quixplus 1.0.0

Quixplus is a Python library for building sources and sinksfor Quix Streams.

Quixplus

This project contains custom data sources for streaming data to QuixStreams using:

• WebSocket: Streams data from WebSocket endpoints.
• CSV: Streams data from CSV files.
• HTTP: Polls data from HTTP APIs at scheduled intervals.

Each source is designed to integrate with QuixStreams for real-time data streaming in Python applications.

Table of Contents

• Quixplus
  • Table of Contents
  • Getting Started
  • Environment Setup
  • Data Sources
    • WebSocket Source
    • CSV Source
    • HTTP Source
  • Usage
    • WebSocket Source Example
    • CSV Source Example
    • HTTP Source Example
  • Contributing
  • License

Getting Started

This project requires:

• Python 3.8 or higher
• QuixStreams library
• Access to your data sources (WebSocket endpoints, HTTP APIs, or CSV files)

Environment Setup

Clone this repository:

git clone https://github.com/your-username/your-repo.git
cd your-repo

Install the dependencies:

pip install -r requirements.txt

Set up your environment variables:

To use the application factory method, you need to set up your environment variables.

export BOOTSTRAP_SERVERS=<your-bootstrap-servers>
export SASL_USERNAME=<your-username>
export SASL_PASSWORD=<your-password>
export SASL_MECHANISM=<your-sasl-mechanism>
export SECURITY_PROTOCOL=<your-security-protocol>

Data Sources

WebSocket Source

The WebSocketSource class connects to a WebSocket endpoint, receives data, applies optional transformations, and streams it to QuixStreams.

Key Features:

• Connects to WebSocket URLs.
• Validates and transforms incoming messages.
• Sends data to a specified Kafka topic.

CSV Source

The CSVSource class reads data from a CSV file, transforms each row, and streams it to QuixStreams.

Key Features:

• Reads from CSV files with configurable delimiters.
• Extracts each row as a JSON object, using column headers as keys.
• Supports configurable keys for Kafka messages and value serialization.

HTTP Source

The AIOHTTPSource class polls an HTTP API endpoint at specified intervals, validates the data, and streams it to QuixStreams.

Key Features:

• Asynchronous polling with configurable intervals.
• Flexible authentication (Bearer token, Basic, or custom headers).
• Supports configurable JSON path extraction for Kafka keys and values.

Installation:

Install from PyPI:

pip install quixplus

Add your environment variables to the .env file.

Usage

WebSocket Source Example

To use the WebSocket source, initialize it with the necessary configurations:

from quixstreams import Application
from custom_sources.websocket_source import WebSocketSource

app = Application(broker_address="your_kafka_broker")
ws_source = WebSocketSource(
    topic="your_topic",
    ws_url="wss://your_websocket_endpoint",
    auth_payload={"api_key": "your_key"},
    subscribe_payload={"action": "subscribe", "params": "A.*"}
)
sdf = app.dataframe(source=ws_source)
sdf.print()
app.run()

CSV Source Example

To use the CSV source, provide the path to your CSV file and specify the columns for Kafka keys:

from quixstreams import Application
from custom_sources.csv_source import CSVSource

app = Application(broker_address="your_kafka_broker")
csv_source = CSVSource(
    topic="your_topic",
    csv_path="path/to/your/csv/file.csv",
    key_columns=["column1", "column2"]
)
sdf = app.dataframe(source=csv_source)
sdf.print()
app.run()

HTTP Source Example

To use the HTTP source, set the URL and polling interval:

from quixstreams import Application
from custom_sources.http_source import AIOHTTPSource

app = Application(broker_address="your_kafka_broker")
http_source = AIOHTTPSource(
    url="https://your-api-endpoint",
    poll_interval=10,
    auth_type="bearer",
    auth_credentials="your_bearer_token",
    key_json_path="$.data.id",
    value_json_path="$.data"
)
sdf = app.dataframe(source=http_source)
sdf.print()
app.run()

Contributing

We welcome contributions! Please read our CONTRIBUTING.md for guidelines on contributing to this project.

License

This project is licensed under the MIT License.