dbseed 0.1.0

Auto-generate fake data for SQLAlchemy models — zero config

dbseed

Auto-generate fake data for SQLAlchemy models — zero config

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The Problem

Every project needs test data. You either write tedious factory code or install heavy libraries like Faker. For most cases, you just want 100 rows of realistic-looking data.

The Solution

pip install dbseed

from dbseed import seed

users = seed(User, SeedConfig(count=100))
session.add_all(users)
await session.commit()
# Done. 100 users with realistic names, emails, ages.

dbseed inspects your SQLAlchemy model and automatically generates the right kind of data for each column.

Smart Field Detection

Column name contains	Generated data
email	[e-mail]
name	Alice Johnson
password, hash	Random 64-char string
description, bio	Lorem ipsum text
url, link	https://example.com/word
phone	[phone]
String type	Random alphanumeric
Integer type	Random 0-10000
Float type	Random 0.0-10000.0
Boolean type	Random True/False
DateTime type	Random date within last 30 days

Override Specific Fields

from dbseed import seed, SeedConfig

users = seed(User, SeedConfig(
    count=50,
    overrides={
        "role": "admin",                    # static value
        "age": lambda: random.randint(18, 65),  # dynamic callable
    },
))

Features

• Inspects SQLAlchemy model columns automatically
• Smart name-based field detection (email, name, url, etc.)
• Type-based fallback for unknown fields
• Field overrides (static values or callables)
• Skips primary keys and server-default columns
• No external dependencies beyond SQLAlchemy
• Works with SQLAlchemy 2.0 mapped columns

License

MIT