Rework packaging intro and Python packaging

03_building_and_packaging/intro_slides.md

@@ -30,7 +30,7 @@ slideOptions:
 ## Learning goals of chapter
 
 - Explain why software is packaged.
-- Create Python packages, publish on PyPI, and install with pip.
+- Create a distributable package of a Python code, publish on PyPI, and install with pip.
 - Understand the difference between static and dynamic libraries and common ways of installation on Linux.
 - Build C++ software and handle dependencies with Make and CMake.
 - Package C++ software with CPack and create Debian packages.
@@ -42,17 +42,17 @@ slideOptions:
 
 - Bare code is often hard to understand for everyone except the developer(s).
 - Packaging is a workflow to convert a code into a standardized distributable software.
-- A code can be standardized in various ways. Some examples are
-    - creating a compact form by following a standardization.
-    - providing an installation recipe, for example, using CMake / make.
-    - bundling code into an app or software with some UI.
-- We discuss **creating a compact form by following a standardization**.
+- A code can be standardized in various ways. For example, by ...
+    - ... providing an installation recipe, for example, using CMake / make.
+    - ... bundling it into an app or software with a user interface.
+    - ... packaging it according to an existing standard.
+- We discuss **packaging a code according to an existing standard**.
 
 ---
 
 ## Why should we package code? 1/2
 
-- A bare code with many files typically has difficulties like
+- A code with many files typically has difficulties like
     - multiple dependencies and requirements of specific versions of dependencies.
     - intricate compilation / installation steps which are hard to get right.
     - missing or limited starting information / documentation, which means a high entry barrier.
@@ -62,7 +62,7 @@ slideOptions:
 ## Why should we package code? 2/2
 
 - Create a package to
-    - benefit from a package index or package manager which is familiar for a broad audience.
+    - benefit from a package index or package manager which is familiar to a broad audience.
     - benefit from automated handling of dependencies of package managers.
     - have ease of distribution and maintenance due to standardization.
     - increase overall usability and sustainability of your code.
@@ -73,20 +73,21 @@ slideOptions:
 
 - First step is finding the right standard for your code.
 - There are several options:
-    - One of the many Linux package managers: apt, dpkg, yum, RPM and many more ...
-    - [CMake](https://cmake.org/) <span>: building / installation / packaging tool mostly for C, C++ projects<!-- .element: class="fragment" data-fragment-index="1" --></span>
-    - [Spack](https://spack.io/) <span>: a package management tool mostly for supercomputing centers<!-- .element: class="fragment" data-fragment-index="1" --></span>
-    - [Conan](https://conan.io/) <span>: open-source package manager for C and C++ development<!-- .element: class="fragment" data-fragment-index="1" --></span>
-    - [PyPI](https://pypi.org/) and [pip](https://pypi.org/project/pip/)
+    - Linux package managers: apt, dpkg, yum, RPM, etc.
+    - [CMake](https://cmake.org/)
+    - [Spack](https://spack.io/)
+    - [Conan](https://conan.io/)
+    - [pip](https://pypi.org/project/pip/)
     - [Conda](https://docs.conda.io/en/latest/)
+    - and many more ...
 
 ---
 
 ## Why do we look at packaging a Python code?
 
 - Python is easy to understand and widely used in research software.
-- A well established packaging workflow already exists in the Python community.
-- Various examples of packaged codes already exist: [NumPy](https://pypi.org/project/numpy/), [SciPy](https://pypi.org/project/scipy/), [PyTorch](https://pypi.org/project/torch/) and more ...
+- Well established package managers and packaging tools already exist in the Python community.
+- Several examples of packaged codes: [NumPy](https://pypi.org/project/numpy/), [SciPy](https://pypi.org/project/scipy/), [PyTorch](https://pypi.org/project/torch/).
 
 ---
 
@@ -95,4 +96,4 @@ slideOptions:
 - Packaging or creating build recipe of a code is a standardized process.
 - Many options in packaging / building tools.
 - Most of these tools / methods are customized for use cases.
-- In this lecture we will concentrate on packaging of Python code.
+- In this lecture, we concentrate on packaging of Python code.

03_building_and_packaging/pip_demo.md

@@ -73,11 +73,3 @@ pip show nutils
 ```bash
 python -m pip install package-name
 ```
-
-## 4. How to read a PEP
-
-- Have a look at [PEP 8](https://peps.python.org/pep-0008/)
-
-## 5. Understanding a PyPI package webpage
-
-- Having a look at [fenicsprecice](https://pypi.org/project/fenicsprecice/)