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thinkinglanguage

v0.3.8

Published

A purpose-built language for Data Engineering & AI

Readme

ThinkingLanguage

A purpose-built language for Data Engineering & AI.

Try it in your browser — no install: tl.thinkingdbx.com

This npm package installs the tl CLI binary by downloading the appropriate prebuilt release for your platform from GitHub Releases.

Highlights

  • Native tables — columnar data on Apache Arrow / DataFusion with pipe-based transforms
  • Data connectors (read & write) — PostgreSQL, MySQL, Redshift, Snowflake, BigQuery, Databricks, ClickHouse, MongoDB, SQLite, DuckDB, S3, and Apache Iceberg
  • AI/ML built-in — tensors, model training, ONNX inference, embeddings, LLM APIs, AI agents with tool-use, and MCP client/server
  • Streaming & pipelines — ETL/ELT constructs, windowed streams, Kafka
  • Gradual typing — optional annotations, generics, traits, pattern matching, Result/Option with ?
  • Ownership semantics — pipe-as-move, .clone(), read-only &ref, use-after-move detection
  • Multiple backends — bytecode VM (default), LLVM AOT native compilation, WASM browser target
  • Rich tooling — LSP server, VS Code extension, formatter, linter, doc generator, package manager, REPL

Install

npx thinkinglanguage --help

Or install globally:

npm install -g thinkinglanguage
tl --help

Supported platforms

  • Linux x86_64
  • macOS arm64 (Apple Silicon)
  • Windows x86_64

Quick example

let users = read_csv("users.csv")

users
    |> filter(age > 30)
    |> aggregate(by: department, count: count(), avg_age: avg(age))
    |> sort("count", "desc")
    |> show()

Links

License

Apache-2.0