Engineering

Pytest for Agent-Generated Code: Concrete Testing Strategies to Put Into Practice

January 26, 2026

Pytest for Agent-Generated Code: Concrete Testing Strategies to Put Into Practice

When agents write tests, intent matters as much as correctness. By defining clear testing levels, preferred patterns, and explicit anti-patterns, we give agents the structure they need to produce fast, reliable Pytest suites that scale with automation.

Dennis Hume

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Type Hinting in Python

August 11, 2023

Type Hinting in Python

In part VI of our Data Engineering with Python series, we explore type hinting functions and classes, and how type hints reduce errors.

Elliot Gunn

Environment Variables in Python

August 7, 2023

Environment Variables in Python

In part V of our series on Data Engineering with Python, we cover best practices for managing environment variables in Python.

Elliot Gunn

Orchestrating dbt™ with Dagster

August 1, 2023

Orchestrating dbt™ with Dagster

Orchestrate dbt with Dagster’s popular dbt integration, now with major enhancements to supercharge your dbt models as part of your data pipeline.

Rex Ledesma

Speeding up the dbt™ docs by 20x with React Server Components

July 31, 2023

Speeding up the dbt™ docs by 20x with React Server Components

dbt docs slow? See how we dropped page load time and memory usage for a large dbt project by 20x using React Server Components.

Jordan Sanders

LLM training pipelines with Langchain, Airbyte, and Dagster

July 5, 2023

LLM training pipelines with Langchain, Airbyte, and Dagster

This tutorial shows you how to combine Langchain, Airbyte, and Dagster to build maintainable and scalable pipelines for training LLMs.

Revisiting the Poor Man’s Data Lake with MotherDuck

June 22, 2023

Revisiting the Poor Man’s Data Lake with MotherDuck

See how much easier you can collaborate using DuckDB’s high-powered cloud version MotherDuck to build a one-system data lake.

Pete Hunt

Backfills in Data & Machine Learning: A Primer

June 6, 2023

Backfills in Data & Machine Learning: A Primer

A step-by-step guide to using backfills and partitions to make data management more simple for data & ML engineers.

Sandy Ryza

Dagster and the Decade of Data Engineering

May 24, 2023

Dagster and the Decade of Data Engineering

We are pleased to announce Elementl's $33M Series B and share our vision for what's next for Dagster and the practice of data engineering.

Nick Schrock

Building Better Analytics Pipelines

May 23, 2023

Building Better Analytics Pipelines

A recap of our live event on the benefits and techniques for orchestrating analytics pipelines.

Pete Hunt

Introducing Dynamic Definitions for Flexible Asset Partitioning

May 19, 2023

Introducing Dynamic Definitions for Flexible Asset Partitioning

Dagster’s dynamic partition definitions allow engineers to use the power of partitions in a broader range of scenarios.

Claire Lin

How to Maintain High Product & Code Quality As Your Startup Scales

May 9, 2023

How to Maintain High Product & Code Quality As Your Startup Scales

Raising the quality bar requires process adjustments and a cultural shift.

Bosmat Eldar

From Python Projects to Dagster Pipelines

April 14, 2023

From Python Projects to Dagster Pipelines

In part IV of our series, we explore setting up a Dagster project, and the key concept of Data Assets.

Elliot Gunn

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