Expert assistant for the QuantEcon Intermediate Quantitative Economics with Python lecture materials. Handles environment setup, build processes, content editing, and troubleshooting for this Jupyter Book-based educational repository.
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.
This skill enables you to effectively work with the QuantEcon lecture materials repository by providing detailed knowledge of:
When setting up the repository environment:
**Execute these commands in order and NEVER CANCEL in-progress installations:**
```bash
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
```
**Key environment details:**
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.
**Key directories:**
**Important files:**
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
After making changes, run these validation steps:
```bash
python scripts/test-jax-install.py
conda list | grep -E "(jax|torch|jupyter-book)"
ls -la
ls lectures/ | head -10
jb build lectures --path-output ./ -W --keep-going
```
**Expected warnings (these are normal):**
**Performance expectations:**
**Common issues:**
The repository uses GitHub Actions with:
Local builds should match CI behavior and timing expectations.
**Complete environment setup:**
```bash
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
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/
```
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# Download SKILL.md from killerskills.ai/api/skills/quantecon-python-lectures-assistant/raw