Skip to main content

Offline, advisory DAX/model standards linter for Power BI semantic models: parses TMDL/.bim, checks measures and model structure against the team's DAX standards, and reports anything that doesn't match. Human report + machine JSON for the company agent. Never edits or blocks.

Project description

coop-dax-review

Offline, advisory DAX/model standards linter for our Power BI semantic models. It parses TMDL (and legacy .bim) models, builds a model catalog, checks measures and model structure against docs/standards.md (our DAX standards + Microsoft/Tabular best practices), and surfaces anything that doesn't match. It never edits or blocks — it only reports. Human reports (a sectioned, colorized terminal report, Markdown, or a self-contained branded HTML file) and machine JSON for the company analytics agent.

Sibling tool to coop-sql-review — same architecture and contracts.

Install

pipx install coop-dax-review        # from PyPI

Use pipx, not system pip, so the tool stays isolated from other CLIs (ms-fabric-cli, azure-cli) it might otherwise fight over shared pins. For local development:

python -m venv .venv && .venv/bin/pip install -e ".[dev]"

Usage

coop-dax-review check [MODEL_PATHS...] [--format text|json|markdown|html] [-o FILE]
                      [--open/--no-open] [--color/--no-color] [--log-file FILE]
                      [--baseline FILE] [--write-baseline FILE]
                      [--min-severity error|warning|info] [--strict]
coop-dax-review rules                 # list every rule (id, severity, tier, agent?)
coop-dax-review upgrade               # show the command to update (never self-applies; alias: update)
coop-dax-review --version
  • MODEL_PATHS point at a PBIP/TMDL model folder (*.SemanticModel/definition/...), any folder of .tmdl files, or a legacy .bim file. Directories are searched recursively; defaults to ..
  • Run it with no paths in a terminal and it offers a checkbox picker of the subfolders to check (all selected by default — press ENTER to scan everything).
  • Advisory: exit code is always 0. --strict is the opt-in CI gate — exit 2 when any finding remains at/above --min-severity.
  • --standards <path> overrides the bundled standards (e.g. point it at a canonical company standards file). Its sha256 travels in the JSON so the agent knows which standards a report used.
  • A rules.yml beside the standards file (or --config) can disable rules / override severities with no rebuild.
coop-dax-review check ./MyModel.SemanticModel
coop-dax-review check . --format json --strict --min-severity warning
coop-dax-review check . --format html              # writes a report file and opens it in your browser
coop-dax-review check . --format markdown -o report.md

The default --format text is a sectioned terminal report: a banner, one section per model with ERROR/WARN/INFO severity badges, and a SUMMARY panel. It's colorized automatically when you're at a terminal and falls back to plain text when piped or redirected (override with --color/--no-color; NO_COLOR is respected).

--format html produces a self-contained, branded HTML report (inline CSS + embedded logo, no network). It is always written to a file — coop-dax-review-report.html by default, or wherever -o points — and the path is printed and opened in your browser (pass --no-open to skip the open, e.g. in CI). upgrade/update print the exact command to run yourself (pipx upgrade coop-dax-review, etc.) rather than self-applying, since a package manager can't replace the tool while it is running.

What it checks

Run coop-dax-review rules for the live list. Deterministic rules (reported as findings):

Rule § Sev Flags
DAX-MEASURE-CATEGORY 1 warning measure not named [Category: Name]
DAX-MEASURE-NOT-PREFIXED 1 warning Table[X] where X is a measure (measures take no prefix)
DAX-COLUMN-PREFIXED 1 warning bare [X] where X is a column (columns need Table[X])
DAX-VAR-RETURN 2 info non-trivial measure with no VAR/RETURN structure
DAX-NO-NESTED-CALCULATE 3 warning CALCULATE nested inside CALCULATE
DAX-FILTER-TABLE-IN-CALCULATE 4 warning FILTER(<table>, <col> = ...) where a plain column filter suffices
DAX-SNOWFLAKE 6 info a table with relationships chained through it (snowflake link)
DAX-BIDI-RELATIONSHIP 7 warning a bidirectional cross-filter relationship
DAX-MARKED-DATE-TABLE 8 warning time-intelligence used but no marked Date table
DAX-MEASURE-IN-ITERATOR 9 info a measure referenced inside a row iterator (hidden context transition)
DAX-COMPLEX-NO-HEADER 12 info a complex measure (≥3 VARs) without a /* ... */ header
DAX-DIRECTLAKE-NO-CALC-COL 13 warning a calculated column in a Direct Lake model
DAX-USE-DIVIDE 14 warning the / operator where DIVIDE() should be used
DAX-FORMAT-STRING 15 warning a measure with no explicit formatString
DAX-NO-FLOAT-KEYS 16 info a relationship key column typed double
DAX-HIDE-FK-COLUMNS 17 info a visible foreign-key (relationship) column
DAX-KEY-SUMMARIZEBY-NONE 18 info a numeric key column that auto-aggregates (summarizeBy ≠ none)
DAX-DISPLAY-FOLDERS 19 info a measure-heavy table with no display folders

Agent-judgment rules — the tool detects the construct but emits to the JSON agent_review list (never an auto-finding), because the call needs intent the linter can't infer:

Rule § Judges
DAX-KEEPFILTERS-NEEDED 5 whether a CALCULATE boolean filter needs KEEPFILTERS
DAX-STAR-SCHEMA 6 whether a snowflake chain should be flattened to a star
DAX-CONTEXT-TRANSITION 9 whether an iterator's context transition is intended/correct
DAX-SIMPLE-FUNCTIONS 10 whether a CALCULATE-heavy measure could use simpler functions
DAX-VALIDATION 11 whether the §11 validation checklist was run for a non-trivial measure
DAX-IMPLICIT-MEASURE 20 whether a visible auto-aggregating numeric column should become an explicit measure

See RULES.md for the full taxonomy. docs/standards.md §14–§20 are adopted Microsoft/Tabular best practices (DIVIDE, format strings, key column types, hidden FKs, key summarizeBy, display folders, explicit measures); docs/standards-proposed-additions.md is the original candidate list.

Suppressing findings (adopting on an existing model)

Two deterministic, never-blocking ways to silence findings you've already triaged:

  • Inline — drop a comment on a finding's line (or the line directly above it):
    // coop-dax-review:ignore DAX-VAR-RETURN reason: legacy measure, rewrite scheduled
    
    List several rule ids (ignore DAX-A, DAX-B), or use a bare ignore / * to silence every rule on that line. The reason: text is for humans; it's ignored by the parser.
  • Baseline (ratchet) — record today's findings and surface only new ones going forward:
    coop-dax-review check . --write-baseline dax-baseline.json   # once, to capture the status quo
    coop-dax-review check . --baseline dax-baseline.json         # thereafter: only new findings appear
    
    Each finding has a stable, line-independent fingerprint (in the JSON), and the baseline is a sorted list of those. A baseline entry that no longer matches any finding (you fixed it) is reported as a diagnostic so the file self-cleans (--write-baseline to prune).

Agent JSON contract

{
  "tool": "coop-dax-review", "schema_version": 1, "version": "x.y.z",
  "standards": {"path": "...", "sha256": "..."},
  "models_checked": 2,
  "verdict": {"clean": false, "highest_severity": "warning"},
  "findings": [{"rule_id":"...","severity":"warning","model":"Sales","file":"...","line":12,
                "object":"[Sales: Revenue YTD]","message":"...","standard_ref":"§3","fingerprint":"4ad6aeb79867"}],
  "summary": {"error":0,"warning":2,"info":4},
  "agent_review": [{"rule_id":"...","model":"Sales","file":"...","line":40,"object":"[...]","note":"...","standard_ref":"§5","fingerprint":"..."}],
  "diagnostics": [{"severity":"warning","category":"parse_failed","file":"...","message":"..."}]
}

schema_version lets a consumer pin the shape; verdict/models_checked give a quick machine verdict + coverage signal; each finding's fingerprint is a stable id for tracking across runs.

Project docs

  • SPEC.md — architecture, CLI, agent contract, milestones.
  • RULES.md — every standard mapped to a concrete check (deterministic vs agent-judgment).
  • docs/standards.md — the canonical DAX standards the linter checks against (bundled as package data).
  • CLAUDE.md — orientation for Claude Code sessions in this repo.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

coop_dax_review-0.5.0.tar.gz (112.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

coop_dax_review-0.5.0-py3-none-any.whl (136.1 kB view details)

Uploaded Python 3

File details

Details for the file coop_dax_review-0.5.0.tar.gz.

File metadata

  • Download URL: coop_dax_review-0.5.0.tar.gz
  • Upload date:
  • Size: 112.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for coop_dax_review-0.5.0.tar.gz
Algorithm Hash digest
SHA256 09aa7dc3f0cb37851c10f0dd6a50de1f4baaf6ec6c7877903598bb474b10a600
MD5 3ccd6c7d02fe4a1534b83941dcdcdffd
BLAKE2b-256 a15cc2c3c7182cff4fa5c67c1de3da6e678d2a7b4a0b795315175394b41c73c5

See more details on using hashes here.

Provenance

The following attestation bundles were made for coop_dax_review-0.5.0.tar.gz:

Publisher: publish.yml on kabukisensei/coop-dax-review

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file coop_dax_review-0.5.0-py3-none-any.whl.

File metadata

  • Download URL: coop_dax_review-0.5.0-py3-none-any.whl
  • Upload date:
  • Size: 136.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for coop_dax_review-0.5.0-py3-none-any.whl
Algorithm Hash digest
SHA256 379258a9964a65c9a545f330901d87c8c52e4029b1fb5c0778dffea72a989a20
MD5 50fccf3005eb910b43732a638159099b
BLAKE2b-256 68502c885e7ab79c92b23c530606fcaeaa5fb6f4d84ba746e430246ddebf8fd3

See more details on using hashes here.

Provenance

The following attestation bundles were made for coop_dax_review-0.5.0-py3-none-any.whl:

Publisher: publish.yml on kabukisensei/coop-dax-review

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page