Skip to main content

Documentation Index

Fetch the complete documentation index at: https://mintlify.com/elenacarino-max/Pildora4_ext_StarWars/llms.txt

Use this file to discover all available pages before exploring further.

The repository is designed so that a technology failure never has to cancel the learning activity. Alongside the Streamlit application, the root-level notebooks/ and docs/ directories contain a complete set of offline fallback materials — Jupyter notebooks for live coding and practice, plus DOCX documents for students and instructors. None of these materials depend on Docker, a running MLflow server, or network connectivity: they are self-contained and can be used on any machine with Python and Jupyter installed, or even printed in advance as a paper-based backup.

​
When to use contingency

Switch to contingency materials in any of the following situations:
  • The Streamlit application fails to start or crashes during a session.
  • The classroom network or lab infrastructure is unavailable.
  • Docker is not installed or cannot build the image on the available machines.
  • The deployed instance at pildora4extstarwars-14.streamlit.app is unreachable.
  • You need to run a session on a machine that cannot meet the Docker or Python 3.12 requirements.

​
Jupyter notebooks — live coding

The notebooks/01_live_coding/ directory contains three versions of the same live-coding session, each targeting a different role or phase of the class.

Live_Coding_COMPLETO.ipynb

Complete reference version for instructors. Contains all cells filled in with working code and explanatory markdown. Use this as the authoritative reference while preparing or as a fallback reference during class.

Live_Coding_DEMO_SEGURA.ipynb

Recommended version for classroom demonstration. Structured for safe live delivery — instructors type and explain each step as students watch. This is the primary contingency notebook for projected live coding.

Live_Coding_PARA_RELLENAR.ipynb

Student version with blanks to fill in. Provides scaffolding and context cells while leaving the key MLflow calls for students to complete. Distribute this file to students as the hands-on alternative to the app chambers.

​
Jupyter notebooks — practice

The notebooks/02_practica/ directory contains three progressive practice notebooks that mirror the mission structure of the app.

01_Tracking_Ejercicios.ipynb

Initial tracking exercises. Introduces mlflow.set_experiment, mlflow.start_run, log_params, log_metrics, log_artifact, and log_model through guided exercises on the Digits dataset. The equivalent of the six app chambers in notebook form.

02_Archivos_Jedi_SOLUCION.ipynb

Complete solution reference. The fully worked solution to the practice exercises, covering all three mission configurations (Tatooine, Coruscant, Mustafar). Use this to unblock students or as an instructor answer key.

03_Orden_66_RETO.ipynb

Final challenge for students. An open-ended notebook challenge that requires students to apply the full tracking cycle independently — the equivalent of the app’s final mission and defense phase.

​
Printed materials

The docs/ directory at the repository root contains DOCX files for both students and instructors. These are the most infrastructure-independent contingency option: print them before any classroom session and keep physical copies on hand.

Misiones_ALUMNADO_DIGITS.docx

Located at docs/alumnado/Misiones_ALUMNADO_DIGITS.docx. Student mission sheets and holocron cards. Contains the written descriptions of each mission objective, the code templates students must complete, and the holocron task cards. Distribute one copy per team when the app is unavailable.

Guion_PROFESORAS_DIGITS.docx

Located at docs/profesorado/Guion_PROFESORAS_DIGITS.docx. Teacher preparation and delivery guide. Contains session timing, facilitation notes, and the script for introducing each phase of the activity. Essential reading before any session.

Misiones_PROFESORADO_DIGITS.docx

Located at docs/profesorado/Misiones_PROFESORADO_DIGITS.docx. Teacher correction guide. Provides expected solutions and evaluation criteria for every mission so instructors can assess student work without the app’s automated validation.

​
Running notebooks

To run any notebook from the contingency set:
  1. Ensure Python 3.12 and the project dependencies are installed: 
    pip install -r app-v2/requirements.txt
  2. Launch JupyterLab or Jupyter Notebook from the repository root: 
    jupyter lab
# or
jupyter notebook
  3. Navigate to the appropriate notebook under notebooks/01_live_coding/ or notebooks/02_practica/ and open it.
No MLflow server, Docker, or network connection is required. MLflow will create a local mlruns/ directory in the working folder to store tracking data when the notebook is run.
Never delete the notebooks/ or docs/ folders from the repository. These directories are the contingency plan. If the application is unavailable during a session, they are the only way to continue the activity without starting over. Treat them with the same importance as the application code.
Before every classroom session, print at least one copy of Misiones_ALUMNADO_DIGITS.docx and Misiones_PROFESORADO_DIGITS.docx and keep them with your session materials. A physical backup costs nothing and eliminates the risk of a complete activity cancellation due to infrastructure failure.

Build docs developers (and LLMs) love

Get started for freeTalk to us