DataPyn - Professional SQL + Python IDE

GitHub Copilot Integration

Your AI Data Assistant

Chat with GitHub Copilot to create queries, generate visualizations, and manage your data workflow naturally.

Natural Language

Ask questions about your data in plain language. Copilot generates the SQL or Python code automatically.

Create Blocks

Copilot can create, edit, and execute code blocks directly. Watch your analysis build itself.

Schema Aware

Ask about your tables and columns. Copilot reads the database schema to give accurate suggestions.

Visualizations

Say "create a chart" and Copilot generates matplotlib code, executes it, and shows the result.

Requires a GitHub Copilot subscription (not included with DataPyn)

GitHub Copilot

Ready to help

Show me the top 10 customers by revenue

Copilot

I'll create a SQL block to query that data.

SELECT name, SUM(revenue)
FROM customers
GROUP BY name LIMIT 10

Block created and executed

Now create a bar chart with the results

Copilot

Creating a Python block with matplotlib visualization.

plt.barh(df['name'], df['revenue'])
plt.title('Top Customers')
plt.show()

Chart rendered

SQL + Python

Two Languages, One Document

Combine SQL queries and Python code in the same file. Query your data, then visualize and transform it - all without switching tools.

Mix Freely

Alternate between SQL and Python blocks in any order

Shared Namespace

SQL results become DataFrames, accessible in Python blocks

Run All

Execute individual blocks or run the entire document sequentially

analysis.dmp - DataPyn

SQL

Production DB top_customers

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SELECT name, SUM(amount) AS total
FROM orders
GROUP BY name
ORDER BY total DESC LIMIT 10

10 rows | top_customers = DataFrame

Python

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# top_customers from SQL block
import matplotlib.pyplot as plt
plt.barh(top_customers['name'], top_customers['total'])
plt.show()

Top 10 Customers by Revenue

Built for Data Professionals

A complete toolkit designed to streamline your data analysis workflow

Mixed Code Blocks

Write SQL and Python in the same document. Query results are automatically available as Pandas DataFrames.

Per-Block Connections

Each SQL block can use a different database connection. Work with multiple data sources in a single document.

Multiple Sessions

Each tab maintains its own connection and Python namespace. Compare data across environments with ease.

Drag and Drop Import

Drop CSV, JSON, Excel, or connection files directly into the editor. Import code is generated automatically.

Block Editor

Execute individual blocks with F5 or run all with Ctrl+F5. Each block is independent.

Integrated Visualization

Built-in Matplotlib support. Create charts directly from your query results without leaving the IDE.

Export Options

Export your work as standalone Python scripts, ready to run in production or share with your team.

Auto Updates

Automatic update notifications keep you on the latest version with new features and improvements.

Quick Start

Get started in under 5 minutes

Clone the repository

$ git clone https://github.com/natharuc/datapyn.git
$ cd datapyn

Install dependencies

$ python -m venv .venv
$ .venv\Scripts\activate
$ pip install -r requirements.txt

Run DataPyn

$ python source/main.py

Prefer a standalone installer?

Download the Windows MSI from Releases. No Python installation required.

Open Source

Built for the community

DataPyn is 100% open source under the MIT license. Contribute, report bugs, suggest features, or simply use it freely in your projects.

View Repository Report Issue

MIT License

Fork Welcome

PRs Accepted

SQL and Python.
One unified workflow.

Your AI Data Assistant

Natural Language

Create Blocks

Schema Aware

Visualizations

Two Languages, One Document

Mix Freely

Shared Namespace

Run All

Built for Data Professionals

Mixed Code Blocks

Per-Block Connections

Multiple Sessions

Drag and Drop Import

Block Editor

Integrated Visualization

Export Options

Auto Updates

Database Support

SQL Server

MySQL

PostgreSQL

MariaDB

SQLite

Databricks

Quick Start

Clone the repository

Install dependencies

Run DataPyn

Prefer a standalone installer?

Documentation

Getting Started

Features

Copilot Integration

Shortcuts

Built for the community

Ready to streamline your data workflow?

SQL and Python. One unified workflow.

Your AI Data Assistant

Natural Language

Create Blocks

Schema Aware

Visualizations

Two Languages, One Document

Mix Freely

Shared Namespace

Run All

Built for Data Professionals

Mixed Code Blocks

Per-Block Connections

Multiple Sessions

Drag and Drop Import

Block Editor

Integrated Visualization

Export Options

Auto Updates

Database Support

SQL Server

MySQL

PostgreSQL

MariaDB

SQLite

Databricks

Quick Start

Clone the repository

Install dependencies

Run DataPyn

Prefer a standalone installer?

Documentation

Getting Started

Features

Copilot Integration

Shortcuts

Built for the community

Ready to streamline your data workflow?

SQL and Python.
One unified workflow.