Top 4 Open-Source Alternatives to Behave

Introduction: Where Behave Came From and Why It Matters

Behavior-Driven Development (BDD) grew out of the test-driven development movement in the mid-2000s. The goal was simple: make tests readable to everyone involved in software delivery—developers, QA, product managers, and business stakeholders—so that tests double as living documentation. Tools like Cucumber popularized plain-language specifications written in Gherkin (Given-When-Then) that map to executable step definitions in code.

Behave is often described as “Cucumber for Python.” It brings the BDD approach to Python projects by letting teams:

• Write features in Gherkin syntax (feature files).

• Implement step definitions in Python.

• Organize scenarios with tags and hooks.

• Share state via a test context.

• Run meaningful acceptance tests that read like requirements.

This combination made Behave popular in Python ecosystems that value collaboration and specification clarity. Teams adopted it to ensure business rules are explicit, testable, and verifiable, and to bridge language barriers between technical and non-technical roles.

However, practices and tool choices evolve. While Behave remains a strong choice for BDD in Python, some teams look beyond it—either because they do not need BDD’s extra abstraction, they want something optimized for a different platform (e.g., Go or Ruby), or they need stronger support for desktop or web UI automation without the BDD layer.

This guide explores four open-source alternatives that teams consider when Behave is not the best fit for their context.

Overview: The Top 4 Alternatives Covered

Here are the top 4 alternatives for Behave:

• Go test

• PyAutoGUI

• Pywinauto

• Watir

Each tool approaches testing from a different angle—language, layer of the stack, or user interface—and each can replace Behave in the right scenario.

Why Look for Behave Alternatives?

BDD unlocks collaboration and readability, but it also introduces trade-offs. Common reasons teams seek alternatives include:

• Extra abstraction and overhead: Maintaining feature files, step definitions, and glue code adds layers that may not be necessary for small teams or projects.

• Verbosity and duplication: Scenarios can become verbose. Step reuse is powerful but can also lead to rigid or bloated step libraries over time.

• Speed and feedback loops: Parsing Gherkin and running high-level acceptance tests can slow down the test cycle compared to unit or integration tools.

• Platform fit: Behave is Python-first. Teams primarily coding in Go or Ruby may prefer native tooling aligned with their language ecosystem.

• Reporting and analytics: Out of the box, reporting can be limited. Teams often need plugins or custom pipelines for detailed dashboards and flaky test analysis.

• UI automation complexity: Behave itself is not a UI automation engine. For desktop or browser automation, you still need libraries (e.g., Selenium, pywinauto, or image-based tooling), which adds integration effort.

• Test flakiness management: High-level BDD scenarios often drive more complex end-to-end flows, which can be flaky if not carefully designed (waiting strategies, robust locators, isolation of test data).

If these pain points resonate—or if your stack and automation goals point elsewhere—one of the following tools may be a better fit.

Alternative 1: Go test

What it is and who built it

Go test is the built-in testing toolchain for the Go programming language. It is maintained by the Go team and the broader open-source community under a BSD-style license. Because it is part of the standard toolset (go test), it is tightly integrated with the Go ecosystem and widely used for unit, integration, and even system-level tests in Go services.

What makes it different

Rather than a BDD layer, Go test offers a pragmatic, code-centric testing experience. It favors fast feedback, simple conventions, and native integration with Go’s toolchain, including benchmarks, coverage, and race detection.

Core strengths

• Well-established in its niche: A standard for Go projects with strong community backing.

• Useful for test automation: Ideal for automated testing in CI/CD pipelines due to consistent CLI and tooling.

• Speed and efficiency: Compiled tests run quickly; excellent for microservices and backend systems.

• Concurrency support: Native support for testing concurrent code and detecting data races via the race detector.

• Built-in benchmarks and coverage: First-class support for performance testing and coverage analysis without extra plugins.

• Simple, portable workflows: Works out of the box across platforms supported by Go.

How it compares to Behave

• Language fit: If your services are written in Go, go test is idiomatic and requires no extra layers. Behave, being Python-based, would be an external dependency and a cross-language integration.

• Abstraction vs. clarity: Behave’s Gherkin aims for business-readable specs. Go test favors code readability for developers, not business stakeholders. You trade collaboration-friendly feature files for a leaner, code-only approach.

• Test levels: Behave is often used for acceptance and end-to-end tests. Go test excels at unit and integration tests; UI automation is not its purpose.

• Tooling ecosystem: Go test integrates seamlessly with the Go toolchain (benchmarks, coverage, race detector). Behave relies on Python tooling and plugins.

Best for

• Teams writing Go services that want fast, maintainable tests with minimal dependencies.

• Projects where the audience for tests is primarily developers and infrastructure engineers.

• Automation-heavy CI/CD pipelines where execution speed and stability are priorities.

Limitations

• Niche applicability: Best when your codebase is in Go; less useful for Python or mixed-language applications that expect BDD.

• UI automation: Not a fit for browser or desktop UI testing without external tools and wrappers.

Alternative 2: PyAutoGUI

What it is and who built it

PyAutoGUI is a cross-platform GUI automation library for Python. It simulates mouse and keyboard actions and can locate GUI elements using screenshots. It is BSD-licensed and maintained by the open-source community. It is often associated with Al Sweigart’s work and is widely used for lightweight desktop automation.

What makes it different

PyAutoGUI automates any application the same way a human would—by moving the mouse, clicking, typing, and recognizing on-screen images. It is not a test framework; rather, it is a driver you can script. This makes it useful for automating legacy or third-party desktop applications where no API or accessibility layer is available.

Core strengths

• Supports native desktop application testing: Works across Windows, macOS, and Linux by simulating OS-level input.

• Close OS integration: Drives real user interactions for “black-box” applications that lack automation hooks.

• Simple API: Easy to start with for smoke tests and repetitive tasks; minimal boilerplate.

• Cross-platform: Write once, run on major desktop platforms with minimal changes.

• Flexible composition: Can be combined with Python test runners or frameworks (e.g., pytest) when you do not need the BDD layer.

How it compares to Behave

• Purpose: Behave structures tests with human-readable scenarios; PyAutoGUI is a low-level UI driver. If you do not require Gherkin features or stakeholder-readable specs, PyAutoGUI can be a leaner route to desktop automation.

• Coverage: Behave itself does not automate UIs; you would need a driver anyway. PyAutoGUI can serve as that driver, either standalone or as an implementation detail behind Behave steps.

• Maintenance: PyAutoGUI scripts can be brittle if they rely heavily on pixel-based image matching. Behave does not solve this; it only organizes tests. If you want less abstraction and direct control over UI actions, PyAutoGUI provides it.

Best for

• QA teams working on legacy or enterprise desktop applications where accessibility APIs are limited or unavailable.

• Quick automation of repetitive desktop tasks without setting up a full BDD framework.

• Cross-platform desktop testing scenarios that prioritize simplicity.

Limitations

• Platform-specific limitations: Permissions, security prompts, focus issues, and different display scaling can affect reliability.

• Smaller ecosystem than web testing: Fewer plugins and patterns for large-scale test suites.

• Flakiness risk: Image-based locators and timing issues can introduce instability without careful synchronization.

Alternative 3: Pywinauto

What it is and who built it

Pywinauto is a Python library for automating native Windows applications. It leverages accessibility technologies such as Microsoft UI Automation (UIA) and Win32 APIs. The project is open source (BSD) and maintained by community contributors. It focuses specifically on Windows UI automation and provides a richer, element-based approach than image matching.

What makes it different

Unlike tools that rely on screenshots, pywinauto interacts with application elements through accessibility trees and control identifiers. This usually produces more stable and maintainable test code for Windows applications.

Core strengths

• Broad UI automation capabilities on Windows: Works with Win32, UIA, and common frameworks used by Windows apps.

• Element introspection: Robust selectors and inspection tools for reliable element identification.

• Better stability than pure image matching: Reduces flakiness via structured UI automation APIs.

• Integrates with CI/CD: Can be scripted and executed as part of Windows-based pipelines.

• Modern workflows: Supports building maintainable page- or screen-object abstractions, versioning, and modular test design.

How it compares to Behave

• Layer and purpose: Behave organizes scenarios; pywinauto actually drives Windows UIs. If your main testing target is Windows desktop, pywinauto can be the core automation library, with or without a BDD layer.

• Readability vs. control: Behave’s readable specs help stakeholders. Pywinauto gives precise, developer-centric control of the UI. Teams that value direct control and stability over narrative specs often favor pywinauto for Windows.

• Combining tools: You can use pywinauto underneath Behave step definitions to keep Gherkin specs while improving Windows UI reliability. Or you can drop the BDD layer and run pywinauto with a lightweight Python test runner.

Best for

• Teams automating end-to-end flows across Windows applications.

• Projects with complex native Windows UIs that need robust selectors and synchronization.

• QA organizations that want maintainable, element-based desktop tests with CI/CD integration on Windows agents.

Limitations

• Windows-only: Not suitable for macOS or Linux desktop testing.

• Setup and maintenance: Requires tooling setup (e.g., accessibility inspectors) and careful test design to minimize flakiness in dynamic UIs.

• Test flakiness if poorly structured: As with any UI automation, brittle locators and timing issues can cause instability without proper waits and abstractions.

Alternative 4: Watir

What it is and who built it

Watir (Web Application Testing in Ruby) is a Ruby library for automating web browsers. It builds on Selenium WebDriver to provide a clean, Ruby-friendly API for browser automation. The Watir project is maintained by the open-source community under a BSD-style license and has a long, well-regarded history in the web testing space.

What makes it different

Watir emphasizes readable Ruby code for UI tests without forcing BDD or Gherkin. It delivers a high-level DSL atop Selenium that simplifies waits, element interactions, and cross-browser support. It also fits smoothly into Ruby-centric pipelines and can be paired with Ruby test frameworks and BDD tools if needed.

Core strengths

• Broad test automation capabilities for the web: Strong cross-browser support through Selenium WebDriver.

• Supports modern workflows: Works well with page objects, factories, and modular test design.

• Integrates with CI/CD: Mature support for headless runs, parallelization (via additional tools), and containerized environments.

• Developer-friendly DSL: Ruby’s expressiveness makes test code concise and maintainable.

• Strong community and history: Battle-tested for web UI testing with extensive examples and guidance.

How it compares to Behave

• Language ecosystem: Watir is Ruby-based. If your team is comfortable with Ruby or your services already use Ruby tooling, Watir aligns better than a Python-based BDD stack.

• Abstraction choice: Behave enforces BDD with Gherkin; Watir is a browser automation library. If you prefer to avoid BDD overhead and write tests directly in code, Watir’s DSL provides a clean alternative.

• Flexibility: You can still do BDD in Ruby (e.g., with Cucumber) on top of Watir if you want business-readable specs, or keep it simple with Ruby test frameworks. In contrast, Behave is tightly bound to Gherkin.

Best for

• Teams automating end-to-end flows across browsers and platforms using Ruby.

• Projects that want concise, code-first web UI tests without a mandated BDD layer.

• Organizations needing a stable, Selenium-based tool with a Ruby-friendly interface.

Limitations

• Requires Ruby expertise: Best for teams that already know Ruby or are willing to adopt it.

• UI flakiness concerns: As with any web UI automation, locator strategy, waiting, and environment stability are critical.

• May require setup and maintenance: Grid setup, browser drivers, and parallelization add operational overhead.

Things to Consider Before Choosing a Behave Alternative

Selecting the right tool depends on your stack, goals, and team skill set. Consider the following before you decide:

• Project scope and test levels:

• Language and ecosystem fit:

• Platform coverage:

• Ease of setup and maintainability:

• Execution speed and feedback loops:

• CI/CD integration:

• Reporting and debugging:

• Flakiness mitigation:

• Community support and documentation:

• Scalability and cost:

Putting It All Together: Which Alternative Fits Your Situation?

• If your services are primarily written in Go and you want fast, reliable unit and integration tests with minimal dependencies, choose Go test. It is a natural fit for Go codebases and provides excellent performance and tooling.

• If you need to automate cross-platform desktop applications without accessibility APIs or if you want a simple way to script user interactions, choose PyAutoGUI. It is a lightweight option for legacy or black-box desktop apps.

• If your testing focus is native Windows applications and you need stable, element-based automation, choose Pywinauto. Its use of Windows accessibility APIs provides more reliable selectors and synchronization than image-based tools.

• If your goal is browser-based end-to-end testing and you prefer a clean, code-first approach in Ruby, choose Watir. It provides a robust, developer-friendly DSL on top of Selenium WebDriver and integrates well with modern CI/CD practices.

Of course, these tools are not mutually exclusive with Behave. Many teams combine a BDD layer for stakeholder-facing scenarios with a code-centric tool underneath for actual automation:

• Behave + Pywinauto for readable Windows desktop acceptance tests.

• Behave step definitions calling PyAutoGUI for legacy desktop flows.

• A pure Go stack using go test for service-level tests, while a separate UI suite uses Watir for end-to-end browser coverage.

Conclusion

Behave remains a powerful BDD framework for Python projects, especially where readable specifications and shared understanding are essential. Its strengths—clear Gherkin feature files, collaboration across roles, and a familiar model for acceptance testing—continue to make it a solid choice.

However, today’s testing needs are diverse. Teams may favor language-native tools for speed and simplicity (Go test), require specialized desktop UI automation (PyAutoGUI or Pywinauto), or prefer a code-first web testing library with a mature ecosystem (Watir). Each alternative shines in particular scenarios:

• Go test for high-speed, developer-focused testing in Go services.

• PyAutoGUI for cross-platform desktop automation, particularly legacy apps.

• Pywinauto for stable Windows UI automation with rich element control.

• Watir for clean, Ruby-based browser automation without enforced BDD.

Before you decide, evaluate your application’s platform, your team’s language strengths, the test levels you need, and how quickly you want feedback in CI/CD. In many cases, the best solution is a pragmatic mix: keep Behave for the specifications that matter to stakeholders and use one of these alternatives where you need tighter language integration, faster feedback, or specialized platform support.

If you aim to simplify execution at scale, plan out your test pyramid, invest in robust locators and synchronization, and automate your environment provisioning. These practices will pay off regardless of the tool you choose—and will help you get the most value from Behave or any of its open-source alternatives.