Install packages once.
Use them everywhere.

The pnpm of Python. Drop-in replacement for pip and uv that saves GBs of disk space using shared global symlinks.

terminal — pepip
$ pepip install pandas
Checking global store...
Found pandas==2.2.0 in ~/.pepip/store
Creating symlink in ./site-packages...
Done in 0.04s (using uv)
$ |
The Redundancy Tax

Stop wasting your disk space on duplicate dependencies.

Traditional pip installs complete package copies into every virtual environment. Developing 5 projects with Pandas? That's 5 copies of the same binary blobs eating your SSD.

Standard pip: 2.5GB per env
Time lost syncing: 15min/day
folder
Project A Pandas (120MB)
folder
Project B Pandas (120MB)
folder
Project C Pandas (120MB)
add_circle Potential Savings 80% Disk Reduction

The Symlink Revolution

Pepip stores every version of every package in a single, central store on your machine. Local environments simply link to these files.

database

Global Store

One immutable instance of every package at ~/.pepip/store

link

Content Addressing

Hard-links and symlinks prevent accidental mutations and maximize sharing.

bolt

Zero Copy

Creating an environment is as fast as your OS can create directory entries.

speed

Lightning Fast (Powered by uv)

Pepip uses the high-performance 'uv' resolver and installer under the hood. It’s written in Rust, but optimized for global storage.

pepip install numpy scipy torch | Resolved in 120ms
hard_drive

Disk Efficient

Save up to 90% of disk space in large monorepos or multi-project workstations.

groups

Team Shared

Set PEPIP_HOME to a shared drive to sync dependencies across your entire internal network instanty.

swap_horiz

Drop-in Replacement

Use the commands you already know. No new learning curve, no specialized configuration files required.

# Before
pip install django
# After
pepip install django

Numbers don't lie.

We benchmarked pepip against standard pip and vanilla uv on a machine with 50 existing virtual environments. The difference isn't just incremental—it's transformative.

Disk Usage Reduction -82%
Cold Install Latency -41%
Subsequent Installs -99.8%
analytics

Storage Efficiency

pip
uv
pepip

Get started in seconds.

Install pepip
pip install pepip
Typical Usage
pepip install numpy scipy scikit-learn

Works on macOS, Linux, and Windows.