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PRQL compiler CLI - prqlc PRQL Developers
Use this command to install PRQL compiler CLI - prqlc:
winget install --id=PRQL.prqlc -e prqlc serves as a CLI for the PRQL compiler.
PRQL Compiler CLI (prqlc)
PRQL Compiler CLI (prqlc) is a command-line tool designed to compile PRQL, a modern language for transforming data, into SQL or other formats. PRQL provides a more intuitive and readable alternative to traditional SQL by enabling users to write pipelined transformations that are both explicit and declarative.
Key Features:
- Intuitive Query Language: Write clean, maintainable queries using PRQL's logical pipeline syntax.
- SQL Compilation: Automatically convert PRQL into optimized SQL for execution in relational databases.
- Versatile Output: Support for generating output in multiple formats, including SQL and JSON.
- Database Compatibility: Works with any database that supports SQL by compiling PRQL queries accordingly.
- Installable via winget: Easily install prqlc on Windows using the winget package manager.
Audience & Benefit:
Ideal for data engineers, analysts, and anyone working with relational databases to streamline query writing and improve code readability. By using PRQL, users can reduce complexity in their data transformation pipelines while maintaining clarity and performance through efficient SQL compilation.
README
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 larger example of the language:
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`)
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