Best Practices¶

Top tips for effective use of dbslice.

1. Start with Low Depth, Increase If Needed¶

dbslice extract postgres://host/db --seed "orders.id=123" --depth 1

Default depth is 3. Reduce for faster, smaller extractions. Increase (up to 5-10) only if you are missing related data.

2. Always Anonymize Production Data¶

dbslice extract postgres://prod/db --seed "users.id=1" --anonymize

Never extract production data without --anonymize. Foreign keys are preserved automatically.

3. Validate Extractions¶

dbslice extract postgres://host/db --seed "orders.id=123" --validate --fail-on-validation-error

Validation checks that all FK references point to included records. Enable --fail-on-validation-error in scripts and CI.

4. Use Config Files for Repeatable Extractions¶

dbslice init postgres://localhost/myapp --out-file dbslice.yaml
dbslice extract --config dbslice.yaml --seed "orders.id=123"

Store settings in YAML for consistency. Use environment variables for credentials (url: ${DATABASE_URL}).

5. Exclude Large Non-Essential Tables¶

dbslice extract postgres://host/db --seed "orders.id=123" \
  --exclude audit_logs \
  --exclude analytics_events

Audit logs, analytics, and session tables are often huge and unnecessary for debugging.

6. Use Streaming for Large Datasets¶

dbslice extract postgres://host/db \
  --seed "orders:created_at > '2023-01-01'" \
  --stream --out-file large.sql

Streaming writes directly to file, avoiding out-of-memory errors. Required for datasets over 100K rows.

7. Use Read-Only Accounts on Production¶

CREATE USER dbslice_readonly WITH PASSWORD 'secure_password';
GRANT CONNECT ON DATABASE myapp TO dbslice_readonly;
GRANT USAGE ON SCHEMA public TO dbslice_readonly;
GRANT SELECT ON ALL TABLES IN SCHEMA public TO dbslice_readonly;

Prefer read replicas over primary servers.

8. Profile Slow Extractions¶

dbslice extract postgres://host/db --seed "orders.id=123" --profile --verbose

Profiling identifies which queries are slow and suggests missing indexes.

9. Use JSON for Cross-Database Workflows¶

dbslice extract postgres://host/db --seed "orders.id=1" --output json --out-file fixtures/

JSON is database-agnostic and works well for test fixtures in any language.

10. Test Import Before Using¶

createdb test_import
psql -d test_import < schema.sql
psql -d test_import < subset.sql
psql -d test_import -c "SELECT COUNT(*) FROM orders;"
dropdb test_import

Always verify extracted data loads cleanly into an isolated database before relying on it.