zephflow 0.2.2rc9

Python SDK for ZephFlow data processing pipelines

ZephFlow Python SDK

Python SDK for building and running ZephFlow data processing pipelines. ZephFlow provides a powerful, intuitive API for stream processing, data transformation, and event-driven architectures.

Features

• Simple, fluent API for building data processing pipelines
• Powerful filtering using JSONPath expressions
• Data transformation with the eval expression language
• Flow composition - merge and combine multiple flows
• Error handling with assertions and error tracking
• Multiple sink options for outputting processed data
• Java-based engine for high performance processing

Documentation

For comprehensive documentation, tutorials, and API reference, visit: https://docs.fleak.ai/zephflow

Prerequisites

• Python 3.8 or higher
• Java 21 or higher (required for the processing engine)

Installation

Install ZephFlow using pip:

pip install zephflow

Quick Start

Here's a simple example to get you started with ZephFlow:

import zephflow

# Create a flow that filters and transforms events
flow = (
    zephflow.ZephFlow.start_flow()
    .filter("$.value > 10")  # Keep only events with value > 10
    .eval("""
        dict(
            id=$.id,
            doubled_value=$.value * 2,
            category=case(
                $.value < 20 => 'medium',
                _ => 'high'
            )
        )
    """)
    .stdout_sink("JSON_OBJECT")  # Output to console
)

# Process some events
events = [
    {"id": 1, "value": 5},   # Will be filtered out
    {"id": 2, "value": 15},  # Will be processed
    {"id": 3, "value": 25}   # Will be processed
]

result = flow.process(events)
print(f"Processed {result.getOutputEvents().size()} events")

Core Concepts

Filtering

Use JSONPath expressions to filter events:

flow = (
    zephflow.ZephFlow.start_flow()
    .filter("$.priority == 'high' && $.value >= 100")
)

Transformation

Transform data using the eval expression language:

flow = (
    zephflow.ZephFlow.start_flow()
    .eval("""
        dict(
            timestamp=now(),
            original_id=$.id,
            processed_value=$.value * 1.1,
            status='processed'
        )
    """)
)

Merging Flows

Combine multiple flows for complex processing logic:

high_priority = zephflow.ZephFlow.start_flow().filter("$.priority == 'high'")
large_value = zephflow.ZephFlow.start_flow().filter("$.value >= 1000")

merged = zephflow.ZephFlow.merge(high_priority, large_value)

Error Handling

Add assertions to validate data and handle errors:

flow = (
  zephflow.ZephFlow.start_flow()
  .assertion("$.required_field != null")
  .assertion("$.value >= 0")
  .eval("dict(id=$.id, validated_value=$.value)")
)

result = flow.process(events, include_error_by_step=True)
if result.getErrorByStep().size() > 0:
  print("Some events failed validation")

Examples

For more detailed examples, check out Quick Start Example - Basic filtering and transformation

Environment Variables

• ZEPHFLOW_MAIN_JAR - Path to a custom ZephFlow JAR file (optional)
• ZEPHFLOW_JAR_DIR - Directory for storing downloaded JAR files (optional)

Support

• Documentation: https://docs.fleak.ai/zephflow
• Discussions: Slack

License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

About Fleak

ZephFlow is developed and maintained by Fleak Tech Inc., building the future of data processing and streaming analytics.