rs-mock 0.2.0

Mock Redshift locally by transpiling Redshift SQL to DuckDB and running it.

rs-mock

A super lightweight, in-process Redshift mocker for test suites.

rs-mock transpiles Redshift SQL to duckdb SQL with sqlglot and runs it against an in-memory duckdb database. No cluster, no network, no Docker — just fast, in-process SQL.

Usage

from rs_mock import RedshiftMock

rs = RedshiftMock()

# DDL / DML — state persists across calls for the instance's lifetime
rs.execute("CREATE TABLE users (id INT, name VARCHAR)")
rs.execute("INSERT INTO users VALUES (1, 'alice'), (2, 'bob')")

# SELECTs, JOINs, CTEs — execute() returns the duckdb cursor
rows = rs.execute("SELECT id, name FROM users ORDER BY id").fetchall()
# [(1, 'alice'), (2, 'bob')]

# Need duckdb power features? Grab the cursor or the connection.
df = rs.execute("SELECT * FROM users").df()
rs.connection  # the underlying duckdb connection

Supported: regular selects, joins, CTEs, and DDL/DML. Redshift-specific syntax (e.g. GETDATE()) is rewritten to its duckdb equivalent automatically.

S3: UNLOAD and COPY

UNLOAD and COPY ... FROM 's3://...' are supported against real S3 or, in tests, a moto-mocked bucket — no cluster and no network. Install the extra (pip install 'rs-mock[s3]') to pull in boto3, then run UNLOAD/COPY like any other statement inside a mock_aws context:

import boto3
from moto import mock_aws
from rs_mock import RedshiftMock

with mock_aws():
    boto3.client("s3").create_bucket(Bucket="my-bucket")

    rs = RedshiftMock()
    rs.execute("CREATE TABLE users (id INT, name VARCHAR)")
    rs.execute("INSERT INTO users VALUES (1, 'alice'), (2, 'bob')")

    # Query result -> S3 (CSV, PARQUET, JSON, or default pipe-delimited text)
    rs.execute(
        "UNLOAD ('SELECT * FROM users') TO 's3://my-bucket/users_' "
        "IAM_ROLE 'arn:aws:iam::123:role/r' FORMAT AS PARQUET"
    )

    # S3 -> table (every object under the prefix is loaded)
    rs.execute("CREATE TABLE loaded (id INT, name VARCHAR)")
    rs.execute(
        "COPY loaded FROM 's3://my-bucket/users_' "
        "IAM_ROLE 'arn:aws:iam::123:role/r' FORMAT AS PARQUET"
    )

Recognized options: UNLOAD FORMAT AS {CSV|PARQUET|JSON}, DELIMITER, HEADER; COPY FORMAT AS {CSV|PARQUET|JSON}, DELIMITER, IGNOREHEADER, and a column list. Authorization (IAM_ROLE/CREDENTIALS) is parsed but ignored — boto3's own credential resolution (or moto) applies.

Development

make test   # run tests
make lint   # ruff + pyrefly
make prek   # pre-commit hooks