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Скачать или смотреть How to Return Nested Aggregated Results in SQLAlchemy Core Using Postgres array_agg()

  • vlogize
  • 2025-04-05
  • 7
How to Return Nested Aggregated Results in SQLAlchemy Core Using Postgres array_agg()
Is there something like func.group_concat() in SQLALchemy Core that will return a list of objects raselectdatabase designsqlalchemyaggregate functions
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Описание к видео How to Return Nested Aggregated Results in SQLAlchemy Core Using Postgres array_agg()

Discover how to efficiently retrieve nested aggregated results from SQLAlchemy Core with Postgres by leveraging the `array_agg()` function and avoiding multiple queries.
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This video is based on the question https://stackoverflow.com/q/77695686/ asked by the user 'Phil' ( https://stackoverflow.com/u/8177724/ ) and on the answer https://stackoverflow.com/a/77700947/ provided by the user 'Gord Thompson' ( https://stackoverflow.com/u/2144390/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: Is there something like func.group_concat() in SQLALchemy Core that will return a list of objects, rather than a string?

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

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Finding Nested Aggregates in SQLAlchemy Core: The Case for array_agg()

When working with SQLAlchemy Core, data retrieval often comes with its own set of challenges—especially when it comes to aggregating results in a way that makes them easy to manage and understand. One question that frequently arises is: Is there a way to return a list of nested objects from joined many-to-many tables instead of a mere string output?

Understanding the Challenge

Imagine you have a normalized database consisting of three tables: movies, actors, and a junction table called actors_in_movies. The objective is simple: for each row of the movie, you want to retrieve all the actors in a list format.

Here's an example;

Desired Output:

For Bill & Ted's Excellent Adventure:

Output: ["Reeves, Keanu", "Carlin, George"]

For The Matrix:

Output: ["Reeves, Keanu", "Carrie-Anne Moss", "Lawrence Fishbourne"]

Typical SQL Output

A standard SELECT statement across these joined tables would return rows like:

[[See Video to Reveal this Text or Code Snippet]]

Using aggregation functions, one can compress those into counts or concatenated strings, but the desired format—nested lists—presents a unique obstacle.

The SQLAlchemy Core Solution

The short answer to whether this can be accomplished with pure SQLAlchemy Core is no—not without additional support from the SQL dialect you are using (like Postgres). Nevertheless, Postgres offers a feature that can achieve this: the array_agg() function.

Using array_agg() in Postgres

In Postgres, the array_agg() function takes care of aggregating rows into an array format. Here’s how you can set this up in SQLAlchemy Core:

[[See Video to Reveal this Text or Code Snippet]]

Breaking It Down:

Setup Tables: First, we define the necessary tables and relationships.

Insert Data: Populate the tables with sample data.

Aggregation: Use array_agg() to retrieve a list of actor names associated with each movie title.

Conclusion

In Summary, while SQLAlchemy Core does not provide a direct method for returning nested aggregates like a list of objects, leveraging specific database features—like Postgres's array_agg() function—can help accomplish this goal. This method allows you to maintain a clear structure without necessitating multiple queries or post-processing at the application level.

This approach highlights the power of SQLAlchemy in conjunction with the robust functionality of SQL databases, ensuring your data retrieval needs not only meet but exceed expectations.

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