Announcing the Comquest Developer Toolkit.

We open-sourced the internal utilities we use to shave hours off mundane data tasks. Convert schemas, generate Pydantic models, and lint SQL costs—right from your browser.

If you work in data engineering, you know the dirty secret of the industry: the 80/20 rule is optimistic.

We spend maybe 20% of our time architecting resilient, scalable pipelines. The other 80%? It's spent battling the mundane: manually mapping PostgreSQL types to Snowflake, writing boilerplate Python to ingest a messy JSON payload, or trying to figure out why a legacy cron job silently failed at 3:00 AM.

This isn't engineering; it's syntax wrangling. And it’s a massive drain on velocity.

At Comquest, we build massive-scale data platforms for enterprise clients every day. Over time, we got tired of repeating the same manual tasks. So, we started building internal scripts—regex parsers, AST generators, and heuristic analyzers—to automate the boring parts.

Today, we are taking those internal utilities out of our private repos and putting them on the web, free for the community. Introducing the Comquest Developer Toolkit.

The "Why" Behind The Hub

We didn't build these tools to sell you anything. We built them because we needed them.

We believe that data engineers should focus on high-value problems—data modeling, reliability, and scalability—not on typing out CREATE TABLE statements by hand. This hub is our contribution to the data community to help everyone move faster. There are no logins, no paywalls, and no API keys required. Just paste your code, get the output, and get back to work.

1. The Universal Schema Converter

The Pain: Migrating an operational database (like MySQL or Postgres) to a cloud warehouse (like Snowflake) usually involves hours of tedious DDL translation and data type mapping.

The Fix: Paste your existing DDL. Select your target warehouse. Our converter handles the dialect specifics, typecasting, and syntax changes instantly.

2. JSON to Pydantic & PySpark Generator

The Pain: Ingesting data from an external API without strict typing is a recipe for silent failures downstream. Writing data classes by hand for massive nested JSON payloads is agonizing.

The Fix: Paste a sample JSON payload. We instantly generate strictly-typed Python Pydantic models or Databricks StructTypes ready for your production pipelines. Stop treating your data lake like a schema-less dumpster.

3. The Warehouse Cost Exploder

The Pain: In columnar databases like Snowflake and BigQuery, a bad query doesn't just slow things down—it costs real money. A junior analyst running an unbounded SELECT * on a petabyte table can burn thousands of dollars in minutes.

The Fix: Paste your query before you run it. Our linter scans for expensive anti-patterns like unbounded scans, leading wildcards in LIKE clauses, and missing partition filters.

4. Cron to Apache Airflow Converter

The Pain: Thousands of critical data pipelines still run on fragile, unmonitored Linux crontab files. Migrating them to a modern orchestrator is necessary but tedious.

The Fix: Paste your messy crontab file. Our engine parses the schedule expressions, groups dependent tasks, and generates boilerplate Python Airflow DAGs using modern TaskFlow syntax.

Build Faster.

This toolkit is just version 1.0. We have more utilities in the pipeline, including a CSV Schema Inferencer and an automated SQL-to-CSV script generator.

We hope these tools save you as much time as they’ve saved us. Go break things (in dev).