is not telling me anything more than this about what

I want to do.

It's basically telling me, I want to set to x the smallest element in the list.

What is this giving me more than this?

It's telling me the how, how am I doing it.


So this one is saying, to find the minimum element in L,

I'm going to be scanning the list all the way from the left to

the right to find the smallest element and I will return that.

Okay? So

[COUGH] this is where pseudo-code allows me, gives me wiggle room to play with how

much description or how much detail I need to give and the algorithm description.

This is acceptable pseudo-code, this is acceptable pseudo-code,

this is not acceptable in Python or in C Plus Plus or in Pascal.

This, if it is translated to proper Python, this will be acceptable,

this is very detailed and this, you know, in terms of instead of putting left arrow,

I would put equal.

In terms of mathematical symbol of infinity,

I will have to put proper thing in Python.

But this is basically would translate one to one, line for line into Python.


But again, in terms of what am I trying to achieve,

this is not telling my anything more than this.

In fact, I would argue that this is more readable than this.

But again, if I say how long does it take to find the minimum element in the list?

It's not easy to, to answer that question with this, because okay,

you are telling me that I find the smallest element.

It is easy to answer this,

if the list has n elements, this is going to take on the order of n operation.

Why it's not easy to find, to say, what is the running time of this?

You might say, well, look this is how I would find the minimum element.

That's not necessarily always the case.

I will give you another way of finding

the minimum element which is [SOUND]

sort the list L in increasing order, return, L0.


This is another pseudo-code that is doing exactly the same like this in terms of

what we want to achieve.

It is sorting the list L in increasing order,

returning the first element in L after it is sorted.

Now notice, this is different than this, different than this.

They are, all three of them are finding the minimum element in the list.

This is going to differ from that in terms of the details.

And also is going to differ in terms of the running time.

This one here for example, what is the time it takes to sort the list?

Returning this is probably one operation.

If I can go to that first,

first element in the list in one operation, then this is not going to take

many operation are going to take a small number of operations.

But how long does it take sort?

So now you start seeing that pseudo-code gives me this flexibility of,

in very simple readable way, describing what I want to do, like this.

But also it allows me, the flexibility to specify exactly how I want to do it.

Here, I'm saying do it like this, sort the list, return the first element.

This is going to be correct, is going to return the smallest element.

This one I'm saying,

scan the list, in, in, in order from left to right and find the smallest element.

This one doesn't tell me anything about how.


Of course, when you write something in a real programming language Python,

C Plus Plus or Java for example, you cannot do this,

you cannot get away with this.

You have to know exactly how it is implemented and how the, all the details.

You have to figure out the details, are you going to be doing this, are you going

to writing a sorting function, sorting and then returning the first element?

So, this is the why we use pseudo-code.

I describing an algorithm like this, look at this here in one line I said, sort

the list, there's nothing ambiguous about it, sort the list in increasing order.

Right? There's nothing ambiguous.

If I wanted to write this in Python,

I have to write a long piece of code that in fact, does actually the sort.


Whereas in, in pseudo-code it was this magic line says, sort in increasing order.

I don't need to describe anything more because it's very well defined.


So it allows me again, to abstract things out,

while still maintaining readability and understanding of what I want.

I want the smallest element, at the same time if I decide to go

into more details so that one understands exactly how I want it to be done,

I can use the pseudo-code as well to achieve that.


So this is why we use pseudo-code, it's a very high level language,

abstract, has flexibility it allows me to write things in English,

it allows me to use mathematical symbols and so on.

But at the same time, it's, it'a efficient to describe what I want to do.


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