pipeql 1.1.1

Pipelined, Injection-Safe, Polyglot Query & Mutation Language

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Write queries once in a clean, left-to-right UNIX pipeline syntax (|). PipeQL compiles directly to target-native SQL for PostgreSQL, SQLite, DuckDB, and MySQL in ~19µs, with 100% structural parameter extraction.

from orders
| join customers on orders.customer_id == customers.id
| filter orders.status == 'active' and orders.total >= $min
| group [region] (total = sum(orders.total), cnt = count(*))
| filter total > $threshold
| select [region, total, cnt]
| sort [total desc]
| take 10

Compiles to PostgreSQL:

SELECT region, SUM(orders.total) AS total, COUNT(*) AS cnt FROM orders
INNER JOIN customers ON (orders.customer_id = customers.id)
WHERE ((orders.status = $1) AND (orders.total >= $2))
GROUP BY region
HAVING (sum(orders.total) > $3)
ORDER BY total DESC
LIMIT 10;

Parameters: ["active", "min", "threshold"]. Every string literal and $param reference is extracted at the AST level into positionally bound parameter arrays.

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Language Ecosystem & Availability Matrix

Language / SDK	Package / Binding	Status	Dialects Supported
Rust	pipeql-core (Native Crate)	✅ Supported	Postgres, SQLite, DuckDB, MySQL
JavaScript / TypeScript	@flaxmbot/pipeql (WASM)	✅ Supported	Postgres, SQLite, DuckDB, MySQL
Python	pipeql (PyO3 ABI3)	✅ Supported	Postgres, SQLite, DuckDB, MySQL
C / C++	libpipeql (CFFI Header)	✅ Supported	Postgres, SQLite, DuckDB, MySQL
Go	pipeql/go (CGO Bridge)	✅ Supported	Postgres, SQLite, DuckDB, MySQL

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Installation & Setup Guide

1. Pre-built CLI & Native Shared Libraries

Download pre-compiled release binaries and shared CFFI libraries directly from GitHub Releases (v1.1.0):

Platform	CLI Executable	Shared Library (CFFI / Go)
Windows (x64)	pipeql-windows-x86_64.exe	pipeql_cffi.dll
Linux (x64)	pipeql-linux-x86_64	libpipeql_cffi.so
macOS (x64)	pipeql-macos-x86_64	libpipeql_cffi.dylib

Using CLI directly:

# Compile PipeQL query to PostgreSQL SQL
./pipeql-linux-x86_64 compile "from users | filter age >= $min | select [id, name]" --dialect postgres

# Compile PipeQL query to SQLite SQL
pipeql-windows-x86_64.exe compile "from notes | filter id == $id" --dialect sqlite

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2. Rust Core Crate & CLI

Build from source or add pipeql-core to your Cargo.toml:

[dependencies]
pipeql-core = { git = "https://github.com/Flaxmbot/PipeQL.git" }

Build & install CLI locally:

cargo install --path crates/pipeql-cli
pipeql compile "from users | take 10" --dialect postgres

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3. JavaScript / TypeScript (Node.js & WebAssembly)

Install from npm or from the GitHub release package:

# Install via npm
npm install @flaxmbot/pipeql

# Or install directly from GitHub release tarball
npm install https://github.com/Flaxmbot/PipeQL/releases/download/v1.1.0/flaxmbot-pipeql-1.1.0.tgz

Usage:

import { compile } from '@flaxmbot/pipeql';

const { sql, params } = compile(
  "from notes | filter category == $cat | sort [updated_at desc]",
  "sqlite"
);

console.log(sql);    // SELECT * FROM notes WHERE (category = ?) ORDER BY updated_at DESC;
console.log(params); // ["cat"]

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4. Python (pipeql)

Install from PyPI or install the release wheel:

# Install via pip
pip install pipeql

# Or build locally using maturin
pip install maturin
maturin develop -m crates/pipeql-python/Cargo.toml

Usage:

import pipeql_python as pipeql

res = pipeql.compile("into users | insert [name = $name, email = $email]", "postgres")
print(res["sql"])    # INSERT INTO users (name, email) VALUES ($1, $2) RETURNING *;
print(res["params"]) # ["name", "email"]

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5. C / C++ (libpipeql)

Include the CFFI header crates/pipeql-cffi/include/libpipeql.h and link against libpipeql_cffi:

Build CFFI library locally:

cargo build --release -p pipeql-cffi
# Linux: target/release/libpipeql_cffi.so
# macOS: target/release/libpipeql_cffi.dylib
# Windows: target/release/pipeql_cffi.dll

C Example (demo.c):

#include <stdio.h>
#include "libpipeql.h"

int main() {
    PipeqlError err = {0};
    PipeqlResult* res = pipeql_compile("from users | filter id == $id", "postgres", &err);
    if (!res) {
        fprintf(stderr, "Error: %s\n", err.message);
        return 1;
    }
    printf("Generated SQL: %s\n", res->sql);
    pipeql_result_free(res);
    return 0;
}

Compile & link:

gcc demo.c -I./crates/pipeql-cffi/include -L./target/release -lpipeql_cffi -o demo
./demo

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6. Go (pipeql/go)

Import the Go binding and link libpipeql_cffi:

go get github.com/Flaxmbot/PipeQL/go

Go Example:

package main

import (
    "fmt"
    "log"
    "github.com/Flaxmbot/PipeQL/go"
)

func main() {
    res, err := pipeql.Compile("from users | filter age >= $min | select [id, name]", "postgres")
    if err != nil {
        log.Fatal(err)
    }
    fmt.Println("SQL:", res.SQL)
    fmt.Println("Params:", res.Params) // ["min"]
}

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Features

• 4 Dialects in One Pass: PostgreSQL ($1), SQLite (?), DuckDB (?), MySQL (?).
• 100% Parameter Extraction: Strings ('active') and explicit parameters ($min, ${min}) are automatically extracted into typed bind parameters.
• Lossless AST: Spans and comments survive parsing for IDE language servers (pipeql-lsp) and formatters.
• Sub-Millisecond Speed: Measured average compilation latency of ~19µs per query.
• Zero Unsafe Core: Enforces #![deny(unsafe_code)] across the entire compiler engine.
• Upsert: Insert-or-update with ON CONFLICT ... DO UPDATE SET (Postgres/SQLite/DuckDB) or ON DUPLICATE KEY UPDATE (MySQL).
• Subqueries: Nested pipelines via in (from ...) for correlated and uncorrelated subqueries.
• Union / Union All: Combine result sets from multiple statements with union or union all.
• Live Playground: Interactive browser-based playground with WASM compilation for all 4 dialects.

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AI & LLM Integration (System Prompt)

PipeQL is designed for first-class AI code generation. The repository includes an optimized LLM System Prompt (ai/system_prompt.md) that instructs models (OpenAI GPT-4, Claude, Gemini, LangChain, etc.) on how to write valid, injection-safe PipeQL code.

Accessing the System Prompt:

• Python SDK:

  import pipeql_python
  
  # Access the pre-loaded LLM System Prompt string
  system_prompt = pipeql_python.SYSTEM_PROMPT
  

• JavaScript / Node.js: Included in the @flaxmbot/pipeql npm package at @flaxmbot/pipeql/ai/system_prompt.md.

• GitHub Release / Direct Link: Download pipeql-ai-system-prompt.md or fetch directly via raw URL: https://raw.githubusercontent.com/Flaxmbot/PipeQL/master/ai/system_prompt.md

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Architecture

The compilation pipeline has 3 stages:

1. Source Lexing — Hand-written lexer tokenizes inputs preserving character positions (for LSP/IDE support).
2. Parsing & AST — Pratt parser translates tokens into a lossless abstract syntax tree.
3. Parameter Isolation + SQL Codegen — Parser walks the AST, extracts all constants into bind parameters, and generates dialect-specific SQL.

All language bindings (JS, Python, C, Go) are thin wrappers that call the Rust core through pipeql-core's api.rs facade.

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Project Structure

PipeQL/
├── crates/
│   ├── pipeql-core/        # Core compiler (lexer, parser, AST, codegen)
│   ├── pipeql-cli/         # CLI tool
│   ├── pipeql-cffi/        # C ABI shared library (libpipeql_cffi)
│   ├── pipeql-wasm/        # WebAssembly target
│   ├── pipeql-python/      # Python bindings (PyO3)
│   └── pipeql-lsp/         # Language server protocol
├── js/                     # JavaScript/TypeScript SDK (@pipeql/js)
├── python/                 # Python package
├── go/                     # Go binding (CGO)
├── docs/                   # Specification and documentation
├── docs-web/               # Interactive documentation website
├── examples/               # Sample .pql query files
├── extensions/             # VS Code extension
├── tree-sitter-pipeql/     # Tree-sitter grammar
└── Notes/                  # Example CRUD application

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License

MIT