thinkinglanguage
v0.3.8
Published
A purpose-built language for Data Engineering & AI
Maintainers
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/Optionwith? - 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 --helpOr install globally:
npm install -g thinkinglanguage
tl --helpSupported 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
- Playground — run ThinkingLanguage in your browser
- Repository
- Documentation
- Website
License
Apache-2.0
