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Stride Documentation
Stride Documentation

Contents:

  • Core Concepts
    • Data Download
    • Global Dataset Data Sources
    • Data Validation with dsgrid
    • Customizing Dataset Checks
    • dbt Computation
    • Weather Year Modeling
    • Time Conventions
  • How Tos
    • Getting Started
    • Download Datasets
    • Override Calculated Tables
    • Launch the Dashboard
    • Customize the Color Palette
    • Compare Scenarios
    • Export Results
    • Query a Project’s Database Directly
  • Tutorials
    • Create a project
    • Browse the dbt project
    • Manage calculated tables
    • Process results with Python
    • Debug stride source code
  • Reference
    • Data API
    • stride Project API
    • CLI reference
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Core Concepts¶

These pages explain the data and computations behind a STRIDE projection. They follow the rough flow of a project: input datasets are sourced, downloaded, and validated, then transformed by dbt into hourly load forecasts that reflect historical weather.

Input Data¶

  • Data Download
  • Global Dataset Data Sources
  • Data Validation with dsgrid
  • Customizing Dataset Checks

Computation¶

  • dbt Computation
  • Weather Year Modeling
  • Time Conventions
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  • Core Concepts
    • Input Data
    • Computation