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interloper-sql

A SQL database destination for interloper: SQLDestination, a DatabaseDestination over SQLAlchemy Core, and the SQLConnection that holds the database URL.

One backend serves every SQLAlchemy dialect whose driver is installed. PostgreSQL works out of the box (the package depends on psycopg[binary]); MySQL, SQLite, Redshift, SQL Server and the rest need their own driver.

Setup

The connection is a single SQLAlchemy URL:

Database URL Driver to install
PostgreSQL postgresql+psycopg://user:password@host:5432/db none, ships with the package
MySQL / MariaDB mysql+pymysql://user:password@host:3306/db pymysql
SQL Server mssql+pyodbc://user:password@host/db?driver=ODBC+Driver+18+for+SQL+Server pyodbc (and the ODBC driver)
Redshift redshift+redshift_connector://user:password@host:5439/db sqlalchemy-redshift, redshift_connector
SQLite sqlite:///path/to/file.db none, in the standard library

Install the driver next to interloper (uv pip install pymysql, or a custom image built from the slim variant). Special characters in the password must be URL-encoded.

The URL carries the password, so it is a secret field: encrypted at rest in a deployed instance and masked in the UI. It also loads from the environment (SQL_URL), so SQLConnection() works with no arguments.

The connection's check runs SELECT 1.

Usage

import interloper as il
from interloper_sql import SQLConnection, SQLDestination

warehouse = SQLDestination(
    connection=SQLConnection(url="postgresql+psycopg://user:password@host:5432/analytics"),
    default_dataset="marketing",
)

In a deployed instance you configure this through the UI instead: add a SQL database connection, then a SQL database destination using it.

Datasets are schemas

An asset's dataset is the SQL schema its table lives in. Without one, the destination's default_dataset applies; without either, the table goes in the connection's default schema (public on PostgreSQL, the database itself on MySQL). A named schema is created on first write when the database supports schemas and it does not exist yet.

Tables

A table is created on first write from the asset's effective schema (declared, or inferred during conform): integers are BIGINT, floats DOUBLE, decimals NUMERIC(38, 9), datetimes timezone-aware timestamps, strings TEXT, and nested or repeated fields JSON. An existing table is never altered: columns it lacks are dropped from the write with a warning, and NaN or infinite floats are written as NULL.

Partitions

Writes replace, inside one transaction:

  • unpartitioned: every row is deleted, then the data inserted;
  • a time partition: the rows inside its half-open bounds (column >= start AND column < end) are deleted, then the data inserted;
  • any other partition: the rows equal to its id are deleted;
  • a window: each partition's rows are deleted, then the whole batch is inserted once.

A failed insert rolls the delete back, so a partition is never left empty. Inserts go in batches of 1000 rows. Reads return rows as list[dict]; reading a table that was never written raises DataNotFoundError.

Metadata

Release files for interloper-sql 0.105.0

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