README_HF_SPACE.md

metadata

title: MorphSQL
emoji: 🧬
colorFrom: blue
colorTo: green
sdk: gradio
sdk_version: 5.49.1
python_version: '3.11'
app_file: app.py
pinned: true
license: apache-2.0
short_description: Convert SQL to pandas, PySpark, warehouses, or dbt
tags:
  - sql
  - pandas
  - pyspark
  - code
  - data-science
  - machine-learning
  - feature-extraction
  - snowflake
  - dbt
  - data-engineering
models:
  - dgvj-work/morphsql
datasets:
  - dgvj-work/vertica-snowflake-pairs
suggested_hardware: cpu-basic

MorphSQL

Convert warehouse SQL → pandas, PySpark, Snowflake, BigQuery, or dbt — then download the result.

Package / CLI / Hub: morphsql · Space: dgvj-work/morphsql

How to use (30 seconds)

1. Open the Convert tab
2. Pick source dialect + Convert to target
3. Load an example, paste SQL, or upload a .sql / .zip
4. Click Convert or Upload & Convert → Download
5. Download the .py / .sql / .zip to your machine

Target	Download
pandas / PySpark	.py ready for notebooks / Databricks
Snowflake / BigQuery	.sql
dbt	.txt project preview (or zip for batches)

Python API

from morphsql.ai import pipeline

out = pipeline("sql-migration")(
    "SELECT COALESCE(a, 0) FROM t",
    source="snowflake",
    target="pandas",  # or "pyspark", "snowflake", "bigquery", "dbt-snowflake"
)
print(out["converted_sql"][:500])

More tab

Object risk assess · repo workbench · ML feature SQL · copilot · dialect notes · offline eval

Author: Digvijay Waghela · Apache-2.0 · GitHub