PRQL: Pipelined Relational Query Language

PRQL

Pipelined Relational Query Language, pronounced “Prequel”.

PRQL is a modern language for transforming data — a simple, powerful, pipelined
SQL replacement. Like SQL, it’s readable, explicit and declarative. Unlike SQL,
it forms a logical pipeline of transformations, and supports abstractions such
as variables and functions. It can be used with any database that uses SQL,
since it compiles to SQL.

PRQL can be as simple as:

from tracks
filter artist == "Bob Marley"                 # Each line transforms the previous result
aggregate {                                   # `aggregate` reduces each column to a value
  plays    = sum plays,
  longest  = max length,
  shortest = min length,                      # Trailing commas are allowed
}

Here’s a fuller example of the language;

For more on the language, more examples & comparisons with SQL, visit
prql-lang.org. To experiment with PRQL in the browser, check out
PRQL Playground.

Current Status – April 2023

PRQL is being actively developed by a growing community. It’s ready to use by
the intrepid, either with our supported integrations, or within your own tools,
using one of our supported language bindings.

PRQL still has some minor bugs and some missing features, and probably is only
ready to be rolled out to non-technical teams for fairly simple queries.

Here’s our current Roadmap and our
Milestones.

Our immediate focus for the code is on:

• Building out the next few big features, including
  types and
  modules.
• Ensuring our supported features feel extremely robust; resolving any
  priority bugs.

We’re also spending time thinking about:

• Making it really easy to start using PRQL. We’re doing that by building
  integrations with tools that folks already use; for example our VS Code
  extension & Jupyter integration. If there are tools you’re familiar with that
  you think would be open to integrating with PRQL, please let us know in an
  issue.
• Making it easier to contribute to the compiler. We have a wide group of
  contributors to the project, but contributions to the compiler itself are
  quite concentrated. We’re keen to expand this;
  #1840 for feedback.

Get involved

To stay in touch with PRQL:

• Follow us on Twitter
• Join us on Discord
• Star this repo
• Contribute — join us in building PRQL, through writing code
  (send us your use-cases!), or
  inspiring others to use it.
• See the development documentation for PRQL. It’s easy to get
  started — the project can be built in a couple of commands, and we’re a really
  friendly community!

Explore

• PRQL Playground — experiment with PRQL in the browser.
• PRQL Book — the language documentation.
• dbt-prql — write PRQL in dbt models.
• Jupyter magic —
  run PRQL in Jupyter, either against a DB, or a Pandas DataFrame / CSV /
  Parquet file through DuckDB.
• pyprql Docs — the pyprql documentation, the
  Python bindings to PRQL, including Jupyter magic.
• PRQL VS Code extension
• prql-js — JavaScript bindings for
  PRQL.

Repo organization

This repo is composed of:

• prql-compiler — the compiler, written in rust,
  whose main role is to compile PRQL into SQL. It also includes
  prqlc, the CLI.
• web — our web content: the Book,
  Website, and Playground.
• bindings — bindings from various languages to
  prql-compiler.

It also contains our testing / CI infrastructure and development tools. Check
out our development docs for more details.

Contributors

Many thanks to those who’ve made our progress possible: