Claude Code dfd3f7b316 ci(lint): enforce no function-body imports (PLC0415) with targeted ignores
Follow-up to #40231 (merged), where a reviewer flagged a function-body
`from datetime import datetime, timedelta` instead of a top-of-file
import. Adds a `ruff-import-placement` pre-commit hook running
`ruff check --select PLC0415 --preview --no-fix`.

Per @rusackas's pushback on the first cut of this PR — which spammed
2,657 `# noqa: PLC0415` annotations across ~410 files without fixing
anything — this revision is a much smaller surface area:

1. **Per-file-ignores** for whole directories where function-body
   imports are a deliberate pattern, not an oversight:
   - `superset/cli/**` and `scripts/**`: subcommand-deferred imports
     keep heavy modules out of the CLI startup path.
   - `superset/tasks/**`: Celery task bodies defer imports of the
     modules they orchestrate.
   - `superset/migrations/versions/**`: Alembic migrations interact
     with model state at runtime, not at module load.
   - `superset/mcp_service/**`: MCP tools lazy-load resources on
     invocation so the server can register many tools without paying
     their import cost at startup.
   - `superset/db_engine_specs/**`: engine specs defer driver imports
     so optional DB drivers don't have to be installed.
   - `superset/initialization/__init__.py`, `superset/extensions/__init__.py`,
     `superset/app.py`: the app-factory and extension wiring are
     intentionally full of circular-import workarounds.
   - `tests/**`: test files routinely defer imports for fixture
     isolation; the rule still applies to production code.

2. **Per-line `# noqa: PLC0415`** on the 259 remaining genuine
   circular-import sites (security/manager.py, sql/execution/executor.py,
   semantic_layers/labels.py, tags/core.py, core_api_injection.py, etc.).
   These are foundational modules where moving the imports up would
   actually break things.

Net result: ~410 files / 2,657 grandfathered → ~73 files / 259 actual
noqa annotations. The rule still catches every new function-body
import outside the explicitly-allowed directories.

Also: silences a pre-existing C901 on `mcp_service/sql_lab/tool/execute_sql.py`
that fires under newer local ruff but not CI's pinned ruff 0.9.7 — blocks
the local pre-commit run otherwise.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-20 13:55:14 -07:00

Superset

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A modern, enterprise-ready business intelligence web application.

Documentation

  • User Guide — For analysts and business users. Explore data, build charts, create dashboards, and connect databases.
  • Administrator Guide — Install, configure, and operate Superset. Covers security, scaling, and database drivers.
  • Developer Guide — Contribute to Superset or build on its REST API and extension framework.

Why Superset? | Supported Databases | Release Notes | Get Involved | Resources | Organizations Using Superset

Why Superset?

Superset is a modern data exploration and data visualization platform. Superset can replace or augment proprietary business intelligence tools for many teams. Superset integrates well with a variety of data sources.

Superset provides:

  • A no-code interface for building charts quickly
  • A powerful, web-based SQL Editor for advanced querying
  • A lightweight semantic layer for quickly defining custom dimensions and metrics
  • Out of the box support for nearly any SQL database or data engine
  • A wide array of beautiful visualizations to showcase your data, ranging from simple bar charts to geospatial visualizations
  • Lightweight, configurable caching layer to help ease database load
  • Highly extensible security roles and authentication options
  • An API for programmatic customization
  • A cloud-native architecture designed from the ground up for scale

Screenshots & Gifs

Video Overview

superset-video-1080p.webm


Large Gallery of Visualizations


Craft Beautiful, Dynamic Dashboards


No-Code Chart Builder


Powerful SQL Editor


Supported Databases

Superset can query data from any SQL-speaking datastore or data engine (Presto, Trino, Athena, and more) that has a Python DB-API driver and a SQLAlchemy dialect.

Here are some of the major database solutions that are supported:

Amazon Athena   Amazon DynamoDB   Amazon Redshift   Apache Doris   Apache Drill   Apache Druid   Apache Hive   Apache Impala   Apache Kylin   Apache Pinot   Apache Solr   Apache Spark SQL   Ascend   Aurora MySQL (Data API)   Aurora PostgreSQL (Data API)   Azure Data Explorer   Azure Synapse   ClickHouse   Cloudflare D1   CockroachDB   Couchbase   CrateDB   Databend   Databricks   Denodo   Dremio   DuckDB   Elasticsearch   Exasol   Firebird   Firebolt   Google BigQuery   Google Sheets   Greenplum   Hologres   IBM Db2   IBM Netezza Performance Server   MariaDB   Microsoft SQL Server   MonetDB   MongoDB   MotherDuck   OceanBase   Oracle   Presto   RisingWave   SAP HANA   SAP Sybase   Shillelagh   SingleStore   Snowflake   SQLite   StarRocks   Superset meta database   TDengine   Teradata   TimescaleDB   Trino   Vertica   YDB   YugabyteDB

A more comprehensive list of supported databases along with the configuration instructions can be found here.

Want to add support for your datastore or data engine? Read more here about the technical requirements.

Installation and Configuration

Try out Superset's quickstart guide or learn about the options for production deployments.

Get Involved

Contributor Guide

Interested in contributing? Check out our Developer Guide to find resources around contributing along with a detailed guide on how to set up a development environment.

Resources

Understanding the Superset Points of View

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