dlt-dagster
OfficialRun dlt pipelines in Dagster with components.
Authoruntitled-data-company
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This skill simplifies running dlt pipelines inside Dagster by offering a component-based (loads.py + defs.yaml) or Pythonic (@dlt_assets) approach, enabling scalable orchestration of data pipelines.
Core Features & Use Cases
- Component workflow: generate Dagster assets via loads.py and defs.yaml with a dlt load collection.
- Pythonic workflow: implement @dlt_assets with DagsterDltResource for code-centric definitions.
- Supports incremental loading, backfills, parallelization, and optional cloud deployment (Dagster Cloud) for production-grade pipelines.
- Suitable for running dlt pipelines on Dagster compute or external compute (ECS, Fargate), with templates and references for setup.
Quick Start
Use this skill to run an existing dlt pipeline inside Dagster by selecting the preferred approach (component or Pythonic) and materializing assets in Dagster Cloud or on your Dagster deployment.
Dependency Matrix
Required Modules
None requiredComponents
assetsreferences
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: dlt-dagster Download link: https://github.com/untitled-data-company/data-skills/archive/main.zip#dlt-dagster Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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