Timelake 0.1.0

The first version. Tagged after the fact: the code at this tag reports version 0.0.1.

Added

• Engine (timelake crate): time-series and plain tables stored as Parquet files with Apache Iceberg metadata, on
  S3, GCS, Azure, S3-compatible stores (R2, MinIO, RustFS) or a local disk. Read-only access over HTTPS.
  • Time-series tables are partitioned by hour, day or month and sorted by (series key, time).
  • Every append is one atomic commit. Concurrent writers are safe without a catalog service (put-if-absent on
    vN.metadata.json); a conflicting commit is rebased and retried.
  • Idempotent appends with a batch_id: a repeated batch is skipped and reported as 0 rows.
  • A last-value index per snapshot gives the newest row of every series without a scan.
  • Maintenance (compaction, deduplication where the latest write wins, retention, snapshot expiry) runs inline after
    appends, or on demand. A maintenance failure is reported separately and never undoes the append.
  • SQL through DataFusion, with time_bucket(), file, row group and page pruning, and "latest row" queries rewritten
    to read the index.
• CLI (timelake): create, append, import, sql, latest, maintain, info, ls, duckdb, drop and
  index. Loads Parquet, CSV, gzipped CSV and TSV.
• Python (timelake package): Lake and Table with create_table, append (pyarrow, polars or any Arrow
  stream), sql, latest and maintain, returning pyarrow tables. Full type stubs. Invalid input raises
  ValueError, a missing table KeyError, and an unresolvable concurrent commit timelake.ConflictError.
• WebAssembly reader and TypeScript client (@timelake/client): reads tables over HTTPS in the browser or Node,
  with latest, range and time-bucket queries and Zod-typed rows.
• Open format: plain DuckDB, Spark and PyIceberg read every table. timelake duckdb <table> prints the SQL.

Full changelog: https://github.com/polythings/timelake/blob/main/CHANGELOG.md