template

DE//AGENT currently lists 9 resources under template: 7 templates, 2 tutorials. Everything below is derived from the live registry — counts, capabilities, verification state and security posture come from the curated records, never from marketing copy.

Documented learning objectives across these resources:

• Scaffold a DAG project with tests and a Dockerfile from the template — via Scaffold an idempotent DAG from the template
• Write tasks that are safe to re-run from day one — via Scaffold an idempotent DAG from the template
• Set catchup, retries and sensor modes as deliberate choices — via Scaffold an idempotent DAG from the template
• Scaffold a PySpark project with the template — via Start a PySpark project from the template
• Arrange transforms and offline test fixtures — via Start a PySpark project from the template
• Add pre/post row-count and null assertions to a job — via Start a PySpark project from the template

These resources map to stages: Orchestration (2), Data Processing (2), Warehousing (1), Cloud (2), Data Quality (1), Streaming (1). Follow the four-phase roadmap to place this topic inside a progression instead of learning it in isolation.

Every entry, its shape and its trust state — sorted by the registry's composite score. This table is the honest version of a marketing comparison: no sponsored placements, no unverifiable claims.

How scores are computed: source quality score.

Highest composite score first:

1. Scaffold an idempotent DAG from the template score 34.15 — beginner
2. Start a PySpark project from the template score 34.15 — beginner
3. Local Docker Data Stack score 34.1 — beginner

Scores rank provenance, completeness and trust — read how verification works before adopting anything.

Start here if you're new: Scaffold an idempotent DAG from the template, Start a PySpark project from the template, Local Docker Data Stack, dbt Project Template.

Reach for these with production experience: Kafka Streaming Job Template, Terraform AWS Data Platform.

Security-flagged entries: Local Docker Data Stack (2 flags), PySpark Project Template (2 flags), Data Contract Template (2 flags), dbt Project Template (4 flags), Airflow DAG Template (4 flags), Kafka Streaming Job Template (4 flags), Terraform AWS Data Platform (5 flags). Flags mean the record declares capabilities like credential use or write access — read the security posture on each page before connecting.

• Scaffold an idempotent DAG from the template — Generate a new pipeline from the Airflow DAG template and keep its guarantees — an idempotent skeleton with task groups, retries and backoff, SLA, pools, and a reschedule-mode sens… details
• Start a PySpark project from the template — Scaffold a testable PySpark project with one command and learn where each piece lives: transforms in src/, 3-10 row fixtures in tests/data/, and a Makefile that runs lint plus test… details
• Local Docker Data Stack — A docker-compose stack (Postgres, Kafka, MinIO, Spark, and a DuckDB CLI) for developing and testing pipelines entirely offline. details
• PySpark Project Template — A testable PySpark project: src/transforms, tests with a local Spark session, a Dockerfile, and a Makefile that runs lint + tests offline. details

Real install commands from the registry — read the source before running any of them:

amp template new de-agent/docker-local-stack ./local

Local Docker Data Stack — review first

amp template new de-agent/pyspark-project ./my-pipeline

PySpark Project Template — review first

amp template new de-agent/data-contract-template ./contracts

Data Contract Template — review first

amp template new de-agent/dbt-project ./my-dbt

dbt Project Template — review first

Adjacent topics: Apache Spark (3 shared), testing (3 shared), Apache Kafka (2 shared), dbt (2 shared), Docker (2 shared), tutorial (2 shared).

Study path: the roadmap places this topic in a progression · the scoring model explains the numbers · the trust rule catalog shows every security check these entries passed through.