pickleshare
Tiny 'shelve'-like database with concurrency support
Decision gist · record as of 2026-08-14
Yes, if you need simple inter-process data sharing in a low-load scenario and want to avoid external database dependencies. The permissive MIT license, low install friction, and stable codebase make it a reasonable choice for development, testing, or lightweight production use. However, the dormant maintenance status (no releases since 2018) means you should verify compatibility with your Python version and filesystem before relying on it for new projects.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Installation is straightforward with low friction; the package is dormant (last release 2018-09-25, last commit 2023-11-15) but remains stable and carries only one lightweight runtime dependency (pathlib2).
License · maintenance · safety
MIT (permissive) — MIT license permits commercial and private use with minimal restrictions; you may use, modify, and distribute the package freely as long as you retain the license notice.
last release 2018-09-25 (2880 days) · last repo commit 2023-11-15 · 73 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 15,209,634 downloads/mo, #1,194 on PyPI
Alternatives
Verify before relying
pip install pickleshare
from pickleshare import PickleShareDB
db = PickleShareDB('~/testpickleshare')
db['hello'] = 15
print(db['hello'])- Whether pathlib2 is required on modern Python versions or only for Python 2 compatibility
- Current performance characteristics under concurrent load compared to alternatives
- Whether the package works reliably on Windows and other non-POSIX filesystems
What it is and what it does
PickleShare is a lightweight, file-based datastore designed for low-load scenarios where multiple processes need to share data. Unlike the standard shelve module, it stores each key-value pair in a separate file within a directory, allowing true concurrent access—changes made by one process are immediately visible to others. The API mimics a Python dictionary, making it familiar to use.
The package is intended for non-mission-critical applications where simplicity and small code size matter more than the advanced features of a full object database. It uses pickle for serialization and relies on the filesystem for concurrency control, making it suitable for scenarios like inter-process communication or simple shared state in development and testing environments.
Use it for
- Sharing configuration or state between multiple worker processes in a simple application
- Storing temporary results or caches that need to be accessible across process boundaries
- Prototyping a multi-process system before committing to a more complex database solution
- Passing data between independent scripts or services in a low-concurrency environment
- Debugging and testing scenarios where you need quick, process-safe data persistence
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need simple inter-process data sharing in a low-load scenario and want to avoid external database dependencies.
The permissive MIT license, low install friction, and stable codebase make it a reasonable choice for development, testing, or lightweight production use. However, the dormant maintenance status (no releases since 2018) means you should verify compatibility with your Python version and filesystem before relying on it for new projects.
Install
pickleshare on PyPI
Before you install
Installation is straightforward with low friction; the package is dormant (last release 2018-09-25, last commit 2023-11-15) but remains stable and carries only one lightweight runtime dependency (pathlib2).
License in practice
MIT license permits commercial and private use with minimal restrictions; you may use, modify, and distribute the package freely as long as you retain the license notice.
Quickstart
pip install pickleshare
from pickleshare import PickleShareDB
db = PickleShareDB('~/testpickleshare')
db['hello'] = 15
print(db['hello'])
Verify before relying
- Whether pathlib2 is required on modern Python versions or only for Python 2 compatibility
- Current performance characteristics under concurrent load compared to alternatives
- Whether the package works reliably on Windows and other non-POSIX filesystems
Package facts
| License | MIT permissive |
| Python support | Not specified |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagepathlib2 |
| Maintenance | Dormant 2,880 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 15,209,634 / month, #1,194 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | License :: OSI Approved :: MIT LicenseProgramming Language :: Python :: 2Programming Language :: Python :: 2.7Programming Language :: Python :: 3 |
Evidence: pickleshare-0.7.5-py2.py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “concurrent file-based datastore”
- picklesharePickleShare provides a dictionary-like datastore where multiple…
- oslo.concurrencyoslo.concurrency provides locking mechanisms and external process…
- fastenersProvides cross-platform locks for synchronizing access between…
Give your agent the search over MCP, or paste the wish link into any chat.
More Database packages
psycopg2-binary is a PostgreSQL database adapter for Python that implements the DB API 2.0 specification, enabling Python applications to connect to and query PostgreSQL databases with thread-safe concurrent operations.
Python client library for connecting to and executing commands against Redis key-value stores, supporting both synchronous and asynchronous operations.
Install it if your application needs to interact with Redis; the only prerequisite is a running Redis server instance.
YDB Python SDK is the official client library for connecting to and querying YDB databases from Python applications.
Install it if you need to connect Python applications to YDB databases.
Connects Python applications to Snowflake data warehouses using the DB API 2.0 specification, enabling SQL queries, data transfers, and warehouse operations.
sqlparse tokenizes SQL text into a tree of statements, clauses, and expressions, and provides functions to split scripts, format queries, and inspect parsed tokens without validating dialect or syntax.
Install it if you need to manipulate, format, or analyze SQL text programmatically.
Provides base adapter protocols and shared functionality that database adapters use to integrate with dbt-core, handling connections, dialect translation, relation caching, and core interface management.
See also fcache · partd · speedict · diskcache-weave · diskcache · sqlitedict · rocksdict · locket · oslo.concurrency · pykka