# PRQL — Pipelined Relational Query Language

> A modern language that compiles to SQL, designed for data transformations with a readable pipeline syntax.

## Install

Save as a script file and run:

# PRQL — Pipelined Relational Query Language

## Quick Use
```bash
pip install prqlc
# Or install via cargo
cargo install prqlc
# Compile PRQL to SQL
echo "from employees | filter age > 30 | select {name, age}" | prqlc compile
```

## Introduction
PRQL (pronounced "prequel") is a modern query language that compiles to SQL. It was created to address the readability and composability limitations of SQL by introducing a pipelined, functional syntax that makes data transformations more intuitive and maintainable.

## What PRQL Does
- Compiles a readable pipeline syntax into standard SQL for any database
- Supports variables, functions, and modular query composition
- Provides a type system that catches errors before queries reach the database
- Integrates with Python, JavaScript, Rust, and other languages via bindings
- Offers editor extensions with syntax highlighting and live SQL preview

## Architecture Overview
PRQL is built as a compiler in Rust. Source code passes through a lexer, parser, semantic analyzer, and finally a SQL backend that emits dialect-specific output. The compiler is packaged as a CLI tool (prqlc), a Rust library, and WASM bindings that power integrations for Python (prqlc-python), JavaScript, and database tools like DBeaver and Jupyter.

## Self-Hosting & Configuration
- Install the CLI via pip, cargo, brew, or npm depending on your ecosystem
- Use prqlc compile to convert .prql files to .sql as part of your CI pipeline
- Integrate with dbt via the dbt-prql plugin for transformation workflows
- Configure target SQL dialect (PostgreSQL, MySQL, SQLite, BigQuery, etc.) with the --target flag
- Embed in Jupyter notebooks using the %%prql magic command from pyprql

## Key Features
- Pipeline syntax reads top-to-bottom like data actually flows
- S-strings allow raw SQL escape hatches when needed
- Automatic column tracking eliminates repetitive GROUP BY clauses
- Dialect-aware compilation targets 15+ SQL databases
- Composable functions let you build reusable query libraries

## Comparison with Similar Tools
- **SQL** — PRQL compiles to SQL; it is not a replacement but a more ergonomic authoring layer
- **Malloy** — Malloy is a semantic modeling language; PRQL focuses on ad-hoc query composition
- **dbt** — dbt orchestrates SQL transformations; PRQL can be used inside dbt via a plugin
- **LINQ** — LINQ is embedded in .NET languages; PRQL is language-agnostic with multi-platform bindings
- **Kusto (KQL)** — KQL is Azure-specific; PRQL targets any SQL database

## FAQ
**Q: Can I use PRQL with my existing database?**
A: Yes. PRQL compiles to standard SQL, so it works with PostgreSQL, MySQL, SQLite, BigQuery, ClickHouse, DuckDB, and many others.

**Q: Does PRQL support joins?**
A: Yes. PRQL supports join operations with a cleaner syntax than SQL, including automatic column disambiguation.

**Q: Is PRQL production-ready?**
A: PRQL is at version 0.x but is actively used in production data pipelines. The compiler is well-tested with thousands of test cases.

**Q: Can I mix PRQL and raw SQL?**
A: Yes. S-strings let you embed raw SQL expressions anywhere in a PRQL query for cases the language does not yet cover.

## Sources
- https://github.com/PRQL/prql
- https://prql-lang.org

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Source: https://tokrepo.com/en/workflows/asset-4fe82100
Author: Script Depot