Merge remote-tracking branch 'upstream/master' into beta

docs/_static/grading-environment-r.yml

@@ -7,6 +7,8 @@ dependencies:
   - python=3.12
   - pip
   - nb_conda_kernels
+  - gcc_linux-64
+  - gxx_linux-64
   - r-base>=4.0.0
   - r-essentials
   - r-devtools

docs/_static/python_setup.sh

@@ -20,9 +20,9 @@ if [ $(uname -p) = "arm" ] || [ $(uname -p) = "aarch64" ] ; \
 fi
 chmod +x /autograder/source/mamba_install.sh
 /autograder/source/mamba_install.sh -b
-echo "export PATH=/root/mambaforge/bin:\$PATH" >> /root/.bashrc
+echo "export PATH=/root/miniforge3/bin:\$PATH" >> /root/.bashrc
 
-export PATH=/root/mambaforge/bin:$PATH
+export PATH=/root/miniforge3/bin:$PATH
 export TAR="/bin/tar"
 
 # install dependencies with mamba

docs/_static/r_setup.sh

@@ -25,9 +25,9 @@ if [ $(uname -p) = "arm" ] || [ $(uname -p) = "aarch64" ] ; \
 fi
 chmod +x /autograder/source/mamba_install.sh
 /autograder/source/mamba_install.sh -b
-echo "export PATH=/root/mambaforge/bin:\$PATH" >> /root/.bashrc
+echo "export PATH=/root/miniforge3/bin:\$PATH" >> /root/.bashrc
 
-export PATH=/root/mambaforge/bin:$PATH
+export PATH=/root/miniforge3/bin:$PATH
 export TAR="/bin/tar"
 
 # install dependencies with mamba

docs/debugging.rst

@@ -76,6 +76,34 @@ If you need to edit the submission file(s), they are located in the ``/autograde
 directory.
 
 
+Viewing the Executed Notebook
++++++++++++++++++++++++++++++
+
+To view the notebook with its outputs from grading, you can copy the ``results.pkl`` file out from
+the container and extract the notebook from it. On Gradescope, you would use SFTP to connect to the
+container while it's still running and download the file ``/autograder/results/results.pkl``. For
+local grading, run
+
+.. code-block:: console
+
+    docker cp <container id>:/autograder/results/results.pkl results.pkl
+
+to copy the file out of the container.
+
+Once you have obtained the ``results.pkl`` file, run this Python snippet to copy the notebook out of
+it.
+
+.. code-block:: python
+
+    import dill
+    import nbformat
+
+    with open("results.pkl", "rb") as f:
+        res = dill.load(f)
+
+    nbformat.write(res.notebook, "executed.ipynb")
+
+
 .. _debugging_with_otter_run:
 
 Debugging with Otter Run
@@ -85,3 +113,23 @@ Read the :ref:`previous section <debugging_container>` first. Because Otter Run
 autograder zip file for its configuration intsead of a Docker container, you will need to manually
 edit the ``otter_config.json`` file in your autograder zip file to set ``"debug"`` to ``true``.
 Then, re-zip the zip file's contents and use this new autograder zip file for ``otter run``.
+
+
+Viewing the Executed Notebook
++++++++++++++++++++++++++++++
+
+If you want access to the executed notebook when using Otter Run, you will need to call it from
+Python instead of using the CLI. Run a script like the one below to grade the submission and obtain
+the notebook.
+
+.. code-block:: python
+
+    import nbformat
+    from otter.api import grade_submission
+
+    # res is the GradingResults object, so you can examine it to see the score details
+    res = grade_submission("submission.ipynb", ag_path="autograder.zip", debug=True)
+    nbformat.write(res.notebook, "executed.ipynb")
+
+You can find details about the ``GradingResults`` class
+:ref:`here <workflow_executing_submissions_otter_run_grading_results>`.

docs/workflow/executing_submissions/otter_run.rst

@@ -69,6 +69,8 @@ console by the grading process during execution when set to ``True`` (default ``
 For more information about grading programmatically, see the :ref:`API reference <api_reference>`.
 
 
+.. _workflow_executing_submissions_otter_run_grading_results:
+
 Grading Results
 +++++++++++++++