Implementation:Mage ai Mage ai Package Setup

Knowledge Sources	Mage AI Mage AI Docs
Domains	Package_Management, Configuration
Last Updated	2026-02-09 00:00 GMT

Overview

Python package setup configuration for the mage-ai PyPI distribution defining dependencies, entry points, and metadata.

Description

The setup.py file configures the mage-ai Python package (version 0.9.79) for distribution via PyPI using setuptools. It reads the project README from README.md for the long description and parses core dependencies from requirements.txt (stopping at lines prefixed with # extras). The package is published under the name mage-ai with author "Mage" (eng@mage.ai), licensed under the Apache Software License, and requires Python >= 3.9. It registers a single CLI entry point, mage, which maps to mage_ai.cli.main:app. The file defines 16 extras_require groups for optional integrations: ai (OpenAI, LangChain), airtable, azure (Event Hub, Key Vault, Storage), bigquery, chroma, clickhouse, dbt (with adapters for BigQuery, ClickHouse, DuckDB, Postgres, Redshift, Snowflake, Spark, SQL Server, Synapse, Trino), google-cloud-storage, hdf5, mysql, oracle, postgres, qdrant, redshift, s3, snowflake, spark, streaming (Kafka, Elasticsearch, RabbitMQ, MongoDB, NATS, OpenSearch, InfluxDB, ActiveMQ via stomp.py), and a comprehensive all group that bundles the full set of optional dependencies including Kubernetes, Prometheus, OpenTelemetry, Great Expectations, and more.

Usage

This file is consumed by pip and setuptools when installing mage-ai. It defines the mage CLI entry point and all required and optional dependency groups. The version must be kept in sync with mage_ai/server/constants.py as noted in the inline comment.

Code Reference

Source Location

• Repository: mage-ai
• File: setup.py
• Lines: 1-214

Signature

setuptools.setup(
    name='mage-ai',
    version='0.9.79',
    author='Mage',
    author_email='eng@mage.ai',
    description='Mage is a tool for building and deploying data pipelines.',
    long_description=readme(),
    long_description_content_type='text/markdown',
    url='https://github.com/mage-ai/mage-ai',
    packages=setuptools.find_packages('.'),
    include_package_data=True,
    classifiers=[...],
    install_requires=requirements,
    python_requires='>=3.9',
    entry_points={
        'console_scripts': [
            'mage=mage_ai.cli.main:app',
        ],
    },
    extras_require={
        'ai': [...],
        'airtable': [...],
        'azure': [...],
        'bigquery': [...],
        'chroma': [...],
        'clickhouse': [...],
        'dbt': [...],
        'google-cloud-storage': [...],
        'hdf5': [...],
        'mysql': [...],
        'oracle': [...],
        'postgres': [...],
        'qdrant': [...],
        'redshift': [...],
        's3': [...],
        'snowflake': [...],
        'spark': [...],
        'streaming': [...],
        'all': [...],
    },
)

Import

# Not imported directly - used by pip install
# pip install mage-ai
# pip install mage-ai[all]

I/O Contract

Inputs

Name	Type	Required	Description
README.md	file	Yes	Provides the long description for PyPI
requirements.txt	file	Yes	Core dependencies parsed until # extras marker

Outputs

Name	Type	Description
mage-ai package	installed package	The mage-ai package with all modules and the mage CLI entry point
mage CLI	console script	CLI entry point mapped to mage_ai.cli.main:app

Extras Require Groups

Group	Key Dependencies	Description
ai	openai, langchain, astor	AI/LLM integration support
airtable	pyairtable	Airtable data source connector
azure	azure-eventhub, azure-identity, azure-keyvault-secrets, azure-storage-blob	Azure cloud services integration
bigquery	google-cloud-bigquery, db-dtypes	Google BigQuery data warehouse support
chroma	chromadb	Chroma vector database integration
clickhouse	clickhouse-connect	ClickHouse database connector
dbt	dbt-core and 11 adapters (BigQuery, ClickHouse, DuckDB, Postgres, Redshift, Snowflake, Spark, SQL Server, Synapse, Trino)	dbt transformation framework support
google-cloud-storage	google-cloud-storage, gspread	GCS and Google Sheets integration
hdf5	tables (version varies by Python version)	HDF5 file format support
mysql	mysql-connector-python	MySQL database connector
oracle	oracledb	Oracle database connector
postgres	psycopg2, psycopg2-binary, sshtunnel	PostgreSQL database connector with SSH tunnel support
qdrant	qdrant-client, sentence-transformers	Qdrant vector database integration
redshift	boto3, redshift-connector, lxml	Amazon Redshift data warehouse connector
s3	boto3, botocore	Amazon S3 object storage integration
snowflake	snowflake-connector-python	Snowflake data warehouse connector
spark	boto3, botocore	Apache Spark integration support
streaming	kafka-python, elasticsearch, mongodb, nats-py, opensearch-py, pika, influxdb_client, stomp.py	Real-time streaming source/destination connectors
all	(comprehensive bundle)	All optional dependencies combined including Kubernetes, Prometheus, OpenTelemetry, Great Expectations, and more

Usage Examples

# Install mage-ai with core dependencies only
pip install mage-ai

# Install with all optional extras
pip install mage-ai[all]

# Install with specific extras
pip install mage-ai[postgres,s3]
pip install mage-ai[dbt]
pip install mage-ai[streaming]

# Run the mage CLI after installation
mage start my_project
mage init my_new_project

Related Pages

Implements Principle

• Principle:Mage_ai_Mage_ai_Source_Configuration

Requires Environment

• Environment:Mage_ai_Mage_ai_Python_3_9_Runtime