Jupyter Magic

The %%misata cell magic lets you generate synthetic datasets from a plain-English story directly inside a Jupyter notebook — no imports, no schema objects, no boilerplate.

Setup

Load the extension once per session (put it in your first cell):

%load_ext misata.magic

To load automatically on every notebook startup, add it to your IPython profile:

# ~/.ipython/profile_default/ipython_config.py
c.InteractiveShellApp.extensions = ["misata.magic"]

Basic usage

%%misata
SaaS company with users, subscriptions, and monthly payments

After running, the following variables appear in your namespace:

_misata — dict of all DataFrames
users_df, subscriptions_df, payments_df — one variable per table

Options

%%misata rows=5000 seed=42
fintech app with transactions, wallets, and fraud flags

Option	Default	Description
`rows`	`1000`	Number of rows for the primary table
`seed`	`None`	Random seed for reproducibility

Example workflow

%%misata rows=2000 seed=123
food delivery app with restaurants, customers, couriers, and orders

# Immediately available in the next cell:
orders_df.head()

import matplotlib.pyplot as plt
orders_df["customer_rating"].hist(bins=20)
plt.title("Order Rating Distribution")

# Check delivery time vs rating correlation
orders_df[["delivery_minutes", "customer_rating"]].corr()

Rich output

The magic prints a summary table after generation:

[misata] Generating: "food delivery app with restaurants, customers..."  rows=2000
  → restaurants_df  (100 rows × 10 cols)
  → customers_df    (2000 rows × 8 cols)
  → couriers_df     (50 rows × 8 cols)
  → orders_df       (2000 rows × 13 cols)
  → order_items_df  (5000 rows × 7 cols)

Followed by an HTML table in Jupyter with table names, row counts, and column previews.

Accessing the full dict

# All tables in one place
for name, df in _misata.items():
    print(f"{name}: {df.shape}")

Reproducibility

%%misata rows=500 seed=42
ecommerce store with products and orders

Same seed → identical output every time. Useful for notebook demos that need consistent results.

Supported domains

All 12 built-in domains work with the magic: saas, ecommerce, fintech, healthcare, marketplace, logistics, hr, social, realestate, fooddelivery, edtech, gaming.

For open-ended stories, add GROQ_API_KEY to your environment and the magic will automatically use LLM-powered schema generation.