Lightweight Python ORM for hierarchical storage management https://doc.olog.io/co3
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README.md

Overview

co3 is a lightweight Python ORM for hierarchical storage management. It implements a general type system for defining database components like relations, schemas, engines, etc. Objects inheriting from the CO3 base class can then define data transformations that connect to database components, and can be automatically collected for coordinated database insertion.

co3 attempts to provide a general interface for interacting with a storage media (e.g., database, pickled objects, VSS framework, in-memory key-value stores, etc). The following top-level classes capture the bulk of the operational model:

  • Database: reference to a storage medium, with an Accessor for accessing data, Manager for managing database state, and an Engine for managing connections and external operations.
  • Accessor: provides access to stored items in a Database, typically via a supported select operation over known Component types
  • Manager: manages database storage state (e.g., supported inserts or database sync operations)
  • Mapper: associates CO3 types with Schema components, and provides automatic collection and composition operations for supported items
  • Collector: collects data from defined CO3 type transformations and prepares for Database insert operations
  • Component: atomic storage groups for databases (i.e., generalized notion of a "relation" in relational algebra).
  • Indexer: automatic caching of supported access queries to a Database
  • Schema: general schema analog for grouping related Component sets
  • Differ: facilitates set operations on results from selectable resources (e.g., automatic comparison between file data on disk and file rows in a SQL database)
  • Syncer: generalized syncing procedure for items between data resources (e.g., syncing new, modified, and deleted files from disk to a SQL database that stores file metadata).

The CO3 an abstract base class then makes it easy to integrate this model with regular Python object hierarchies that can be mapped to a storage schema.