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msiemens / tinydb

TinyDB is a lightweight document oriented database optimized for your happiness :)

Python★ 7,571
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github.com/msiemens/tinydb·Indexed at 18d73a1·18d ago·Up to date with upstream

About this codebase

Tinydb is a lightweight document database engine: it consumes a user-provided dataset (and optional persistence configuration), builds internal indexable representations through its query/operation pipeline, and outputs query results plus persisted table state back through its storage/write-back interfaces. In practice, you create a TinyDB instance, define one or more `Table`s, run `Query` operations (e.g., `all`, `any`, `one_of`) against the table’s indexed documents, and optionally persist changes via the table’s write-back workflow.

Written by gpt-5.4-nano from the index

33 files and 361 symbols in 3 modules, led by Python (21 files) and Makefile (1).

Start reading

  • Knowledge graph33 files and how they depend on each other.→
  • Remove Query constructor parameter; use Query().field styleDecisionProposed decision, from a pull request.→

Code health

7.4out of 10Good

This codebase scores 7.4 out of 10 for code health, which we rate good. It also scores maintainability 9.2 and static performance 10.0 out of 10. The three are scored separately and never blended into one number. Risk is concentrated, as it usually is: 2 of 33 files are git hotspots, and they average 5.6 — which is where the fixes pay off most.

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Nothing stands out in the week to Sep 18, the last indexed commit.

Repowise ran 5 checks over this index and none of them produced work for this time frame.

No accepted decisions to drift. Too few files for coverage to change the list.

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How msiemens/tinydb works

TinyDB is a lightweight document oriented database optimized for your happiness :) This page is a map of the msiemens/tinydb repository, written primarily in Python, rebuilt from the source each time it is indexed. Repowise parses every symbol, computes a dependency graph, scores per-file code health from complexity, duplication, test coverage and churn, mines git history for hotspots and ownership, and lifts the architectural decisions into documentation you can read here or query through MCP.

The codebase has 33 files and 361 symbols in 3 modules, led by Python and Makefile. Code health is 7.4 out of 10, rated good.

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