Welcome to the documentation for the Python SDK for the Data Layer by Syntropy! This SDK allows seamless integration with our Data Layer solution, enabling you to leverage real-time data streams in your Python applications. With the Python SDK, you can unlock the power of the Data Layer and harness real-time insights for your data-driven projects.
pubsub-python is a Python example illustrating the use of the Syntropy Data Layer project, which facilitates subscription to existing data streams or publishing new ones. This example employs the NATS messaging system and offers a simpler starting point for integrating Python applications with the Syntropy Data Layer platform.
To install the Python SDK for Data Layer, you can use pip, the Python package manager. Here's an example of how to install it:
pip install syntropynet-pubsubBefore you begin using the Python SDK, make sure you have the necessary credentials and access tokens from the Syntropy Developer Portal platform. These credentials will allow you to connect to the Data Layer and subscribe to or publish data streams.
For detailed usage examples, please refer to the examples directory in the repository. These examples cover various scenarios and demonstrate how to utilize the SDK's features effectively.
The preferred authentication method is using an access token from the developer portal.
import asyncio
import nats
import tempfile
import os
from helper import create_app_jwt
access_token = "EXAMPLE_ACCESS_TOKEN"
async def main():
jwt = create_app_jwt(access_token)
# Write the JWT to a temporary file with correct format
with tempfile.NamedTemporaryFile(mode='w+t', delete=False) as temp:
temp.write(jwt)
temp_path = temp.name
nc = await nats.connect("nats://127.0.0.1", user_credentials=temp_path)
async def message_handler(msg):
subject = msg.subject
data = msg.data.decode()
print("Received a message on '{subject}: {data}".format(
subject=subject, data=data))
# await nc.publish("syntropy.test.subject", msg.data)
await nc.subscribe("syntropy.bitcoin.tx", cb=message_handler)
# run infinitely
while True:
await asyncio.sleep(1)
# Terminate connection to NATS.
await nc.drain()
# Delete the temporary file
os.unlink(temp_path)
if __name__ == '__main__':
asyncio.run(main())
We welcome contributions from the community! If you find any issues or have suggestions for improvements, please open an issue or submit a pull request on the GitHub repository. We appreciate your feedback and collaboration in making this SDK even better.
To contribute to this project, please follow the guidelines outlined in the Contribution.md file. It covers important information about how to submit bug reports, suggest new features, and submit pull requests.
This project adheres to a Code of Conduct to ensure a welcoming and inclusive environment for all contributors. Please review the guidelines and make sure to follow them in all interactions within the project.
When making changes to the codebase, it's important to follow a consistent commit message format. Please refer to the Commit Message Format for details on how to structure your commit messages.
To streamline the pull request process, we have provided a Pull Request Template that includes the necessary sections for describing your changes, related issues, proposed changes, and any additional information. Make sure to fill out the template when submitting a pull request.
We appreciate your contributions and thank you for your support in making this project better!
If you encounter any difficulties or have questions regarding the Python SDK for Data Layer, please reach out to our support team at Discord #developer-discussion. We are here to assist you and ensure a smooth experience with our SDK.
We hope this documentation provides you with a comprehensive understanding of the Python SDK for the Data Layer. Enjoy leveraging real-time data streams and unlocking the power of the Data Layer in your Python applications!