datus-semantic-metricflow 0.2.6

MetricFlow adapter for Datus semantic layer

datus-semantic-metricflow

MetricFlow adapter for Datus semantic layer.

Installation

pip install datus-semantic-metricflow

Dependencies (datus-metricflow, pydantic) will be installed automatically.

Requirements

• Python >= 3.12

Quick Start

import asyncio
from datus_semantic_metricflow import MetricFlowAdapter, MetricFlowConfig

config = MetricFlowConfig(
    datasource="my_project",
    config_path="/path/to/metricflow/config",  # optional
)

adapter = MetricFlowAdapter(config)

async def main():
    # List metrics
    metrics = await adapter.list_metrics(limit=10)
    for metric in metrics:
        print(f"{metric.name}: {metric.description}")

    # Get dimensions for a metric
    dimensions = await adapter.get_dimensions("revenue")
    for dim in dimensions:
        print(f"{dim.name}: {dim.description}")

    # Query metrics
    result = await adapter.query_metrics(
        metrics=["revenue", "orders"],
        dimensions=["date", "region"],
        limit=100,
    )
    print(f"Columns: {result.columns}")
    print(f"Data: {result.data[:5]}")

asyncio.run(main())

Configuration

Field	Type	Default	Description
datasource	str	Required	Datasource for this semantic layer instance
config_path	str	None	Path to MetricFlow configuration file
timeout	int	300	Query timeout in seconds
db_config	dict	None	Datus datasource config; Snowflake supports password or private_key / private_key_file with private_key_file_pwd plus optional role

API

• list_metrics(path=None, limit=100, offset=0) - List available metrics
• get_dimensions(metric_name, path=None) - Get dimensions for a metric
• query_metrics(metrics, dimensions=[], ...) - Execute metric queries
• validate_semantic() - Validate configuration files

Development

pip install -e ".[dev]"
pytest