Evan Rusackas 2db41bb2b2 feat(country-map): minimum-viable build pipeline (NE → GeoJSON)
End-to-end working pipeline replacing the legacy notebook for one
worldview / admin level. Verified locally:

  $ ./build.sh
  Country Map build — pinned to NE v5.1.2 (f1890d9f)
  Loaded 10 name override entries
  Building worldview=ukr admin_level=0
  Downloading NE ne_10m_admin_0_countries_ukr (worldview=ukr)…
    mapshaper: ne_10m_admin_0_countries_ukr.shp → _raw_ukr_admin0.geo.json
    loaded 249 features
    name_overrides: applied 0 field updates across 10 entries
    wrote .../output/ukr_admin0.geo.json (23,639,348 bytes)
  Done.

What's wired:
- NE download from pinned tag (v5.1.2 / SHA f1890d9f) with cache
- Shapefile → GeoJSON via mapshaper CLI
- YAML config loading (currently just name_overrides)
- name_overrides transform with {match, set} semantics, including
  the {in: [...]} list-membership matcher
- Output writes to scripts/output/ (gitignored)
- build.sh wrapper validates Python + Node + PyYAML are available

What's stubbed for future commits (TODO inline):
- Multiple worldviews (currently UA only)
- Admin 1 build (where name_overrides actually fire — currently no
  features in Admin 0 match the FRA/PHL admin1 entries)
- flying_islands, territory_assignments, regional_aggregations,
  composite_maps transforms
- Simplification (mapshaper -simplify)
- Procedural escape-hatch orchestration
- Manifest with NE SHA + build metadata

The 0 overrides applied is correct, not a bug: all current entries
target Admin 1 features.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-05-12 16:00:29 -07:00
2025-12-04 13:18:34 -05:00

Superset

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A modern, enterprise-ready business intelligence web application.

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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
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  • 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
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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.

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

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