--- id: partd version: "1.4.2" license: BSD license_treatment: permissive maintenance: dormant --- # partd — Appendable key-value storage License: permissive · Maintenance: dormant · Popularity: top 1,000 on PyPI ## Install pip install partd uv add partd poetry add partd ## Description PartD ===== |Build Status| |Version Status| Key-value byte store with appendable values Partd stores key-value pairs. Values are raw bytes. We append on old values. Partd excels at shuffling operations. Operations ---------- PartD has two main operations, ``append`` and ``get``. Example ------- 1. Create a Partd backed by a directory:: >>> import partd >>> p = partd.File('/path/to/new/dataset/') 2. Append key-byte pairs to dataset:: >>> p.append({'x': b'Hello ', 'y': b'123'}) >>> p.append({'x': b'world!', 'y': b'456'}) 3. Get bytes associated to keys:: >>> p.get('x') # One key b'Hello world!' >>> p.get(['y', 'x']) # List of keys [b'123456', b'Hello world!'] 4. Destroy partd dataset:: >>> p.drop() That's it. Implementations --------------- We can back a partd by an in-memory dictionary:: >>> p = Dict() For larger amounts of data or to share data between processes we back a partd by a directory of files. This uses file-based locks for consistency.:: >>> p = File('/path/to/dataset/') However this can fail for many small writes. In these cases you may... ## AI interpretation — verify before relying Partd is a key-value byte store that appends values to keys and supports multiple storage backends (in-memory, file-based, buffered, or remote server). It excels at shuffling operations and can be composed with compression and encoding layers for transparent serialization. Verdict: Partd is a lightweight, permissively licensed tool for append-only key-value storage with flexible backends and composition options. Its low install friction and lack of known vulnerabilities make it technically sound, but the dormant maintenance status (no activity in 829 days) means it is unlikely to receive updates for new Python versions or emerging issues. Suitable for stable, self-contained use cases but risky for projects requiring ongoing support. [View on SkillFed](https://skillfed.io/packages/partd) · [View on PyPI](https://pypi.org/project/partd/)