automation

Airflow: Seamless workflow automation for data teams

Design, schedule, and monitor complex data pipelines with Apache Airflow—ideal for founders building data‑driven products. 47k+ GitHub stars.

From the repo · “Apache Airflow - A platform to programmatically author, schedule, and monitor workflows”

intermediate⏱ 30 minutes💵 Free (self-hosted)
47,255 stars+68★ this week18,117 forksPythonGuide quality 9/10 · reviewed Sep 29Install verified Sep 21Updated 10/22/2026100% free · open source
What it is

Airflow: Automate Workflows lets you create a schedule for tasks and jobs with code.

Real use case example

"A solo developer uses Airflow to automate a daily report on website traffic. She sets up a DAG, creates a schedule for the task to run every morning, and configures a connection to Google Analytics. Once done, the report will be sent to her email every morning at 8 am."

When to use it
  • •When you need to manage complex data workflows across multiple systems and teams
  • •To automate and schedule recurring data tasks, such as data ingestion and processing
  • •For building and managing machine learning pipelines that require data preparation, training, and deployment
Ready-to-paste prompt
Run a sample DAG with `airflow trigger_dag example_bash_operator` to see how Airflow can execute a series of bash commands
Heads up: Airflow requires a database backend to store its metadata, so you need to configure a database connection, such as PostgreSQL or MySQL, before running the `airflow db init` command
Saves to your device
Use with Claude
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✅ Light setup✓ Install verified 9/21/2026

Installs with a command or two; your AI agent can do it for you.

Try it instantly — no install
Claude Code
mkdir -p ~/.claude/skills/airflow && curl -fsSL https://workflowstacks.com/api/skills/airflow/claude-skill -o ~/.claude/skills/airflow/SKILL.md
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Connect the whole catalog (MCP)
claude mcp add --transport http workflowstacks https://workflowstacks.com/api/mcp

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How Airflow: Seamless workflow automation for data teams works
Codeflow
Free to inspect

Airflow: Seamless workflow automation for data teams is a very large Python project (~945k lines across 5104 code files, plus 4034 test files). Setup is light: installs like a normal app. Reading the code is optional. Last commit this month, Apache-2.0 license, has a test suite.

Size
Very large codebase
~945k lines · 5104 code files · days to read — use, don't read
Setup
One-command install
Installs like a normal app. Reading the code is optional.
Runs on
Python · Docker
No API keys detected
Python 90%TypeScript 8%Go 1%JavaScript 1%
Where to start reading
  1. 1
    README.md
    Start here — what it does and how to install it
  2. 2
    AGENTS.md
    The instructions the AI actually follows
  3. 3
    pyproject.toml
    Dependencies and the commands it exposes
What's in each folder
providers/Sub-packages / plugins7870 files
docs/Documentation16 files
airflow-core/Folder3062 files
dev/Folder625 files
scripts/Helper scripts423 files
task-sdk/Folder296 files
chart/Folder269 files
devel-common/Folder153 files
READMEHas testsDocumentedCI checksDocker readyApache-2.0 licenseUpdated this month
Quick Actions
Details
Creator
apache
Language
Python
Category
automation
Published
4/13/2015

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