QuantEcon Python Lectures Assistant

Expert assistant for the QuantEcon Intermediate Quantitative Economics with Python lecture materials repository (QuantEcon/lecture-python.myst). Provides comprehensive guidance on environment setup, build processes, content editing, and troubleshooting for this Jupyter Book-based educational project.

What This Skill Does

This skill enables you to effectively work with the QuantEcon lecture materials repository by providing detailed knowledge of:

Instructions

1. Environment Setup and Bootstrap

When setting up the repository environment:

**Execute these commands in order and NEVER CANCEL in-progress installations:**

```bash

1. Create conda environment (3-5 minutes)

conda env create -f environment.yml

2. Activate environment (required for all subsequent work)

source /usr/share/miniconda/etc/profile.d/conda.sh

conda activate quantecon

3. Install PyTorch with CUDA support (3-5 minutes)

pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu128

4. Install Pyro (10 seconds)

pip install pyro-ppl

5. Install JAX with CUDA support (30 seconds)

pip install --upgrade "jax[cuda12-local]==0.6.2"

6. Install NumPyro (5 seconds)

pip install numpyro

7. Validate JAX installation (5 seconds)

python scripts/test-jax-install.py

```

**Key environment details:**

2. Build Process Management

When building the lectures:

**HTML build (primary target, 45-60 minutes):**

```bash

jb build lectures --path-output ./ -W --keep-going

```

**PDF build via LaTeX (30-45 minutes):**

```bash

jb build lectures --builder pdflatex --path-output ./ -n -W --keep-going

```

**Jupyter notebook build (30-45 minutes):**

```bash

jb build lectures --path-output ./ --builder=custom --custom-builder=jupyter -n -W --keep-going

```

**CRITICAL:** Set timeouts to 90+ minutes and NEVER CANCEL these commands. They execute 80+ notebooks sequentially.

3. Repository Navigation

**Key directories:**

**Important files:**

4. Content Editing Workflow

When modifying lecture content:

1. Always activate environment first: `conda activate quantecon`

2. Edit MyST markdown files in `lectures/` directory

3. Test changes with subset build if possible

4. Run full HTML build for complete validation

5. Verify outputs in `_build/html/` directory

**Content format:** MyST markdown with embedded executable Python code blocks

5. Validation and Testing

After making changes, run these validation steps:

```bash

1. Verify environment

python scripts/test-jax-install.py

2. Check installed packages

conda list | grep -E "(jax|torch|jupyter-book)"

3. View repository structure

ls -la

4. Check lecture files

ls lectures/ | head -10

5. Start build and monitor first few notebooks

jb build lectures --path-output ./ -W --keep-going

```

6. Troubleshooting Guidance

**Expected warnings (these are normal):**

**Performance expectations:**

**Common issues:**

7. CI/CD Awareness

The repository uses GitHub Actions with:

Local builds should match CI behavior and timing expectations.

Usage Examples

**Complete environment setup:**

```bash

Run full bootstrap sequence

conda env create -f environment.yml && \

source /usr/share/miniconda/etc/profile.d/conda.sh && \

conda activate quantecon && \

pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu128 && \

pip install pyro-ppl && \

pip install --upgrade "jax[cuda12-local]==0.6.2" && \

pip install numpyro && \

python scripts/test-jax-install.py

```

**Quick environment verification:**

```bash

conda activate quantecon

python scripts/test-jax-install.py

conda list | grep -E "(jax|torch|jupyter-book)"

```

**Monitor build progress:**

```bash

Build shows progress as: "reading sources... [X%] filename"

Watch for notebook execution times and warnings

jb build lectures --path-output ./ -W --keep-going

```

**Check build outputs:**

```bash

ls -la _build/html/

ls -la _build/jupyter/

ls -la _build/.jupyter_cache/

```

Important Constraints