Sam G. b726f495b6 | ||
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_deprecated | ||
co3 | ||
docs | ||
tests | ||
.gitignore | ||
LICENSE | ||
MANIFEST.in | ||
README.md | ||
pyproject.toml |
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 storage media (e.g.,
databases, 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 anEngine
for managing connections and external operations. - Accessor: provides access to stored items in a
Database
, typically via a supportedselect
operation over knownComponent
types - Manager: manages database storage state (e.g., supported inserts or database sync operations)
- Mapper: associates
CO3
types withSchema
components, and provides automatic collection and composition operations for supported items - Collector: collects data from defined
CO3
type transformations and prepares forDatabase
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.