apilinker 0.7.1

A universal bridge to connect, map, and automate data transfer between any two REST APIs

ApiLinker

A universal bridge to connect, map, and automate data transfer between any two REST APIs.

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📚 Documentation

Full documentation is available at https://kkartas.github.io/APILinker/.

🚀 Quick Install

pip install apilinker

⭐ Message Queue Connectors

Message-queue connectors are optional.

pip install apilinker[mq]

Minimal example (worker loop):

from apilinker.core.error_handling import DeadLetterQueue
from apilinker.core.message_queue import MessagePipeline, MessageWorker
from apilinker.core.message_queue_connectors import RabbitMQConnectorPlugin

consumer = RabbitMQConnectorPlugin()
producer = RabbitMQConnectorPlugin()

consumer_conn = consumer.connect(host="localhost")
producer_conn = producer.connect(host="localhost")

pipeline = MessagePipeline(
    consumer=consumer,
    producer=producer,
    dlq=DeadLetterQueue("./dlq"),
)

worker = MessageWorker(
    pipeline,
    consumer_connection=consumer_conn,
    producer_connection=producer_conn,
    source="input_queue",
    default_destination="output_queue",
)

worker.run()

🌟 Features

• 🔄 Universal Connectivity - Connect any two REST APIs.
• 🗺️ Powerful Mapping - Transform data with ease.
• 🔗 Multi-Source Aggregation (v0.7.1) - Join data from multiple APIs (inner/left/right/outer joins) via the Python API.
• 📥 Large Download Streaming (v0.7.1) - Stream HTTP responses to disk with resume and progress callbacks.
• ⭐ Event-Driven Pipelines - Optional message queue connectors (RabbitMQ, Redis Pub/Sub, AWS SQS, Kafka).
• SSE Streaming - Built-in SSE connector with reconnection, chunked processing, and backpressure controls.
• 🔒 Secure - Enterprise secret management (Vault, AWS, Azure, GCP).
• 🧬 Scientific Connectors - Built-in support for NCBI, arXiv, and more.

Multi-source aggregation (v0.7.1)

from apilinker import ApiLinker

linker = ApiLinker()
linker.register_source("crm", crm_connector)
linker.register_source("billing", billing_connector)

rows = linker.aggregate_sources(
    source_requests={
        "crm": {"connector": "crm", "endpoint": "list_users"},
        "billing": {"connector": "billing", "endpoint": "list_plans"},
    },
    aggregation_config={
        "join_type": "inner",
        "merge_strategy": "flat",
        "sources": [
            {"name": "crm", "join_key": "id", "fields": [...]},
            {"name": "billing", "join_key": "customer_id", "fields": [...]},
        ],
    },
)

See Multi-Source Aggregation and examples/multi_source_aggregation.py.

🤝 Contributing

We welcome contributions! Please see our Contributing Guide for details.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.