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dbslice

Extract minimal, referentially-intact database subsets for local development and debugging.

The Problem

Copying an entire production database to your machine is infeasible. But reproducing a bug often requires having the exact data that caused it. dbslice solves this by extracting only the records you need, following foreign key relationships to ensure referential integrity.

Quick Example

# Extract an order and all related records
dbslice extract postgres://localhost/myapp --seed "orders.id=12345" > subset.sql

# Import into local database
psql -d localdb < subset.sql

Key Features

Feature Description
Zero-config Introspects schema automatically, no data model file required
Single command Extract complete data subsets with one command
Safe by default Auto-detects and anonymizes sensitive fields
Cross-database PostgreSQL, MySQL, SQLite with identical interface
Virtual FKs Support for Django GenericForeignKeys and implicit relationships

Getting Started

Step Link Description
1 Installation Install dbslice and dependencies
2 Quick Start Extract your first subset in 5 minutes
3 CLI Reference Learn all available options
4 Configuration Set up YAML config files

Use Cases

Scenario How dbslice helps
Debug a production bug Extract the failing order and all related data
Create test fixtures Extract representative data samples with anonymization
Seed development database Get realistic data without the full database dump
Data migration testing Extract subset to test migration scripts safely

How It Works

┌──────────────┐     ┌──────────────┐     ┌──────────────┐
│   Seed ID    │────▶│  FK Graph    │────▶│  Topo Sort   │
│ orders.id=1  │     │  Traversal   │     │  & Output    │
└──────────────┘     └──────────────┘     └──────────────┘
                            │
                     ┌──────┴──────┐
                     │             │
                 ┌───▼───┐   ┌─────▼─────┐
                 │ users │   │ products  │
                 └───────┘   └───────────┘
  1. Introspect - Reads database schema to discover tables and FK relationships
  2. Traverse - Starting from seed record(s), follows FK relationships via BFS
  3. Extract - Fetches all identified records
  4. Sort - Topologically sorts tables for correct INSERT order
  5. Output - Generates SQL/JSON/CSV with proper escaping

Documentation