f840ce9813
Five structural changes — no behaviour change — applied as one commit per the tidy-first discipline. All from the clean-code review of e4070a4716. * Tidy 1 — Fix _fetch_change_records sort key. Was calling .timestamp() on issued_at with an `else 0` fallback; the fallback was dead defense (column is non-null per sc-103156 schema) and .timestamp() introduces non-determinism on tz-naive datetimes. Sort on the datetimes directly. * Tidy 2 — parse_activity_query_params now raises ActivityParamsError (subclass of ValueError) instead of returning (Optional[dict], Optional[str]). The tuple was forcing every caller into a defensive `if error or params is None: return self.response_400(message=error or "Invalid query parameters")`. The new shape — `try: params = parse(...); except ActivityParamsError as exc: return response_400(str(exc))` — is shorter, type-safe, and the contract is enforced at the boundary. * Tidy 3 — Test helper now uses Flask client's query_string= parameter instead of f-string concatenation. Handles URL-encoding correctly for the day a test passes a value containing & / = / + / etc. * Tidy 4 — get_activity pipeline collapses to a single rolling `records` variable instead of the mid-stream `raw / visible_raw / enriched / visible` naming. Each function call's name documents what the step does; no intermediate variable names needed. * Tidy 5 — Extracted four per-parameter parsers: _parse_optional_iso, _parse_include, _parse_page, _parse_page_size. The "parse one parameter" concept now has a name. Cost: four small helpers (each 10-15 lines, one job). Benefit: parse_activity_query_params is a 10-line table-driven dispatcher. Test changes: parser unit tests now use pytest.raises(ActivityParamsError) instead of unpacking the (params, error) tuple. Added one test confirming ActivityParamsError subclasses ValueError so the standard library exception hierarchy still catches it. Total unit tests: 57. Integration tests still 10/10 green. Deferred per the review: the UUID-parse + entity-find + ownership- check dance is duplicated between activity / list_versions / get_version and will grow to T028 / T033. Refactor when T028 lands — three real callers > one prospective one. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Superset
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
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:
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
- Ask and answer questions on StackOverflow using the apache-superset tag
- Join our community's Slack and please read our Slack Community Guidelines
- Join our dev@superset.apache.org Mailing list. To join, simply send an email to dev-subscribe@superset.apache.org
- If you want to help troubleshoot GitHub Issues involving the numerous database drivers that Superset supports, please consider adding your name and the databases you have access to on the Superset Database Familiarity Rolodex
- Join Superset's Town Hall and Operational Model recurring meetings. Meeting info is available on the Superset Community Calendar
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
- Superset "In the Wild" - see who's using Superset, and add your organization to the list!
- Feature Flags - the status of Superset's Feature Flags.
- Standard Roles - How RBAC permissions map to roles.
- Superset Wiki - Tons of additional community resources: best practices, community content and other information.
- Superset SIPs - The status of Superset's SIPs (Superset Improvement Proposals) for both consensus and implementation status.
Understanding the Superset Points of View
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Getting Started with Superset
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Deploying Superset
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Recordings of Past Superset Community Events
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Visualizations
Repo Activity
