In-depth topics

Chapter-length notes on individual topics that come up in the templates but don’t fit cleanly into a README. Each file is a standalone reference — read whichever one you need, in any order. Linked from the hub README.

Chapters

The list will grow as topics are written. Linked entries below are live; unlinked entries are placeholders for content I plan to add.

  • Project structure for research — the three storage locations (GitHub, local clone, cloud sync), why code and data must be separate, why the local clone shouldn’t be inside Dropbox, the recommended folder layout, file-naming conventions, and the LaTeX-vs-Word manuscript decision.
  • Git and GitHub for research projects — Git vs. GitHub, the everyday commit/push/pull workflow, template repositories, branching for R&R revisions, tagging paper versions, .gitignore essentials, and a glossary.
  • Setting up your IDE — what an IDE is and the popular ones, why an IDE beats Jupyter notebooks for reproducible research code, how IDEs treat a folder as a project, the source-control panels in RStudio and VS Code, per-editor setup notes, ligature fonts, and AI-assistant integration.
  • Python virtual environments with venv and uv — what a Python virtual environment is, why you need one per project, the messy Python tool landscape (venv / pip / pip-tools / pyenv / pipx / poetry / conda) and why the templates standardize on uv, the pyproject.toml + uv.lock model, and the five uv commands you’ll actually use day-to-day.
  • Environment variables and the .env file — what an environment variable is, why the templates use .env instead of hardcoded paths, how each of R / Python / Stata / SAS reads it, credentials in keyring vs. .env, common gotchas.
  • About AGENTS.md — what the AGENTS.md file in each repo is, the cross-tool standard behind it, how it interacts with CLAUDE.md, and why you might want one in your own projects.
  • SAS macros and batch_run_sas — MACROS.sas, a working SAS script (002-merge-fdp-data.sas from the consensus repo), and a walkthrough of using %load_env + batch_run_sas() for JAR-style logs.

Table of contents