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  • OP Labs Data Platform
  • Development Guide
  • OP Labs Data Platform
  • Development Guide

Section Navigation

  • Architecture
  • Onchain Data Processing
    • Design Principles
    • Marker Metadata Layer
    • Ingestion
    • Blockbatch Models
  • Third-Party Data Ingestion
    • Overview
    • DailyDataset (GCS)
    • ClickHouseDataset
  • Data Warehouse
    • Onchain Data Pipelines: Blockbatch Load
    • General Purpose Data Pipelines: Transforms
    • Comparison to dbt and SQLMesh
  • OP Labs Public BigQuery Data
  • OP Labs Data Platform
  • Third-Party Data Ingestion

Third-Party Data Ingestion#

At OP Labs we ingest data from many different third-party data sources. To help implement data ingestion we have developed some common patterns which we cover in this section.

  • Overview
    • DataAccess Pattern
    • Directory Structure
  • DailyDataset (GCS)
    • Historical Note
    • Subclassing the DailyDataset class
    • Discoverability
    • Writing Data
    • Root Paths
    • Other built-in functionality
    • Execution and Scheduling
    • Prototyping and Debugging
    • Monitoring
    • Advanced use cases
    • When to use ClickHouseData instead
  • ClickHouseDataset
    • Subclassing the ClickHouseDataset class.
    • CREATE TABLE
    • Writing Data
    • Execution
    • Scheduling
    • Monitoring

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