try vs virtualenv

Side-by-side — pricing, strengths, tradeoffs, and fit.

try

A CLI to easily try out Python packages.

virtualenv

Create isolated Python environments for project-specific dependencies.

At a glance

Open SourceFree Tier
◌ Declining·From $0
Open SourceFree Tier
● Established·From $0

Overview

One-liner

A CLI to easily try out Python packages.

One-liner

Create isolated Python environments for project-specific dependencies.

Maturity

Declining

Maturity

Established

Open source

✓ Yes

Open source

✓ Yes

Pricing

Free tier

✓ Available

Open source — free to use

Free tier

✓ Available

Open source — free to use

Starts at

$0

Starts at

$0

Model

Flat rate

Model

Flat rate

Enterprise

✕ None

Enterprise

✕ None

Best for

✓ Best for

Developers looking to quickly test the functionality of various Python packages without manual setup.
Teams that need a streamlined process for evaluating new libraries before integrating them into projects.

✓ Best for

Developers working on multiple Python projects with differing dependencies
Teams needing to isolate project environments for consistent testing and deployment

Not ideal for

✕ Not for

Projects requiring real-time package updates or continuous integration testing
Users who prefer graphical user interfaces over command-line tools

✕ Not for

Projects requiring cloud-based or managed environment services
Users who prefer a fully integrated development environment (IDE) solution over command-line tools

Strengths

↑ Strengths

Quickly test Python packages without installation
Simplified experimentation with new libraries
Easy to integrate into development workflows

↑ Strengths

Isolated Python environments for each project
Easy installation of packages without affecting system-wide dependencies
Supports both virtualenv and venv creation methods

Weaknesses

↓ Weaknesses

Limited to Python only, no support for other languages
Potential security risks when testing unknown packages
Documentation is sparse and lacks comprehensive examples
Performance overhead when testing large packages

↓ Weaknesses

Steep learning curve for non-Python developers
Limited language support beyond Python
Complex setup process for advanced configurations
Performance overhead when managing multiple environments
Full try profile →Full virtualenv profile →