PyPI to Neon Integration
AI-first ETL from PyPI into Neon. Governed entities, incremental sync, typed landing tables.
How Datrise loads PyPI into Neon
Datrise syncs PyPI's packages, releases, versions, download counts, maintainers, and dependencies into Neon as a typed table per source entity. Flexible or custom fields land in jsonb columns, and timestamps such as created, updated, and status changes are typed as timestamptz.
Sync is incremental: Datrise uses a watermark on updated-at, applied with INSERT … ON CONFLICT DO UPDATE, so re-runs update only what changed. Optional declarative partitioning by load date. Neon separates compute from storage, so Datrise batches writes to keep autoscaling compute from cold-starting on every small change.
Ideal for serverless Postgres workloads that scale to zero between syncs.
Endpoints
PyPI: Python package registry metadata and downloads.
Neon: Serverless Postgres destination with branching and autoscaling.
How PyPI entities map to Neon
| PyPI entity | Neon object | Notes |
|---|---|---|
| packages | pypi_packages | id PK · custom fields → jsonb columns |
| releases | pypi_releases | id PK · linked to pypi_packages |
| versions | pypi_versions | id PK · linked to pypi_packages |
| download counts | pypi_download_counts | id PK · linked to pypi_packages |
FAQ
How does Datrise handle PyPI's custom fields in Neon?
Flexible values are stored as jsonb columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Neon types.
How does the PyPI to Neon sync stay up to date?
It runs incrementally — Datrise uses a watermark on updated-at, applied with INSERT … ON CONFLICT DO UPDATE.
Related pipelines
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Early access
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