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https://github.com/max-sixty/prql
PRQL is a modern language for transforming data — a simple, powerful, pipelined SQL replacement
https://github.com/max-sixty/prql
Last synced: 11 days ago
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PRQL is a modern language for transforming data — a simple, powerful, pipelined SQL replacement
- Host: GitHub
- URL: https://github.com/max-sixty/prql
- Owner: max-sixty
- License: apache-2.0
- Fork: true (PRQL/prql)
- Created: 2022-12-23T06:38:31.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-04-01T20:31:34.000Z (7 months ago)
- Last Synced: 2024-04-01T21:23:22.070Z (7 months ago)
- Language: Rust
- Homepage: https://prql-lang.org
- Size: 19.8 MB
- Stars: 33
- Watchers: 2
- Forks: 1
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: .github/CONTRIBUTING.md
- License: LICENSE
- Code of conduct: .github/CODE_OF_CONDUCT.md
Awesome Lists containing this project
README
# PRQL
[](https://prql-lang.org)
[](https://prql-lang.org/playground)
[](https://prql-lang.org/book)
[](https://discord.gg/eQcfaCmsNc)
[](https://twitter.com/prql_lang)
[](https://github.com/PRQL/prql/actions?query=branch%3Amain+workflow%3Atests)
[](https://github.com/PRQL/prql/graphs/contributors)
[](https://github.com/PRQL/prql/stargazers)
**P**ipelined **R**elational **Q**uery **L**anguage, 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:
```elm
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 larger example of the language:
```elm
from employees
filter start_date > @2021-01-01 # Clear date syntax
derive { # `derive` adds columns / variables
gross_salary = salary + (tax ?? 0), # Terse coalesce
gross_cost = gross_salary + benefits_cost, # Variables can use other variables
}
filter gross_cost > 0
group {title, country} ( # `group` runs a pipeline over each group
aggregate { # `aggregate` reduces each group to a value
average gross_salary,
sum_gross_cost = sum gross_cost, # `=` sets a column name
}
)
filter sum_gross_cost > 100_000 # `filter` replaces both of SQL's `WHERE` & `HAVING`
derive id = f"{title}_{country}" # F-strings like Python
derive country_code = s"LEFT(country, 2)" # S-strings allow using SQL as an escape hatch
sort {sum_gross_cost, -country} # `-country` means descending order
take 1..20 # Range expressions (also valid here as `take 20`)
```
For more on the language, more examples & comparisons with SQL, visit
[prql-lang.org][prql website]. To experiment with PRQL in the browser, check out
[PRQL Playground][prql playground].
## Current Status - June 2024
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 bugs and some missing features, and is probably only ready
to be rolled out to non-technical teams for fairly simple queries.
In particular, we're working on a new resolver, which will let us squash many
bugs and simplify our code a lot. It'll also let us scale the language without
scaling the complexity of the compiler.
While we work on that, we're also focusing on
- Ensuring our supported features feel extremely robust; resolving any
[priority bugs](https://github.com/PRQL/prql/issues?q=is%3Aissue+is%3Aopen+label%3Abug+label%3Apriority).
As more folks have started using PRQL, we've had more bug reports — good news,
but also gives us more to work on.
- Filling remaining feature gaps, so that PRQL is possible to use for almost all
standard SQL queries.
- Expanding our set of supported features — we are working to add experimental
support for modules / multi-file projects, and for auto-formatting.
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 a VS Code
extension, Jupyter integration, and the recent
[qStudio](https://www.timestored.com/qstudio/prql-ide) 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.
- Whether all our initial decisions were correct — for example
[how we handle window functions outside of a `window` transform](https://github.com/PRQL/prql/issues/2723).
- 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](https://github.com/PRQL/prql/issues/1840) for feedback, some
suggestions on starter issues are below.
## Get involved
To stay in touch with PRQL:
- Follow us on [Twitter](https://twitter.com/prql_lang)
- Join us on [Discord](https://discord.gg/eQcfaCmsNc)
- Star this repo
- [Contribute][contributing] — join us in building PRQL, through writing code
[(send us your use-cases!)](https://github.com/PRQL/prql/discussions), or
inspiring others to use it.
- See the [development][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!
- For those who might be interested in contributing to the code now, check out
issues with the
[good first issue](https://github.com/PRQL/prql/labels/good%20first%20issue)
label. Always feel free to ask questions or open a draft PR.
## Explore
- [PRQL Playground][prql playground] — experiment with PRQL in the browser.
- [PRQL Book][prql book] — the language documentation.
- [Jupyter magic](https://pyprql.readthedocs.io/en/latest/magic_readme.html) —
run PRQL in Jupyter, either against a DB, or a Pandas DataFrame / CSV /
Parquet file through DuckDB.
- [pyprql Docs](https://pyprql.readthedocs.io) — the pyprql documentation, the
Python bindings to PRQL, including Jupyter magic.
- [PRQL VS Code extension](https://marketplace.visualstudio.com/items?itemName=prql-lang.prql-vscode)
- [prqlc-js](https://www.npmjs.com/package/prqlc) — JavaScript bindings for
PRQL.
## Repo organization
This repo is composed of:
- **[prqlc](./prqlc/)** — the compiler, written in rust, whose main role is to
compile PRQL into SQL. Also contains the CLI and bindings from various
languages.
- **[web](./web/)** — our web content: the [Book][prql book],
[Website][prql website], and [Playground][prql playground].
It also contains our testing / CI infrastructure and development tools. Check
out our [development docs][development] for more details.
## Contributors
Many thanks to those who've made our progress possible:
[](https://github.com/PRQL/prql/graphs/contributors)
[prql book]: https://prql-lang.org/book
[prql website]: https://prql-lang.org
[contributing]: https://prql-lang.org/book/project/contributing/
[development]: https://prql-lang.org/book/project/contributing/development.html
[prql playground]: https://prql-lang.org/playground