Harmonize pyproject.toml etc. across projects.

.gitignore

@@ -1,13 +1,13 @@
 # python
 *.egg-info
-*_version.py
 *.pyc
 *__pycache__
+*_version.py
 .mypy_cache
 
 # pytask
-.pytask*.sqlite3
 .pytask
+.pytask*.sqlite3
 
 # bld
 bld*
@@ -26,31 +26,32 @@ bld*
 *.vscode
 
 # slidev
-node_modules
-package-lock.json
-.DS_Store
-dist
 *.local
-index.html
+.DS_Store
 .remote-assets
-components.d.ts
 .slides_pdf
+components.d.ts
+dist
+index.html
+node_modules
+package-lock.json
 
 # nonsense
-desktop.ini
 *.bak
 *.tmp
+desktop.ini
 
 # jupyter-book
 site_*
 
+# jupyter
+.ipynb_checkpoints/
+
 # videos
 *.mp4
 
+# data
 gapminder.arrow
 
-.ipynb_checkpoints/
-
 # pixi environments
 .pixi
-*.egg-info

pyproject.toml

@@ -141,6 +141,8 @@ extend-ignore = [
     "S301",
     "S602", # `subprocess` call with `shell=True`.
     "T201",
+    "TC002",  # Move third-party import into a type-checking block
+    "TC003",  # Move standard library import into a type-checking block
     "TRY003",
 ]
 
@@ -158,12 +160,6 @@ convention = "google"
 
 [tool.pytest.ini_options]
 filterwarnings = []
-markers = [
-    "wip: Tests that are work-in-progress.",
-    "unit: Flag for unit tests which target mainly a single function.",
-    "integration: Flag for integration tests which may comprise of multiple unit tests.",
-    "end_to_end: Flag for tests that cover the whole program.",
-]
 norecursedirs = ["docs"]
 
 [tool.yamlfix]

src/epp_topics/plotting/what_to_plot/objectives_materials.ipynb

@@ -44,7 +44,7 @@
     "- [How Charts Lie](https://www.amazon.com/gp/product/0393358429) (Alberto Cairo).\n",
     "  Similar to Chapter 7 of Calling Bullshit, but the entire book is devoted to\n",
     "  visualisations.\n",
-    "- [The Functional Art](http://www.thefunctionalart.com/p/about-book.html) (Alberto\n",
+    "- [The Functional Art](https://thefunctionalart.blogspot.com/p/about-book.html) (Alberto\n",
     "  Cairo) and [Show Me the Numbers](http://www.perceptualedge.com/library.php) (Stephen\n",
     "  Few). Authoritative References if you want to become a data viz pro. Alberto Cairo has\n",
     "  an [interesting blog accompanying the book](http://www.thefunctionalart.com/). *Show\n",

src/epp_topics/projects/setup/objectives_materials.ipynb

@@ -27,7 +27,7 @@
     "\n",
     "Download the [slides](projects-setup.pdf).\n",
     "\n",
-    "Link to the [getting started section of the documentation](https://econ-project-templates.readthedocs.io/en/latest/getting_started/index.html)."
+    "Link to the [getting started section of the documentation](https://econ-project-templates.readthedocs.io/en/stable/getting-started/)."
    ]
   }
  ],

src/epp_topics/projects/setup/screencast/script.md

@@ -10,9 +10,9 @@ Give a brief motivation what the templates help to do:
 
 ## Where to get help (show docs)
 
-[Customising the template for your needs](https://econ-project-templates.readthedocs.io/en/stable/getting_started/index.html#customising-the-template-for-your-needs)
+[Customising the template for your needs](https://econ-project-templates.readthedocs.io/en/stable/customising-the-template/)
 
-## Create a github repo
+## Create a github repogetting_started/index.html#customising-the-template-for-your-needs
 
 - Go to https://github.com/OpenSourceEconomics/econ-project-templates
 - Click on "Use this template"+

src/epp_topics/projects/setup/screencast/slides.md

@@ -33,4 +33,4 @@ Janoś Gabler and Hans-Martin von Gaudecker
 
 # Getting started
 
-[Getting started page of the documentation](https://econ-project-templates.readthedocs.io/en/stable/getting_started/index.html)
+[Getting started page of the documentation](https://econ-project-templates.readthedocs.io/en/stable/getting_started/)

src/epp_topics/python_installation_execution_via_conda/installation_linux/instructions.md

@@ -25,7 +25,7 @@ We will cover the following topics:
 ## Installing mamba
 
 Go to
-[https://github.com/conda-forge/miniforge#download](https://github.com/conda-forge/miniforge#download)
+[https://github.com/conda-forge/miniforge?tab=readme-ov-file#unix-like-platforms-macos-linux--wsl](https://github.com/conda-forge/miniforge?tab=readme-ov-file#unix-like-platforms-macos-linux--wsl)
 and Download the Linux x86_64 version of the installer in your Downloads folder.
 
 ![0_download](0_download.png)

src/epp_topics/python_installation_execution_via_conda/installation_mac/instructions.md

@@ -27,7 +27,7 @@ you have an Intel processor.
 ## Installing mamba
 
 1. Go to
-   [https://github.com/conda-forge/miniforge#download](https://github.com/conda-forge/miniforge#download)
+   [https://github.com/conda-forge/miniforge?tab=readme-ov-file#unix-like-platforms-macos-linux--wsl](https://github.com/conda-forge/miniforge?tab=readme-ov-file#unix-like-platforms-macos-linux--wsl)
    and download the **OS X x86_64** version (for Intel processors) or the **OS X arm64**
    version (for Apple processors) of the installer in your Downloads folder.
 

src/epp_topics/python_installation_execution_via_conda/installation_windows/instructions.md

@@ -35,7 +35,7 @@ shells and conda environments.
 ## Installing mamba
 
 1. Go to
-   [https://github.com/conda-forge/miniforge#download](https://github.com/conda-forge/miniforge#download)
+   [https://github.com/conda-forge/miniforge?tab=readme-ov-file#windows](https://github.com/conda-forge/miniforge?tab=readme-ov-file#windows)
    and Download the Windows x86_64 version of the installer in your Downloads folder.
 
    ![0_download](0_download.png)

src/epp_topics/scientific_computing/randomness/objectives_materials.ipynb

@@ -28,7 +28,7 @@
     "\n",
     "Download the [slides](scientific_computing-randomness.pdf).\n",
     "\n",
-    "- This [Blogpost](https://albertcthomas.github.io/good-practices-random-number-generators/) explains some of the reasons behind our best practices.\n",
+    "- This [Blogpost](https://blog.scientific-python.org/numpy/numpy-rng/) explains some of the reasons behind our best practices.\n",
     "- If you find the \"legacy\" version of the NumPy random number generator somewhere (i.e., calling `np.random.seed`. E.g., LLMs are trained on lots of data using that...), a clear exposition of why you want to use the suggested version can be found [here](https://builtin.com/data-science/numpy-random-seed).\n",
     "\n",
     "## Quiz\n"