Applications with Python
System Programming with Python
"System focused programming" might be the better term than "System Programming".
System programming or systems programming means often only the activity of "programming
system software", programs which are often part of the operating system.
Our topics in this section of our online course deal with Pipes, Threads and Forks and starting and
using shell commands and scripts from a Python script.
Python has various modules to support system focused programming.
The sys module is introduced in the first chapter. A focal point are the data streams (stdin, stdout, stderr) and redirections of streams.
The interaction between is the focus in the following chapter of our course.
The interaction between Python and the Linux Shell is another topic of our advanced section. This chapter is followed by Forks and Forking.
You can learn more about threads and threading in our Introduction into Threads. We show how to find the active IP addresses in a local network by using forks.
The chapter, which is subtitled as "Pipe, Pipes and '99 Bottles of Beer'" might be interesting to teetotallers as well, because it's not about alcohol but dealing with alcohol, even though the "99 bottles of beer" in the title give the impression. Instead, we show you how to write a program which is construing the famous American song "99 bottles of beer" by using forked processes and Pipes. So, if you need a good example of pipes and forks working together you will find it here.
Graph Theory
We have three chapters dealing with Graphs.- A general introduction into the Graph theory and the corresponding Python code can be found in "Graphs in Python" You will also here the implementations of a graph class with essential functionalities for graph creation, manipulation and calculations.
- Introduction into the module pygraph
- Introduction into the module NetworkX
Mathematics
- In our chapter on Polynomials we demonstrate how easily and beautifully a class for the creation and manipulation of polynomial functions can be written in Python.
Computer Science and Computer Linguistics
Finite State Machines are not only used in computer science but in natural language processing as well. We cover the concept of the Finite State Machine in great detail, so that even an amateur in Computer Science can understand the examples. At least we hope so.Alan Turing's Turing Machines and above all the underlying theory is a must for every computer scientist. We show a simple implementation of a Turing Machine.
If you are interested in Classifying documents, the Introduction into Text Classification using Naive Bayes and our Python Implementation of Text Classification will be the right chapters for you.
Music
It's also possible to create scores with Python: You can find a complete working example in Creating Musical Scores With PythonIf you feel that the above topics are too complicated or sophisticated for you, you might like our course for beginners in Python. You find a documented link list in the following lines:
Databases with Python
An introduction into using database interfaces in Python for SQL, MySQL and SQLite"Games"
What you find are not real games! We show a recursive solution to Towers of Hanoi and a game Cows and Bulls better known in a commercial version called "Mastermind".Online Course
Further Topics
News
January 2021:
Read my new chapter on "Pandas Groupby" (Bernd)
December 2020:
Create your own creative birthday or christmas card? Let Python be creative for you. In my chapter
"Word Clouds"
I show you how to create beautiful wordclouds! (Bernd)
November 2020:
Predicting the Future? How would it be to know the price of objects, shares or currencies in the future? Impossible. Yes and no! Machine Learning makes it possible to have a small glimpse in the futures. Read my new chapter on "Regression" to see how your wishes may come true :-) (Bernd)
November 2020:
Do you like curry and currying? I have corrected some typos in the chapter "Currying with Python". Furthermore I improved the explanations and the code examples! Thanks a lot Larry for your hints!
(Bernd)
September 2020:
In my new article "Encoding Text for Machine Learning", I show how texts, like newspaper articles, books or the like, can be converted into numerical values. You need this conversion if you want to edit natural-language texts with neural networks. This is done with the help of the bag-of-words method. I also added a chapter in which I present some interesting text classification examples:
"Natural Language Processing: Examples"
(Bernd)
September 2020:
One of the most visited chapters of my Python tutorial has the title Recursion and Recursive Functions. Have you ever heard about tribonacci, tetranacci, or pentranacci numbers? Most probably not. I haven't known them until this day.
(Bernd)
August 2020:
I have improved the tutorial on functions. A smoother introduction, i.e. the call behavior and the parameter transfer are now introduced in easy-to-understand diagrams. Furthermore a lot of additional exercises with solutions round off the topics. Concerning Machine Learning: I added a new chapter on metrics (precision, accuracy, recall, f1-score)(Bernd)
August 2020:
Today I finally took the Python2 tutorial offline. Python2 should finally be history. I also reorganized the existing content. Up to now there was an "Advanced" rubric, which did not provide actual Python topics but applied Python programming. I have renamed it to Applications. I have also added a new section "Advanced". This time with advanced Python topics. Object orientation received a section of its own now. We still keep a link to the outdated Python2 tutorial, just in case!
(Bernd)
June 2020:
I added three new chapters in the section "Machine Learning": Finally, I added a proper introduction chapter, "Representation and Visualization of Data" and "Train and Test Sets" (Bernd)
June 2020:
We are proud to present a new Turkish sibling of our website. Python-kurslari.eu. Thanks to the work of Melisa Atay and Barbaros Akkurt.
June 2020:
I (Bernd) revised the chapter "Python Iterators and Generators"
May 2020:
Bernd changed the chapter on "Magic Methods and Operator Overloading". He added further examples of the __call__ method and sharpened the explanations a bit more.
April 2020:
Great news: The listings in the Python tutorial are getting more colorful. Melisa Atay works hard to turn the existing html files into Jupyter Notebooks, which get automatically transformed into html. This way the code listings get syntax highlighting. She also checks the tests and examples by doing this.
February 2020:
Bernd Klein finally finished two new chapters of my machine learning tutorial:
- Lots of people are afraid of Neural Networks but they can be so easy to understand. I hope you will see what I mean, if you have a look at my chapter "From Dividing Lines to Neural Networks"
- The sequal of my previous chapter: Simple Neural Networks and Linearly Separable Data Sets
November 2019:
After having worked so much on Numpy, Matplotlib and Pandas, I (Bernd) concentrated on pure Python. I continued the journey into the the depth of properties. You can join me: "Deeper into Properties" One step further: "Descriptors"
October 2019:
I added a new chapter to the Pandas Tutorial: Replacing Values in DataFrames and Series
September 2019:
I reshaped most of the chapters of my Matplotlib Tutorial:
- The Introductory chapter of the Matplotlib Tutorial
- Spines and Ticks
- Python and Matplotlib Legends and Annotations
- Subplot of Matplotlib
- Using Gridspec to be more flexible with Subplots
- Histogram and Barplots
August 2019:
It was long overdue. Finally we have a chapter on pytest
Juli 2019:
I wrote a new chapter with an extensive example of multiple inheritance in Bursa and Istanbul and did the final touches on a train from Geneva to Zurich. The underlying ideas have arisen while giving Python courses in various locations. The examples were nearly finished as well. All I did in Turkey was writing the explanatory text.
June 2019:
The Chapter on Inheritance has been nearly completely rewritten. Instead of using the old and boring "employee" and "person" classes, we are now using the Robot, which we have also used in our Introduction into OOP. You will meet the robot Marvin and his new friends "James" and "Dr. Frankenstein"!
April 2018:
A completely new chapter An Extensive Example for Sets was added to our tutorial. This chapter is supplementing the chapter Sets and Frozensets
October 2017:
In our chapter on Polynomials we demonstrate how easily and beautifully a class for the creation and manipulation of polynomial functions can be written in Python.
January - March 2017:
We extended our chapters on Generators and Decorators
May 2016:
New chapter on Decorators. In combination with our chapter on Memoisation and Decorators it belongs to the most extensive treatisises on the topic of decoration à la Python!
December - March 2016:
We wrote four chapters dealing with abstract classes as a tutorial on Metaclasses:
- Classes and Class Creation
- On the Road to Metaclasses
- Metaclasses
- Count Method Calls Using a Metaclass
We added a chapter on Slots and another about the difference between type and classes.
July 2014:
An introduction into using database interfaces in Python for SQL, MySQL and SQLite
March 2014:
We are currently completely revising the chapter on object oriented programming. It's more or less complete rewrite. The old version dealing with OOP can still be accessed, though we recommend to work through the new ones.
The topic now comprises five instead of previously only one chapter:
Our Next Training Courses
Our next open Python classes with Bernd Klein, the author of this website:
Due to the corona pandemic, we are currently running all courses online. Further Information!
Amsterdam:
Python Course for Data Analysis and Machine Learning
22 - 26 Feb 21 3 - 7 May 21
Python Course for Beginners
25 - 29 Jan 21 22 - 26 Mar 21 19 - 23 Apr 21 7 - 11 Jun 21
Python Intensive Course
17 - 19 Feb 21 24 - 26 Mar 21 19 - 21 May 21 23 - 25 Jun 21
Python Seminar for Engineers and Scientists
18 - 20 Jan 21 24 - 26 Mar 21 19 - 21 May 21
Python Text Processing and Computer Linguistics Course
21 - 25 Jun 21
Cologne:
Python Course for Data Analysis and Machine Learning
22 - 26 Feb 21 3 - 7 May 21
Python Course for Beginners
25 - 29 Jan 21 22 - 26 Mar 21 19 - 23 Apr 21 7 - 11 Jun 21
Python Intensive Course
17 - 19 Feb 21 24 - 26 Mar 21 19 - 21 May 21 23 - 25 Jun 21
Python Seminar for Engineers and Scientists
18 - 20 Jan 21 24 - 26 Mar 21 19 - 21 May 21
Python Text Processing and Computer Linguistics Course
21 - 25 Jun 21
Frankfurt:
Python Course for Data Analysis and Machine Learning
22 - 26 Feb 21 3 - 7 May 21
Python Course for Beginners
25 - 29 Jan 21 22 - 26 Mar 21 19 - 23 Apr 21 7 - 11 Jun 21
Python Intensive Course
17 - 19 Feb 21 24 - 26 Mar 21 19 - 21 May 21 23 - 25 Jun 21
Python Seminar for Engineers and Scientists
18 - 20 Jan 21 24 - 26 Mar 21 19 - 21 May 21
Python Text Processing and Computer Linguistics Course
21 - 25 Jun 21
Hamburg:
Python Course for Data Analysis and Machine Learning
22 - 26 Feb 21 3 - 7 May 21
Python Course for Beginners
25 - 29 Jan 21 22 - 26 Mar 21 19 - 23 Apr 21 7 - 11 Jun 21
Python Intensive Course
17 - 19 Feb 21 24 - 26 Mar 21 19 - 21 May 21 23 - 25 Jun 21
Python Seminar for Engineers and Scientists
18 - 20 Jan 21 24 - 26 Mar 21 19 - 21 May 21
Python Text Processing and Computer Linguistics Course
21 - 25 Jun 21
Online-Schulungen:
Python Course for Data Analysis and Machine Learning
22 - 26 Feb 21 3 - 7 May 21
Python Course for Beginners
25 - 29 Jan 21 22 - 26 Mar 21 19 - 23 Apr 21 7 - 11 Jun 21
Python Intensive Course
17 - 19 Feb 21 24 - 26 Mar 21 19 - 21 May 21 23 - 25 Jun 21
Python Seminar for Engineers and Scientists
18 - 20 Jan 21 24 - 26 Mar 21 19 - 21 May 21
Python Text Processing and Computer Linguistics Course
21 - 25 Jun 21
ParisBerlin, Munich:
Python Course for Data Analysis and Machine Learning
22 - 26 Feb 21 3 - 7 May 21
Python Course for Beginners
25 - 29 Jan 21 22 - 26 Mar 21 19 - 23 Apr 21 7 - 11 Jun 21
Python Intensive Course
17 - 19 Feb 21 24 - 26 Mar 21 19 - 21 May 21 23 - 25 Jun 21
Python Seminar for Engineers and Scientists
18 - 20 Jan 21 24 - 26 Mar 21 19 - 21 May 21
Python Text Processing and Computer Linguistics Course
21 - 25 Jun 21
Vienna, Salzburg or Linz:
Python Course for Data Analysis and Machine Learning
22 - 26 Feb 21 3 - 7 May 21
Python Course for Beginners
25 - 29 Jan 21 22 - 26 Mar 21 19 - 23 Apr 21 7 - 11 Jun 21
Python Intensive Course
17 - 19 Feb 21 24 - 26 Mar 21 19 - 21 May 21 23 - 25 Jun 21
Python Seminar for Engineers and Scientists
18 - 20 Jan 21 24 - 26 Mar 21 19 - 21 May 21
Python Text Processing and Computer Linguistics Course
21 - 25 Jun 21
Zürich, Schaffhausen, Bern, St. Gallen:
Python Course for Data Analysis and Machine Learning
22 - 26 Feb 21 3 - 7 May 21
Python Course for Beginners
25 - 29 Jan 21 22 - 26 Mar 21 19 - 23 Apr 21 7 - 11 Jun 21
Python Intensive Course
17 - 19 Feb 21 24 - 26 Mar 21 19 - 21 May 21 23 - 25 Jun 21
Python Seminar for Engineers and Scientists
18 - 20 Jan 21 24 - 26 Mar 21 19 - 21 May 21
Python Text Processing and Computer Linguistics Course
21 - 25 Jun 21
A Course is not a Course
The question is ambiguous. First we want to explain, why this website is called
"A Python Course". This website is seen all over the world
and the expression "course" has varying meanings in the English speaking world.
Both in the United States and Canada, a course is a teaching unit, which might last
e.g. one academic term. The students normally get a grade or some academic credit
for attending the course, usually after having passed an exam.
In the United Kingdom and Australia the term "course" usually defines the complete
programme of studies required to complete a major or a study path leading to a
university degree. The word "unit" is used in the UK to refer to an
academic course in the North American sense.
On the one hand, we had the US and Canadian sense in mind: Our Python is one teaching
unit and when you have successfully passed it, you are capable of programming
in Python. On the other hand, we had the original meaning of the word in mind:
A "course of instruction" as it might be used in book titles like "A Course in
Programming Python".