Superset Dev fe3fa946c4 fix(i18n): handle JSON-list plural responses from the model
A fresh test run on French exposed a real bug in _apply_translation:
when the model returns a JSON list for a plural entry (e.g.
["form0", "form1"], which is a valid representation since plural forms
are ordered), the previous code took the else branch and broadcast
str(list) — Python list-repr like ['form0', 'form1'] — to every plural
form. Both msgstr[0] and msgstr[1] ended up containing the same
literal Python list-repr string, breaking gettext lookups for that
entry. Spanish dodged it by chance (the model returned dicts that
time); the failure mode is reproducible on French.

Changes:
- Extract _apply_plural_translation helper. Handles dict, list,
  scalar, and non-JSON-string responses. List path distributes forms
  by index and repeats the last form if the model returned fewer
  forms than the language requires (better than leaving slots blank,
  which falls back to displaying the raw English msgid).
- The split also drops _apply_translation's cyclomatic complexity
  back below the C901 threshold.
- Adds 4 regression tests covering: list response, list response
  round-tripped through parse_response, list shorter than required
  forms (last-form-repeats), and empty list (falls back to raw-string
  broadcast).

Verified end-to-end on French: the previously-broken plural entry
"Added 1 new column to the virtual dataset" / "Added %s new columns
to the virtual dataset" now writes msgstr[0] and msgstr[1] correctly
on a fresh run.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-05-11 17:47:24 -07:00
2026-04-17 17:21:23 -03:00
2025-12-04 13:18:34 -05:00

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

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Video Overview

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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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