prql
chumsky
prql | chumsky | |
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106 | 54 | |
9,436 | 3,327 | |
0.8% | - | |
9.9 | 8.8 | |
1 day ago | 5 days ago | |
Rust | Rust | |
Apache License 2.0 | MIT License |
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prql
- Prolog language for PostgreSQL proof of concept
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SQL is syntactic sugar for relational algebra
> I completely attribute this to SQL being difficult or "backwards" to parse. I mean backwards in the way that in SQL you start with what you want first (the SELECT) rather than what you have and widdling it down.
> The turning point for me was to just accept SQL for what it is.
Or just write PRQL and compile it to SQL
https://github.com/PRQL/prql
- Transpile Any SQL to PostgreSQL Dialect
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Show HN: Open-source, browser-local data exploration using DuckDB-WASM and PRQL
Hey HN! We’ve built Pretzel, an open-source data exploration and visualization tool that runs fully in the browser and can handle large files (200 MB CSV on my 8gb MacBook air is snappy). It’s also reactive - so if, for example, you change a filter, all the data transform blocks after it re-evaluate automatically. You can try it here: https://pretzelai.github.io/ (static hosted webpage) or see a demo video here: https://www.youtube.com/watch?v=73wNEun_L7w
You can play with the demo CSV that’s pre-loaded (GitHub data of text-editor adjacent projects) or upload your own CSV/XLSX file. The tool runs fully in-browser—you can disconnect from the internet once the website loads—so feel free to use sensitive data if you like.
Here’s how it works: You upload a CSV file and then, explore your data as a series of successive data transforms and plots. For example, you might: (1) Remove some columns; (2) Apply some filters (remove nulls, remove outliers, restrict time range etc); (3) Do a pivot (i.e, a group-by but fancier); (4) Plot a chart; (5) Download the chart and the the transformed data. See screenshot: https://imgur.com/a/qO4yURI
In the UI, each transform step appears as a “Block”. You can always see the result of the full transform in a table on the right. The transform blocks are editable - for instance in the example above, you can go to step 2, change some filters and the reactivity will take care of re-computing all the cells that follow, including the charts.
We wanted Pretzel to run locally in the browser and be extremely performant on large files. So, we parse CSVs with the fastest CSV parser (uDSV: https://github.com/leeoniya/uDSV) and use DuckDB-Wasm (https://github.com/duckdb/duckdb-wasm) to do all the heavy lifting of processing the data. We also wanted to allow for chained data transformations where each new block operates on the result of the previous block. For this, we’re using PRQL (https://prql-lang.org/) since it maps 1-1 with chained data transform blocks - each block maps to a chunk of PRQL which when combined, describes the full data transform chain. (PRQL doesn’t support DuckDB’s Pivot statement though so we had to make some CTE based hacks).
There’s also an AI block: This is the only (optional) feature that requires an internet connection but we’re working on adding local model support via Ollama. For now, you can use your own OpenAI API key or use an AI server we provide (GPT4 proxy; it’s loaded with a few credits), specify a transform in plain english and get back the SQL for the transform which you can edit.
Our roadmap includes allowing API calls to create new columns; support for an SQL block with nice autocomplete features, and a Python block (using Pyodide to run Python in the browser) on the results of the data transforms, much like a jupyter notebook.
There’s two of us and we’ve only spent about a week coding this and fixing major bugs so there are still some bugs to iron out. We’d love for you to try this and to get your feedback!
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Pql, a pipelined query language that compiles to SQL (written in Go)
> Looks like PRQL doesn't have a Go library so I guess they just really wanted something in Go?
There's some C bindings and the example in the README shows integration with Go:
https://github.com/PRQL/prql/tree/main/prqlc/bindings/prqlc-...
- FLaNK Stack 26 February 2024
- FLaNK Stack Weekly 19 Feb 2024
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PRQL as a DuckDB Extension
Can someone tell me why PRQL is better? I went here: https://github.com/PRQL/prql
It looks nice, but what's the strengths compared to SQL?
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Shouldn't FROM come before SELECT in SQL?
PRQL [1] is a compile-to-SQL relational querying language that puts FROM first.
[1] https://prql-lang.org
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Vanna.ai: Chat with your SQL database
https://prql-lang.org/ might be an answer for this. As a cross-database pipelined language, it would allow RAG to be intermixed with the query, and the syntax may(?) be more reliable to generate
chumsky
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Lezer: A Parsing System for CodeMirror, Inspired by Tree-Sitter
I attempted to use this but was disheartened but the fact that it doesn't statically type node names. Tree Sitter doesn't either but it has much more of an excuse given that it targets C.
https://github.com/lezer-parser/lezer/issues/8
The dev seems mildly hostile to outside involvement too, so I moved on. These days I use Chumsky which is Rust rather than Typescript, but also way more awesome, if you can deal with the often incomprehensible compilation errors at least!
https://github.com/zesterer/chumsky
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nom > regex
there’s also chumsky: https://github.com/zesterer/chumsky
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Writing an Equation Solver
We are using technique called parser combinator. And we are using a library chumsky to write parser combinators.
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loxcraft: a compiler, language server, and online playground for the Lox programming language
rust-langdev has a lot of libraries for building compilers in Rust. Perhaps you could use these to make your implementation easier, and revisit it later if you want to build things from scratch. I'd suggest logos for lexing, LALRPOP / chumsky for parsing, and rust-gc for garbage collection.
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Examples of function-based parsers in chumsky? Examples of unit tests?
The examples that come with chumsky and the chumsky tutorial and guide all define their parsers using closures.
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Flamingo - A start: the syntax, a soon-to-be-built keyword-less lang with flavoured code blocks. Seeking help and advice please :)
Parser: https://crates.io/crates/chumsky
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pep-508 v0.2.1 - Zero copy Python dependency parser written with chumsky
chumsky's zero-copy rewrite has reached its first alpha release, and I have migrated my pep-508 parser to it, as suggested in my last announcement.
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winnow = toml_edit + combine + nom
On my side, nom is still advancing well and a new major version is in preparation, with some interesting work a new GAT based design inspired from the awesome work on chumsky, that promises to bring great performance with complex error types. 2023 will be fun for parser libraries!
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Rust implementation of Python dependency parser for PEP 508
I am using chumsky because I like the API, but it doesn't support zero copy at the moment. Although efficiency is good to have, it is not my primary good. This will probably get supported once chumsky implements support for it (see upstream issue).
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Question about lexer and parser generators in Rust
Checkout https://github.com/zesterer/chumsky or https://github.com/rust-bakery/nom
What are some alternatives?
malloy - Malloy is an experimental language for describing data relationships and transformations.
nom - Rust parser combinator framework
Preql - An interpreted relational query language that compiles to SQL.
pest - The Elegant Parser
bustub - The BusTub Relational Database Management System (Educational)
pom - PEG parser combinators using operator overloading without macros.
tresql - Shorthand SQL/JDBC wrapper language, providing nested results as JSON and more
lalrpop - LR(1) parser generator for Rust
spyql - Query data on the command line with SQL-like SELECTs powered by Python expressions
instaparse
toydb - Distributed SQL database in Rust, written as a learning project
combine - A parser combinator library for Rust