Add WuS notebook

.github/workflows/build_and_push_all_images.yml

@@ -221,6 +221,36 @@ jobs:
       e2xgrader_branch: ${{ inputs.e2xgrader_branch }}
     secrets: inherit
 
+  wus_notebook:
+    needs: [datascience_notebook]
+    uses: ./.github/workflows/build_image.yml
+    with:
+      force_build: ${{ inputs.force_build || needs.datascience_notebook.outputs.did_build_image == 'true' }}
+      registry: ${{ inputs.registry }}
+      base_image_name: ${{ inputs.registry }}/digiklausur/docker-stacks/datascience-notebook
+      base_image_tag: ${{ inputs.tag }}    
+      image_path: images/wus-notebook
+      image_name: wus-notebook
+      image_tag: ${{ inputs.tag }}  
+      push: ${{ inputs.push }}
+    secrets: inherit
+
+  e2x_wus_notebook:
+    needs: [wus_notebook]
+    uses: ./.github/workflows/build_e2xgrader_images.yml
+    with:
+      force_build: ${{ inputs.force_build || needs.wus_notebook.outputs.did_build_image == 'true' }}
+      registry: ${{ inputs.registry }}
+      image_name: wus-notebook
+      image_tag: ${{ inputs.tag }}
+      base_image_name: ${{ inputs.registry }}/digiklausur/docker-stacks/wus-notebook
+      base_image_tag: ${{ inputs.tag }}
+      push: ${{ inputs.push }}
+      e2xgrader_installation_source: ${{ inputs.e2xgrader_installation_source }}
+      e2xgrader_version: ${{ inputs.e2xgrader_version }}
+      e2xgrader_branch: ${{ inputs.e2xgrader_branch }}
+    secrets: inherit
+
   nlp_notebook:
     needs: [ml_notebook]
     uses: ./.github/workflows/build_image.yml

images/wus-notebook/Dockerfile

@@ -0,0 +1,22 @@
+ARG IMAGE_SOURCE=ghcr.io/digiklausur/docker-stacks/minimal-notebook:latest
+FROM $IMAGE_SOURCE
+
+LABEL maintainer="e2x project H-BRS <e2x@inf.h-brs.de>"
+LABEL description="e2x notebook for statistics course"
+LABEL org.opencontainers.image.description="e2x notebook for statistics course"
+LABEL org.opencontainers.image.authors="e2x project H-BRS <e2x@inf.h-brs.de>"
+
+USER root
+# Copy nbgrader wus config
+COPY configs/nbgrader_config.py /opt/conda/etc/jupyter/nbgrader_config.py
+RUN chown root:"$NB_GID" /opt/conda/etc/jupyter/nbgrader_config.py &&\
+    chmod g+rwX /opt/conda/etc/jupyter/nbgrader_config.py
+
+USER $NB_USER
+
+# Disable execute time extension and enable highlight word
+RUN jupyter nbextension disable --sys-prefix execute_time/ExecuteTime \
+    && pip install --no-cache-dir jupyter_highlight_selected_word \
+    && jupyter nbextension install --py --sys-prefix jupyter_highlight_selected_word \
+    && jupyter nbextension enable --sys-prefix highlight_selected_word/main \
+    && jupyter nbextension list

images/wus-notebook/README.md

@@ -0,0 +1,54 @@
+# e2x Data Science Notebook
+
+TThis Docker image is a customized version of the [e2x Data Science Notebook](../datascience-notebook) image, with certain extensions specific to the WuS course at H-BRS installed.
+
+## Build Args
+
+The following build arg is available:
+
+* `IMAGE_SOURCE`: The base image to use for the build. Defaults to `ghcr.io/digiklausur/docker-stacks/datascience-notebook:latest`.
+
+## Description
+
+This image is designed to provide a comprehensive Jupyter Notebook environment for data science tasks, building on top of the e2x Minimal Notebook image. It includes:
+
+* All features from the e2x Minimal Notebook image
+* A collection of popular Python data science libraries, including NumPy, Pandas, SciPy, Matplotlib, Scikit-learn, and more
+
+## Versions
+
+This images comes as a basic data science image or with `e2xgrader` installed and a specific mode activated.
+For more information look at the [E2xGrader Notebook](../e2xgrader-notebook) image and the [e2xgrader](https://github.com/Digiklausur/e2xgrader) package.
+
+* `wus-notebook`
+    + Base WuS science image
+* `wus-notebook-teacher`
+    + Base data science image with `e2xgrader` teacher mode activated (includes grading tools)
+* `wus-notebook-student`
+    + Base data science image with `e2xgrader` student mode activated (includes extensions for students)
+* `wus-notebook-exam`
+    + Base data science image with `e2xgrader` student_exam mode activated (provides a restricted notebook for students in an exam)
+
+## Usage
+
+### Pull and Run
+
+To pull and run the image use:
+
+`docker run -p 8888:8888 ghcr.io/digiklausur/docker-stacks/wus-notebook:latest`
+
+Available tags are `latest` and `dev`. Available registries are `quay.io` and `ghcr.io`.
+
+### Build and Run
+
+To build the image from the standard source, run:
+
+`docker build -t wus-notebook:dev .`
+
+To build the image from a custom source, run:
+
+`docker build -t wus-notebook:dev . --build-arg="IMAGE_SOURCE=<your_base_image>:<your_tag>"`
+
+To run the image, use:
+
+`docker run -p 8888:8888 wus-notebook:dev`

images/wus-notebook/configs/nbgrader_config.py

@@ -0,0 +1,102 @@
+from e2xgrader.config import configure_base
+from nbgrader.preprocessors import GetGrades
+from nbformat import NotebookNode
+from nbconvert.exporters.exporter import ResourcesDict
+from nbgrader.api import MissingEntry
+from nbconvert.preprocessors import CSSHTMLHeaderPreprocessor
+from e2xgrader.preprocessors import FilterTests
+
+from e2xgrader.graders import MultipleChoiceGrader, CodeGrader, SingleChoiceGrader
+from e2xgrader.utils.extra_cells import get_choices, get_instructor_choices
+from traitlets import Unicode
+
+class GetGradesWithUngradedComment(GetGrades):
+    """
+    If a cell has not been graded, this processor adds a comment 
+    saying "Unbewertet" to the cell
+    """
+
+    ungraded_comment = Unicode(
+        "Unbewertet",
+        help="Comment to add to ungraded cells"
+    ).tag(config=True)
+
+    def _get_comment(self, cell: NotebookNode, resources: ResourcesDict) -> None:
+        """Graders can optionally add comments to the student's solutions, so
+        add the comment information into the database if it doesn't
+        already exist. It should NOT overwrite existing comments that
+        might have been added by a grader already.
+
+        """
+        comment = self.gradebook.find_comment(
+            cell.metadata['nbgrader']['grade_id'],
+            self.notebook_id,
+            self.assignment_id,
+            self.student_id)
+
+        needs_manual_grade = False
+        try:        
+            grade = self.gradebook.find_grade(
+                cell.metadata['nbgrader']['grade_id'],
+                self.notebook_id,
+                self.assignment_id,
+                self.student_id)
+            needs_manual_grade = grade.needs_manual_grade
+        except MissingEntry:
+            pass
+
+        comment = comment.comment
+
+        if comment is None:
+            comment = ""
+        else:
+            comment += "\n"
+
+        # save it in the notebook
+        if needs_manual_grade:
+            cell.metadata.nbgrader['comment'] = comment + self.ungraded_comment
+        else:
+            cell.metadata.nbgrader['comment'] = comment
+
+
+class WuSMultipleChoiceGrader(MultipleChoiceGrader):
+
+    def determine_grade(self, cell, log=None):
+        '''
+        Grader for multiple choice questions
+        
+        Only give full points if student did select all correct 
+        answers and no incorrect answers
+        '''
+        max_points = float(cell.metadata['nbgrader']['points'])
+        student_choices = get_choices(cell)
+        instructor_choices = get_instructor_choices(cell)
+
+        # Return 0 points if the student did not select all correct answers
+        for choice in instructor_choices:
+            if choice not in student_choices:
+                return 0, max_points
+
+        # Return 0 points if the student did select an incorrect answer
+        for choice in student_choices:
+            if choice not in instructor_choices:
+                return 0, max_points
+
+        return max_points, max_points       
+
+c = get_config() # noqa: F821
+
+c.GenerateFeedback.preprocessors = [
+    GetGradesWithUngradedComment,
+    FilterTests,
+    CSSHTMLHeaderPreprocessor
+]
+
+#print("Local config is", c)
+
+c.SaveAutoGrades.graders = {
+    'multiplechoice': WuSMultipleChoiceGrader(),
+    'code': CodeGrader(),
+    'singlechoice': SingleChoiceGrader()
+}
+