to_sql append mode and write idempotency limits

Handling Duplicate Rows During Retries

The to_sql method in pandas provides the if_exists='append' parameter to add data to an existing database table. However, this mode performs standard SQL inserts without native support for "upsert" or "insert ignore" logic.

When a network timeout or database interruption occurs during a large write operation, retrying the process often leads to duplicate records if the previous attempt partially succeeded. While chunksize can manage memory and transaction boundaries, it does not inherently prevent the duplication of rows already committed to the target table.

Given that if_exists='replace' removes all table constraints and indexes, it is unsuitable for maintaining data integrity during retries.

Technical Uncertainties

• What is the most efficient way to ensure idempotency when using to_sql without manually implementing a staging table pattern?
• Does the method='multi' parameter influence transaction atomicity in a way that mitigates partial write duplication across different SQLAlchemy dialects?