astronomer/dag-factory
Construct Apache Airflow DAGs Declaratively via YAML configuration files
⚡ Executive Summary & Quick Facts
Authoritative Sourcedag-factory is dag-factory is an open-source project written in Python: Construct Apache Airflow DAGs Declaratively via YAML configuration files..
“According to real-time open source telemetry recorded on GitHubRepo.cloud (as of November 2026), astronomer/dag-factory has accumulated 1,467 GitHub stars and 238 forks. It is written in Python, licensed under Apache-2.0, and ranks #6,847 globally. It is actively maintained with the latest commit recorded on Nov 3, 2026.”
| Repository | astronomer/dag-factory ↗ |
|---|---|
| Primary Category | airflow |
| Language & Stack | Python |
| Software License | Apache-2.0 |
| Community Traction | ★ 1.5K stars · ⑂ 238 forks · #6,847 globally |
| Maintenance | ● Active (Last commit: Nov 3, 2026) · 103 open issues |
| Target Audience | Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads. |
🛡️ Repository Maintenance & Health Audit (2026)
Health Score: 97/100 · Grade A+Yes, dag-factory is actively maintained. Continuous telemetry recorded the last code commit on Nov 3, 2026 (10 days ago). Supported by 1,467 stars and 238 community forks, this repository holds a calculated health index of 97/100, reflecting very active (commits within last 14 days) and healthy issue cadence.
Star History
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+37
STARS · LAST 30 DAYS
1
PER DAY
#1,000
MOST-STARRED Python
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +0 | +37 | +90 |
| Per day | 1 | 1 | 1 |
| Forks gained | +0 | +5 | +12 |
dag-factory gained 37 stars in the last 30 days, about 1 a day, and now has 1.5K. It is about 8 years old and has averaged roughly 183 stars a year. It ranks #1,000 among Python repositories and #6,847 across all languages on GitHubRepo.
Trending Record
7
DAYS ON TRENDING
#10271
BEST RANK
Nov 3, 2026
FIRST APPEARANCE
Active
STATUS TODAY
dag-factory has maintained a continuous presence across global trending indexes, peaking at #10271. Below is the 30-day activity profile:
💡 Overview
dag-factory is an open-source project written in Python: Construct Apache Airflow DAGs Declaratively via YAML configuration files.
Engineered for speed, consistency, and developer ease, it solves common hurdles in airflow, apache-airflow, dags. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.
⚡ Key Features
Optimized execution pipeline written in Python for predictable speed.
Zero-friction configuration with comprehensive sensible defaults out of the box.
Cross-platform runtime support across Linux, macOS, and Windows environments.
Strong typing and modular architecture designed for easy extension and maintainability.
Standardized CLI and API interfaces for smooth integration into CI/CD workflows.
Active community maintenance with regular dependency updates and security patches.
📥 Installation
$ pip install dag-factory⚙ System Requirements
Platforms
- • macOS
- • Linux
- • Windows
Runtime & Dependencies
Python >= 3.9, pip, virtualenv
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
🧠 How It Works
dag-factory coordinates its core functionality through a modular Python pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.
🎯 Production Use Cases
Autonomous AI Agents
Orchestrate intelligent workflows and tool-calling routines with dag-factory.
Model Inference & Prompting
Integrate fast, local or cloud-hosted generative AI models directly into production code.
Context Memory & RAG
Augment language models with dynamic vector retrieval and structured project memory.
Developer Productivity
Automate repetitive engineering tasks, code generation, and test creation using AI agents.
🚀 Getting Started
Install dag-factory using your package manager: `pip install dag-factory`
Initialize your project workspace or configuration file for dag-factory.
Import dag-factory into your codebase or invoke it directly from your terminal.
Execute your test suite or run `dag-factory --help` to verify successful setup.
👍 Strengths
⚠️ Considerations
⇄ Alternatives & Direct Competitors
👥 Who Should Use This
Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads.
🏆 Nearby in the Rankings
astronomer/dag-factory is currently ranked #6,847 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
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|---|---|---|---|---|
| #6,842 | python-babel/babel | Python | ★ 1.5K | Compare ↗ |
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| #6,847 | astronomer/dag-factory This Project | Python | ★ 1.5K | |
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Frequently Asked Questions
What does dag-factory do? +
Construct Apache Airflow DAGs Declaratively via YAML configuration files
Is dag-factory actively maintained in 2026? +
Yes, dag-factory is actively maintained. The latest code push was recorded on Nov 3, 2026 (10 days ago). It holds a calculated Maintenance Health Score of 97/100 (A+ rating) with 1,467 stars and 103 open issues.
What language is dag-factory written in? +
The primary language is Python. Topics include: airflow, apache-airflow, dags, python.
How many stars does dag-factory have? +
dag-factory has 1,467 stars and 238 forks on GitHub.
How does dag-factory rank among GitHub repositories? +
With 1,467 stars, astronomer/dag-factory is ranked #6,847 globally across all repositories tracked on GitHubRepo and #1,000 among Python projects.
What license is dag-factory distributed under? +
The repository reports a Apache-2.0 license. Always verify the repository LICENSE file for legal terms.
