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@amattas/retail-demo
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Describes the primary technologies, frameworks, libraries, and language conventions used in this codebase.

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SKILL.md

name tech-stack
description Describes the primary technologies, frameworks, libraries, and language conventions used in this codebase.

Tech Stack Overview

Language-Specific Conventions

  • Python: See PYTHON.md for detailed conventions and examples

Primary Languages

Language Usage Version
Python datagen, notebooks 3.10+
PySpark Fabric notebooks Spark 3.x
KQL Eventhouse queries N/A
JSON/YAML Fabric item definitions N/A

Frameworks & Libraries

Data Generation (datagen)

  • DuckDB: Local analytical database for historical data
  • Faker: Synthetic data generation
  • Pydantic: Data validation and event schemas
  • azure-eventhub: Event streaming to Azure

Lakehouse

  • Delta Lake: ACID transactions, schema enforcement
  • PySpark: Distributed data processing

Real-Time Analytics

  • Microsoft Fabric Eventhouse: KQL-based analytics
  • Eventstream: Event routing and transformation

Project Architecture

Event Flow:
  datagen (Python)
    → Azure Event Hubs
    → Eventstream
    → KQL Tables + Lakehouse Bronze

Data Layers:
  Bronze (raw JSON)
    → Silver (typed Delta)
    → Gold (aggregated Delta)
    → Semantic Model (Power BI)

Key Dependencies

See datagen/pyproject.toml for Python dependencies.

Core packages:

  • pydantic - Schema validation
  • duckdb - Local analytics
  • faker - Data generation
  • azure-eventhub - Event streaming