Smoke Test Source

The Smoke Test source generates synthetic test data for destination regression testing. It produces records across 15 predefined scenarios covering common destination failure patterns: type variations, null handling, naming edge cases, schema variations, and batch sizes.

All business logic lives in PyAirbyte's airbyte.cli.smoke_test_source module. This connector is a thin wrapper that delegates to it.

Features

Feature	Supported
Full Refresh Sync	Yes
Incremental Sync	No

Getting Started

This connector requires no configuration. It generates synthetic data deterministically.

Supported Streams

Fast Scenarios (default)

• basic_types — string, integer, number, boolean (3 records)
• timestamp_types — date, datetime, epoch values (3 records)
• large_decimals_and_numbers — precision, large integers, boundary values (3 records)
• nested_json_objects — nested objects, arrays, deep nesting (2 records)
• null_handling — null across all types, always-null columns (3 records)
• column_naming_edge_cases — CamelCase, dashes, dots, spaces, SQL reserved words (1 record)
• table_naming_edge_cases — special characters in stream name (1 record)
• CamelCaseStreamName — CamelCase stream name handling (1 record)
• wide_table_50_columns — 50-column table with nullable strings (2 records)
• empty_stream — zero records (0 records)
• single_record_stream — exactly one record (1 record)
• unicode_and_special_strings — emoji, CJK, Cyrillic, escape sequences (4 records)
• schema_with_no_primary_key — append-only / no dedup (3 records)
• long_column_names — column names exceeding typical DB limits (1 record)

Slow Scenarios

• large_batch_stream — 1000 records for batch/flush testing

Changelog

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Version	Date	Pull Request	Subject
0.1.0	2026-03-18	75181	Initial release: smoke test source for destination regression testing

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