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name: cookiecutter-data-science description: "Use Cookiecutter Data Science to generate, configure, validate, and troubleshoot reproducible data-science project templates and generated project workflows." disable-model-invocation: true metadata: disco-role: operating license: MIT

Cookiecutter Data Science

Use this repo skill for Cookiecutter Data Science (CCDS), the cookiecutter-data-science Python package and ccds CLI for creating standardized but flexible data-science project skeletons.

What this skill covers

• Installing and checking the ccds CLI.
• Generating a new CCDS v2 project interactively or noninteractively.
• Choosing and validating CCDS options such as environment manager, dependency file, cloud storage, docs, tests, linting, license, and code scaffold.
• Understanding CCDS prompt patches, post-generation hooks, dependency-file writers, and custom config overlays.
• Working inside a generated CCDS project: layout, Makefile commands, data workflow, environment managers, scaffold modules, docs, tests, linting, and validation.
• Troubleshooting install/import, CLI, option, hook, generated layout, Makefile, external manager, and cloud-sync failures.

Quick package facts

• Distribution: cookiecutter-data-science.
• Import module: ccds.
• Console script: ccds.
• Runtime requirement: Python 3.9+.
• Runtime dependencies: click, cookiecutter, and tomlkit.

Install for CLI use:

pipx install cookiecutter-data-science

Alternative inside a Python environment:

python -m pip install cookiecutter-data-science

Minimal checks:

python -c "import ccds; print(ccds.__version__)"
ccds --help

Run scripts/check_ccds_environment.py for a bundled import/CLI/helper smoke check.

Route by task

Task intent	Read next
Install CCDS, run ccds, generate a project, set --output-dir, pin --checkout, use --no-input, handle replay/config, or debug project-generation failures.	sub-skills/project-generation-cli/SKILL.md
Understand option names, defaults, nested choices, valid environment-manager/dependency-file pairs, hook effects, dependency-file generation, prompt monkey patches, or custom config overlays.	sub-skills/template-options-and-hooks/SKILL.md
Work inside a generated project: data layout, Makefile rules, environment setup, dependency installation, scaffold modules, docs, tests, linting, cloud sync, or validation.	sub-skills/generated-project-workflows/SKILL.md
Check whether this skill matches the current CCDS repository or package version.	references/repo-provenance.md
Diagnose cross-cutting package, route, version, external tool, validation, data, or secret-handling issues.	references/troubleshooting.md
Check Python, manager, backend, and native verification expectations.	references/compatibility.md

High-level operating flow

1. If creating a project, route to project-generation-cli. Decide interactive vs noninteractive generation, output parent, checkout/version, hook policy, and whether a disposable bake is safer.
2. If choosing options, route to template-options-and-hooks. Validate manager/dependency-file pairings and predict hook outputs before generation.
3. After a project exists, route to generated-project-workflows. Inspect actual option-dependent files, validate the tree, then decide whether to run environment, dependency, lint, test, data, or cloud commands.
4. Before exact maintenance claims, read provenance. CCDS option schemas and hooks are version-sensitive.

Safety boundaries

• Do not run generated cloud sync rules unless credentials, destination, direction, and transfer size are explicitly intended.
• Do not run generated environment-manager commands in a shared or constrained environment without confirming the required external CLI and local side effects.
• Do not treat starter tests as project failures; generated pytest/unittest starters intentionally fail until replaced.
• Do not apply v2 option and hook behavior to the deprecated v1 template.
• Do not rely on the original source checkout at runtime. This skill bundles distilled references and safe helper scripts for CCDS v2.3.0 behavior.