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kvgit 🔀

Git-style versioning for your data. Commits, branches, and merges -- backed by a dict-like MutableMapping.

Features Description
Dict interface MutableMapping[str, Any] -- reads and writes work like a dict
Commits Immutable, content-addressable snapshots with rollback
Branches Cheap forks with CAS-based optimistic concurrency
Tags Immutable names for commits; a tagged commit outlives every branch that reached it, in every kvgit version
Three-way merge Auto-merges non-overlapping changes; pluggable merge fns for conflicts
Pluggable backends In-memory, disk (diskcache), IndexedDB (Pyodide/browser), or bring your own KVStore
Chunked codecs Optional content-addressed dedup for large numpy arrays and pandas DataFrames -- equal buffers stored once across keys, commits, and branches

Install

pip install kvgit              # in-memory only
pip install kvgit[disk]        # adds disk backend via diskcache
pip install kvgit[scientific]  # adds chunked codecs for numpy / pandas
# IndexedDB backend is available automatically in Pyodide (browser) environments

Quick example

import kvgit

main = kvgit.store()

main["user"] = "alice"
main["score"] = 0
main.commit()

# Branch and diverge
dev = main.create_branch("dev")
dev["score"] = 999
dev.commit()

print(main["score"])  # 0   (main unchanged)
print(dev["score"])   # 999 (dev branch)

# Tag a commit by name -- immutable, and safe from garbage collection
main.tag("v1")
print(main.peek("score", tag="v1"))  # 0

Chunked codecs (numpy / pandas)

Large numpy arrays and pandas DataFrames -- and any sliced views of them -- can be stored once and shared across keys, commits, and branches:

import kvgit
import numpy as np

s = kvgit.store(codecs="scientific")

big = np.arange(1_000_000, dtype="float64")  # ~8 MB
s["full"] = big
s["head"] = big[:100_000]
s["tail"] = big[-100_000:]
s.commit()
# All three keys reference the same chunk on disk -- ~8 MB total, not ~24 MB.

Pandas DataFrames piggyback on the numpy codec via their underlying block ndarrays. See docs/quick-start.md and the API reference.

Part of the agex stack

kvgit provides versioned agent memory in agex with branching and rollback. It also works as a versioned backing store for monkeyfs virtual filesystems -- pass a Staged instance anywhere a dict is expected.

Development

uv sync --extra dev
uv run pytest

Documentation

See docs/ for detailed documentation:

  • Quick Start -- common patterns with runnable examples
  • API Reference -- full reference for all classes, methods, and types
  • Browser persistence (Pyodide) -- choosing between the IndexedDB and OPFS-mounted-disk backends, plus the syncfs flush requirement and recommended host-side patterns

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