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growthepie/gtp-backend

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growthepie/gtp-backend has 33 GitHub stars and 13 forks. Star changes are not measured yet. Last checked 2026-11-14 13:54 UTC. Last push 2026-11-13.

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What you can do

  • backend/src/adapters/: Source-specific connectors (adapter_stables.py, adapter_defillama.py, etc.) plus shared clients like bigquery.py.
  • backend/src/queries/: Jinja-templated SQL powering metrics (e.g., select_txcount.sql.j2) and API endpoints.
  • backend/airflow/dags/: Production DAGs grouped by feature area (metrics_*, api_*, other_*) with alerting and JSON generation pipelines.
  • backend/src/api/: JSON builders (json_gen.py, json_creation.py) and the lightweight API surface in oli/api.

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소개

The backend powering growthepie, the open analytics platform for the Ethereum ecosystem. It indexes and aggregates onchain data across Ethereum Mainnet, Layer 2s, and leading applications.

데이터

README.md

Original

Welcome to the growthepie 📏🥧 Backend!

growthepie improves transparency across the Ethereum ecosystem by curating onchain, offchain, and community-sourced signals into actionable metrics, dashboards, and research.

growthepie logo

What This Repo Does

The gtp-backend repository powers growthepie’s public dashboard and data products. It runs on Python 3.10.12 and houses:

  • Data ingestion adapters that pull metrics from RPC nodes, Dune, CoinGecko, L2Beat, DeFiLlama, BigQuery, and bespoke indexers.
  • Curation and enrichment jobs that normalize raw payloads, stitch cross-source identifiers, and enforce common schemas before persisting to PostgreSQL.
  • Analytics layers that transform curated tables into pre-aggregated highlights, trendlines, and API payloads used by the dashboard, alerts, and JSON exports.
  • Airflow orchestration for scheduling hourly/daily DAGs, data quality checks, and downstream notifications.

Repository Highlights

  • backend/src/adapters/: Source-specific connectors (adapter_stables.py, adapter_defillama.py, etc.) plus shared clients like bigquery.py.
  • backend/src/queries/: Jinja-templated SQL powering metrics (e.g., select_txcount.sql.j2) and API endpoints.
  • backend/airflow/dags/: Production DAGs grouped by feature area (metrics_*, api_*, other_*) with alerting and JSON generation pipelines.
  • backend/src/api/: JSON builders (json_gen.py, json_creation.py) and the lightweight API surface in oli/api.
  • backend/src/config.py and friends manage environment-specific wiring.

Functional Flows

  1. Ingest – Adapters fetch fresh slices of chain activity, market data, or third-party metrics.
  2. Transform – Helper modules clean, reconcile, and upsert into curated PostgreSQL tables.
  3. Analyze – SQL templates and Python processors compute KPIs for quantities like TPS, fees, security, and ecosystem health.
  4. Distribute – Airflow DAGs trigger JSON generation, API refreshes, alerts, and highlights consumed by growthepie.com and partner feeds.

Related Repositories

Explore the rest of the growthepie org for front-end, infra, and research companions.