sqlfluff-complexity

sqlfluff-complexity

SQLFluff rules and reports for finding SQL and dbt models that are too complex to review safely.

sqlfluff-complexity adds CPX rules to SQLFluff for CTE count, join count, nested subquery depth, CASE expressions, nested CASE depth, boolean predicates, window functions, CTE dependency depth, set operations (UNION / INTERSECT / EXCEPT), inline derived tables, and an aggregate weighted complexity score. The same metric engine also powers a companion sqlfluff-complexity report command for non-blocking console, JSON, SARIF, and standalone HTML reports.

Who It Is For

• Analytics engineers who want dbt models to stay small enough to review.
• Data platform teams that already run SQLFluff in local development or CI.
• Teams that want gradual complexity reporting before turning on strict lint failures.

Quick Start

Requires SQLFluff 4.x in the same environment (sqlfluff>=4,<5). SQLFluff 3 is not supported as of sqlfluff-complexity 0.4.0; pin sqlfluff-complexity<0.4 if you cannot upgrade SQLFluff yet.

Install the custom SQLFluff plugin in the same Python environment where you run SQLFluff:

pip install sqlfluff-complexity

If your project uses uv:

uv add --dev sqlfluff-complexity

Then enable CPX rules in .sqlfluff and run SQLFluff:

[sqlfluff]
dialect = postgres
rules = CPX_C101,CPX_C102,CPX_C103,CPX_C104,CPX_C105,CPX_C106,CPX_C107,CPX_C108,CPX_C109,CPX_C110,CPX_C201

sqlfluff lint models/

For a complete walkthrough, see docs/quickstart.md.

Migrating complexity_weights: Use a JSON object in [sqlfluff:rules:CPX_C201] (not comma-separated key:value lists). See Configuration: aggregate score and CHANGELOG.

Documentation

• Quick start: install, configure, and run the first lint.
• Configuration: thresholds, aggregate weights, SQLFluff nested config by path, and path_overrides.
• Rules reference: CPX rule codes and what each metric counts.
• Reporting: console, JSON, SARIF, and HTML report mode.
• Python API: stable programmatic imports (today: report pipeline and related config helpers; more subcommands documented here as they ship).
• Adoption: calibration, CI/SARIF examples, before/after SQL vignette.
• dbt usage: SQLFluff dbt templater compatibility and v1 boundaries.
• Dialects: tested dialects and dbt adapter mapping caveats.
• Docs index: all user, contributor, and design documents.
• Internal import migration: if you import sqlfluff_complexity.core submodules directly, update paths after subpackage refactors.

Large dbt projects

This plugin does not read dbt artifacts (manifest.json, run_results.json, catalog.json) or graph metadata. Complexity is measured from the SQLFluff parse tree only—which aligns well with SQLFluff’s dbt templater so ref(), source(), and macros compile before linting.

Practical adoption patterns:

• Use the dbt templater when you need compiled SQL fidelity; keep sqlfluff-complexity focused on structural signals from parsed SQL.
• Tune thresholds per rule and use path_overrides on CPX_C201 where staging vs marts need different budgets.
• Prefer sqlfluff lint on changed models in CI and sqlfluff-complexity report for broader visibility without failing builds.
• For CTE dependency depth, see docs/rules.md (CPX_C107) and docs/reporting.md (report vs per-WITH lint).

See also dbt usage and configuration.

Project Status

• Native SQLFluff plugin rules and the companion report CLI are available in the package.
• v1 measures SQLFluff-parsed SQL; direct dbt manifest.json and DAG-level metrics are deferred.
• Architecture decisions are recorded in docs/adr/.

Development

Contributor setup, Nox sessions, fixture authoring, ADR workflow, and verifier guidance live in CONTRIBUTING.md. Agent-specific project instructions live in AGENTS.md.