Usage Guide

Usage Guide#

Installation#

pip install -e .

CLI Usage#

python -m wxdi.data_product_recommender.cli \
  --platform snowflake \
  --input-file query_logs.csv \
  --output output \
  --num-recommendations 20 \
  --min-score 60.0

Options#

  • --platform - Database platform (snowflake, databricks, bigquery, watsonxdata)

  • --input-file - Path to CSV or JSON query log file

  • --output - Output directory (default: output)

  • --output-format - Output format: markdown or json (default: markdown)

  • --num-recommendations - Number of recommendations (default: 20)

  • --min-score - Minimum score threshold 0-100

Python API#

from wxdi.data_product_recommender.platforms import SnowflakeQueryParser
from wxdi.data_product_recommender.recommender import DataProductRecommender

# Initialize
parser = SnowflakeQueryParser()
recommender = DataProductRecommender(parser)

# Load query logs
recommender.load_query_logs_from_csv_file('query_logs.csv')

# Calculate metrics
recommender.calculate_metrics()

# Get recommendations
recommendations = recommender.recommend_data_products(
    num_recommendations=20,
    min_score=60.0
)

# Export results
recommender.export_recommendations_markdown(recommendations, 'output/recommendations.md')
recommender.export_recommendations_json(recommendations, 'output/recommendations.json')

See Also#