Updates 12-24 (#27)

* update section 1 and main section

* update links section 2 and 3

* update link 4

* update link 5

Author: iulusoy

Material_Part1_PEP/README.md

@@ -14,7 +14,7 @@ You can find a list of PEPs [here](https://peps.python.org/).
 
 1. Line length  
 Don't write lines that are very long. Reason: Often you would use multiple windows next to each other and that makes it hard to read code (and possibly lead to introduction of bugs).  
-PEP 8 recommends lines no longer than 79 characters, but 90 is also a good number.
+PEP 8 recommends lines no longer than 79 characters, but 90 is also used quite often.
 
 1. Alignment of code  
 Make use of indentation when using continuation lines:  
@@ -128,11 +128,11 @@ Make use of indentation when using continuation lines:
     - use two leading underscores to invoke name mangling for attributes that should not be used in subclasses of the parent class (`__only_parent`)
     - double leading and trailing underscores for "magic" objects (dunder methods) - `__init__`, `__str__`
 
-**Task 1: [GitHub assignment PEP right or wrong?](https://classroom.github.com/a/OQSBs2Ey)**
+**Task 1a: [GitHub assignment PEP right or wrong?](https://classroom.github.com/a/Vg9Rjdry)**
 
 Please checkout the assignment repo and mark the answers in the file `chapter1/PEP_right_or_wrong.md` using markdown. Commit your answer to a new branch and open a pull request. If the autograding/CI checks succeed, you have marked the correct answers and can merge the pull request with main to submit your assignment.
 
-**Task 2: [GitHub assignment PEP fixme's](https://classroom.github.com/a/gH7zaDzE)**
+**Task 1b: [GitHub assignment PEP fixme's](https://classroom.github.com/a/zEgcY5ds)**
 
 Please checkout the assignment repo and correct the files `chapter1/example1.py`, `chapter1/example2.py` and `chapter3/example1.py` for stylistic and other errors that contradict PEP 8 recommendations. Commit your changes to a new branch and open a pull request. If the autograding/CI checks succeed, you have resolved all issues and can merge the pull request with main to submit your assignment.
 

Material_Part2_Linter/README.md

@@ -1,7 +1,7 @@
 # Linter
 A code linter is there to highlight issues with the code that do not conform with a style guide, and that may lead to errors when interpreted or compiled. For Python, a code linter makes sure that the code conforms with PEP 8 standards.
 
-**Task 3: [GitHub assignment code linter and formatter](https://classroom.github.com/a/8Naj1QMJ)**
+**Task 2: [GitHub assignment code linter](https://classroom.github.com/a/d0dI5zx_)**
 
 Please checkout the assignment repo and follow through with the commands below. Commit any changes to a new branch and open a pull request. If the autograding/CI checks succeed, you have completed all tasks and can merge the pull request with main to submit your assignment.
 
@@ -12,7 +12,7 @@ First, you need to install flake8. You can do so by typing
 ```
 pip install flake8
 ```
-in your terminal. Alternatively, you can install it via the `requirements.txt` in the assignment repo"
+in your terminal. Alternatively, you can install it via the `requirements.txt` in the assignment repo
 ```
 pip install -r requirements.txt
 ```

Material_Part3_Formatter/README.md

@@ -18,7 +18,9 @@ flake8 chapter2_3/example1.py
 ```
 You will notice that flake8 is not returning errors except a line length error for one of the comment lines: Note that black does not reformat comments other than inserting proper whitespace before and after the #.
 
-**Subtask (iii): Reformat `example1.py` and `example2.py` using black. Compare to your own reformatted files from the previous assignemt.**
+**Task 3: [GitHub assignment code formatter](https://classroom.github.com/a/nsZ7ryTk)**
+
+**Subtask (i): Reformat `example1.py` and `example2.py` using black. Compare to your own reformatted files from the previous assignemt.**
 
 ## Black configuration
 Sometimes you only want to check what black would actually reformat. In order to do so, run
@@ -29,12 +31,12 @@ or
 ```
 black chapter2_3/example1.py --diff --color
 ```
-**Task 3: Now you should have completed all edits on your assignment repo and should be able to submit the results (if the autograding and CI do not raise any issues).**
+**Now you should have completed all edits on your assignment repo and should be able to submit the results (if the autograding and CI do not raise any issues).**
 
 ## Black with jupyter notebooks
 The new versions of black directly allow you to run it on jupyter notebooks,
 
-**Subtask (iv): Try out reformatting notebooks with `example_jupyter.ipynb`.**
+**Subtask (ii): Try out reformatting notebooks with `example_jupyter.ipynb`.**
 
 
 ## Black with VSCode

Material_Part4_Pitfalls/README.md

@@ -1,6 +1,6 @@
 # Pitfalls: Common ways to introduce bugs in your Python code
 
-**Task 4: [GitHub assignment Python pitfalls](https://classroom.github.com/a/N7Scip_G)**
+**Task 4: [GitHub assignment Python pitfalls](https://classroom.github.com/a/XBSxiwZi)**
 
 Please checkout the assignment repo and follow through with the examples and instructions below. Commit any changes to a new branch and open a pull request. If the autograding/CI checks succeed, you have completed all tasks and can merge the pull request with main to submit your assignment.
 

Material_Part5_BetterCoding/README.md

@@ -1,6 +1,6 @@
 # Better coding
 
-**Task 5: [GitHub assignment write more readable code using these suggestions](https://classroom.github.com/a/jQ5QZphi)**
+**Task 5: [GitHub assignment write more readable code using these suggestions](https://classroom.github.com/a/98DEpTgF)**
 
 Please checkout the assignment repo and follow through with the examples and instructions below. Commit any changes to a new branch and open a pull request. If the autograding/CI checks succeed, you have completed all tasks and can merge the pull request with main to submit your assignment.
 

README.md

@@ -4,9 +4,9 @@
 # Python-best-practices-course
 Material for the course "Python best practices", Scientific Software Center, Heidelberg University
 
-Inga Ulusoy, June 2024
+Inga Ulusoy, December 2024
 
-Python has rapidly advanced to the most popular programming language in science and research. From data analysis to simulation and preparation of publications, all can be done in Python with appropriate libraries and implementing own modules. We will discuss most important Python Enhancement Proposals (PEP) and how these can help you write cleaner code. You will learn how to use a code linter and code formatter. Common pitfalls in Python will be explained with examples. We will demonstrate typical “bad programming” and how to code the examples in a more pythonic way.
+Python has rapidly advanced to the most popular programming language in science and research. From data analysis to simulation and preparation of publications, all can be done in Python with appropriate libraries and through implementing your own scripts, modules and packages. We will discuss some fundamental Python Enhancement Proposals (PEP) and how these can help you write cleaner code. You will learn how to use a code linter and code formatter. Common pitfalls in Python will be explained with examples. We will demonstrate typical “bad programming” and how to code the examples in a more pythonic way.
 
 ## Prerequisites
 Basic Python knowledge is required. Participants need a laptop/PC with a working Python environment installed, ideally in an IDE, and a GitHub account as we are using GitHub classrooms.
@@ -21,7 +21,7 @@ After the course participants will be able to
 ## Time and place
 The course takes place in the conference room of the Mathematikon Bauteil A (room 5/104).
 
-Course date: June 4th 2024, 9:00AM - 1:00PM 
+Course date: December 16th 2024, 9:00AM - 1:00PM 
 
 ## Course content
 
@@ -33,4 +33,4 @@ Course date: June 4th 2024, 9:00AM - 1:00PM
 
 ## Additional Topics
 
-For general coding best practices, you should always put your source code under version control, implement tests and a documentation, and also add a license to your code. It is not possible to discuss all of this in a short course - here we only discuss Python-specific content. The SSC offers [tailored courses](https://www.ssc.uni-heidelberg.de/en/learning/all-courses) that you can participate in. There is also a [block course](https://ssciwr.github.io/sustainable_development_course/) that touches on all these aspects; the block course takes place every year in February/March.
+For general coding best practices, you should always put your source code under version control, implement tests and a documentation, and also add a license to your code. It is not possible to discuss all of this in a short course - here we only present Python-specific content. The SSC offers [tailored courses](https://www.ssc.uni-heidelberg.de/en/learning/all-courses) that you can participate in. There is also a [block course](https://ssciwr.github.io/sustainable_development_course/) that touches on all these aspects; the block course takes place every year in February/March.