Top 16 Alternatives to Behave for Python Testing

Introduction and context

Behavior-Driven Development (BDD) emerged in the mid-2000s as a way to make tests more readable and collaborative. Tools like Cucumber popularized the Gherkin syntax (Given–When–Then) to express requirements in a human-friendly format that both technical and non-technical stakeholders could understand. In the Python ecosystem, Behave became the de facto “Cucumber for Python,” bringing BDD-style acceptance testing to Python teams.

Behave gained popularity because it:

• Uses Gherkin to write readable specifications that bridge the gap between developers, QA, and business stakeholders.

• Separates feature files (plain text) from step definitions (Python functions) for clear organization.

• Supports tagging, hooks, and reusable steps for structured workflows.

• Plays well with CI and version control, aligning test artifacts with requirements.

However, as test needs broadened—covering web, mobile, desktop, APIs, performance, and visual regressions—teams started evaluating alternatives. Some need faster execution or lower maintenance. Others want low-code options, richer debuggability, visual validation, or specialized support for desktop or embedded systems. This guide walks through 16 strong alternatives to Behave and how they compare for modern Python testing needs.

The top 16 alternatives covered

Here are the top 16 alternatives to Behave for Python testing:

• Airtest + Poco

• Airtest Project

• Applitools Eyes

• Locust

• Mabl

• Playwright

• PyAutoGUI

• Pytest

• Pywinauto

• Repeato

• Robot Framework + SeleniumLibrary

• Selene (Yashaka)

• Squish

• TestCafe Studio

• TestComplete

• Waldo

Why look for Behave alternatives?

Even if you like BDD, there are practical reasons to consider other tools:

• Overhead of the BDD layer: Writing and maintaining feature files plus step definitions adds an abstraction that may slow teams focused on rapid iteration or unit-level tests.

• Verbosity and step sprawl: As features grow, step definitions can become duplicated or overly generic, increasing maintenance costs and making refactoring harder.

• Not ideal for non-functional testing: Behave is not designed for load testing, visual regression, or device/cloud orchestration out of the box.

• Debugging and traceability: Debugging Gherkin-level failures often requires diving through step resolution, which can be less direct than debugging plain Python tests.

• Execution speed: A Gherkin-driven workflow can be slower than direct API-level or browser automation APIs when running large suites.

• Skill alignment: If business stakeholders do not actively participate in writing Gherkin, the readability benefits may not justify the extra complexity.

• Platform breadth: Behave is excellent for acceptance-level logic but does not natively solve challenges in native desktop, embedded, or game UI automation.

If any of the above issues resonate, the tools below offer different trade-offs that might fit your team’s goals and constraints better.

Detailed breakdown of alternatives

Airtest + Poco

Airtest + Poco, from NetEase, is a Python-based automation stack for mobile, desktop, and game testing. Airtest offers image-based (computer vision) interactions, while Poco provides object-based UI access for engines like Unity and native apps.

Core strengths

• Cross-platform: Android, iOS, and Windows support.

• Dual strategy: Computer vision (CV) plus hierarchical UI selectors via Poco.

• Recorder and IDE: AirtestIDE makes authoring and debugging more approachable.

• CI/CD friendly: CLI and Python entry points integrate with pipelines easily.

How it compares to Behave

• Airtest + Poco focuses on end-to-end UI automation, especially for mobile and games, not on BDD-style specification. If your priority is realistic device interactions and resilient selectors for complex UIs, this is a stronger fit than Behave. If you need business-readable Gherkin, Behave still wins.

Airtest Project

Airtest Project broadly refers to the open-source frameworks and tooling centered on game and app UI automation. It emphasizes computer vision for robust interactions where traditional DOM or accessibility layers are limited.

Core strengths

• Game-centric: Optimized for game UIs on Android and Windows.

• Visual-first: CV interactions handle dynamic scenes and non-standard controls.

• Python-driven: Scriptable tests work well with existing Python stacks.

• Pipeline-ready: Suited for automated runs in CI with device farms or emulators.

How it compares to Behave

• Airtest Project shines where Gherkin adds little value—highly dynamic game interfaces. Compared to Behave, it provides richer primitives for UI interactions but no BDD semantics. Choose it for game or graphical UI validation; choose Behave when executable specifications are central.

Applitools Eyes

Applitools Eyes is a commercial visual testing platform that uses AI-powered comparisons to detect visual regressions across web, mobile, and desktop applications. It plugs into many test frameworks, including Python-based ones.

Core strengths

• Visual AI: Detects layout and pixel differences that functional tests miss.

• Ultrafast Grid: Parallel cross-browser rendering for rapid feedback.

• Baseline management: Streamlines visual review and approvals.

• Broad SDK support: Works with Python, JavaScript, Java, and more.

How it compares to Behave

• Applitools is complementary rather than a direct replacement. If your pain is missed visual breakages rather than BDD workflow, Applitools adds value atop existing tests (including Behave). If you need a single tool to both define and execute acceptance tests, Behave is simpler; if you need visual confidence at scale, Applitools is stronger.

Locust

Locust is an MIT-licensed load testing tool where you write user behavior in Python. It scales from local runs to distributed clusters for performance and stress testing of web, API, and protocol targets.

Core strengths

• Python-first: Test scenarios are plain Python, easy to version and review.

• Scalable: Distributed load generation for high throughput.

• Extensible: Hooks for custom metrics and integration with APM/observability tools.

• Web UI and CLI: Real-time monitoring of test runs.

How it compares to Behave

• Locust is specialized for performance, an area Behave does not cover. If your goal is throughput, latency, and scalability under load, pick Locust. Keep Behave for functional acceptance tests if BDD brings value to your team.

Mabl

Mabl is a commercial, low-code end-to-end testing platform for web and API testing with self-healing and AI-assisted maintenance. It is SaaS-first with built-in analytics and CI/CD integrations.

Core strengths

• Low-code authoring: Faster test creation for non-developers.

• Self-healing: Reduces flakiness by adapting to UI changes.

• Rich reporting: Cloud dashboards and insights across runs.

• CI/CD friendly: Pipelines, environments, and data management baked in.

How it compares to Behave

• Mabl trades BDD readability for speed of authoring and maintenance. If your stakeholders do not contribute Gherkin scenarios, Mabl’s low-code, self-healing approach may reduce maintenance compared to Behave-based UI suites. If executable specifications matter, Behave remains more aligned.

Playwright

Playwright is an open-source end-to-end web testing tool from Microsoft, supporting Chromium, Firefox, and WebKit with auto-waiting, tracing, and powerful selectors. It offers official clients for Python, Node.js, Java, and .NET.

Core strengths

• Reliable automation: Auto-waiting and robust locators reduce flakes.

• Cross-browser: One API for multiple engines in headless or headed modes.

• Rich tooling: Trace viewer, network mocking, and code generation.

• Fast execution: Modern architecture and parallelism.

How it compares to Behave

• Playwright focuses on programmatic E2E tests rather than BDD artifacts. If you need fast, reliable browser automation in Python, Playwright will likely outpace a Behave + Selenium stack. If you need business-readable specs, pair Playwright with a BDD layer or stick with Behave.

PyAutoGUI

PyAutoGUI is a cross-platform Python library for automating keyboard and mouse interactions on Windows, macOS, and Linux. It works at the OS level and can automate virtually any on-screen application.

Core strengths

• OS-level control: Works with apps lacking automation APIs.

• Cross-platform: One library for major desktop OSes.

• Simple API: Quick to prototype and script.

• Lightweight: Minimal dependencies.

How it compares to Behave

• PyAutoGUI is not a test framework; it is an automation building block. For desktop or legacy apps where BDD adds little value, PyAutoGUI can be a pragmatic choice. Combine it with a Python test runner (e.g., Pytest) for structure, while Behave remains preferable when you want Gherkin-based documentation.

Pytest

Pytest is the most popular Python testing framework for unit, functional, and integration tests. It offers fixtures, parametrization, and a large plugin ecosystem.

Core strengths

• Pythonic and flexible: Concise tests with rich fixtures.

• Ecosystem: Thousands of plugins (e.g., coverage, xdist, mock).

• Fast local feedback: Parallelization and selective runs.

• Extensible: Easy to create custom markers and hooks.

How it compares to Behave

• If you do not need Gherkin, Pytest is often simpler and faster than Behave for Python teams. You can still adopt BDD-style patterns using plugins if needed. For pure acceptance tests aimed at non-technical stakeholders, Behave’s Gherkin syntax may be more appropriate.

Pywinauto

Pywinauto is an open-source Python library for automating native Windows applications using Win32 and UI Automation (UIA) backends.

Core strengths

• Native Windows support: Access to controls, properties, and events.

• Robust selectors: Identify elements via automation IDs and hierarchies.

• Python-based: Integrates with standard Python tooling and CI.

• Useful for legacy: Works with traditional desktop apps lacking web-like DOMs.

How it compares to Behave

• Pywinauto is ideal for Windows desktop UI testing where Behave offers no native UI automation. If you need acceptance-level descriptions, you could wrap Pywinauto calls in Gherkin steps, but for direct, maintainable desktop automation, Pywinauto alone is leaner.

Repeato

Repeato is a commercial, codeless mobile testing tool using computer vision for Android and iOS. It focuses on resilient tests that tolerate UI changes better than brittle selectors.

Core strengths

• Codeless authoring: Lower barrier for non-developers.

• CV-based resilience: Handles UI changes without fragile locators.

• Mobile-focused: Purpose-built for iOS and Android.

• CI-friendly: Cloud or local execution with reporting.

How it compares to Behave

• Repeato prioritizes speed to value in mobile UI automation, while Behave emphasizes BDD clarity. If your team struggles with flaky mobile selectors or lacks coding capacity for step definitions, Repeato can reduce maintenance overhead. If your organization relies on Gherkin for alignment, Behave remains a better fit.

Robot Framework + SeleniumLibrary

Robot Framework is a keyword-driven automation framework with a large ecosystem. Combined with SeleniumLibrary, it is widely used for web UI testing, though it also supports APIs, desktop, and more via additional libraries.

Core strengths

• Keyword-driven: Human-readable test syntax without Gherkin.

• Ecosystem: Libraries for web, APIs, mobile, desktop, and databases.

• Reporting: Detailed logs and reports out of the box.

• Extensibility: Custom keywords in Python and integration with CI.

How it compares to Behave

• Both Robot Framework and Behave aim to be readable for non-developers. Robot uses keyword tables instead of Given–When–Then. If you need a broader set of built-in libraries and reporting with less glue code, Robot can be more productive. If your teams already collaborate around Gherkin, Behave is more aligned.

Selene (Yashaka)

Selene is a Selenide-inspired Python wrapper over Selenium, focused on concise, readable, and stable web UI tests. It adds smart waiting and expressive selectors.

Core strengths

• Concise API: Reduces boilerplate compared to raw Selenium.

• Smart waits: Fewer flaky tests due to automatic conditions.

• Readability: Expressive, chainable actions and assertions.

• Python-friendly: Works seamlessly with Pytest and other tools.

How it compares to Behave

• Selene is not a BDD framework; it is a better way to write Selenium-based tests. If your pain with Behave is slow, verbose UI automation using Selenium, Selene can make tests smaller and more reliable. If BDD artifacts are essential, combine Behave with Selene or remain with Behave alone.

Squish

Squish is a commercial tool from The Qt Company for testing Qt, QML, web, desktop, and embedded UIs. It supports scripting in Python, JavaScript, Ruby, Tcl, and Perl and is known for strong object recognition in complex UIs.

Core strengths

• Deep Qt/QML support: Best-in-class for Qt and embedded UIs.

• Multi-technology: Web, desktop, and embedded platforms in one tool.

• Powerful object recognition: Stable selectors and introspection.

• Professional tooling: Integrated recorder, debugger, and reporting.

How it compares to Behave

• Squish is a full-stack GUI testing solution with broad platform support, especially for Qt. It is stronger for native/embedded objects than Behave, which requires additional automation tooling. If BDD documentation is less important than strong object-level control, Squish may be the better choice.

TestCafe Studio

TestCafe Studio is a commercial, codeless IDE built on top of the open-source TestCafe engine for web testing. It offers a recorder, visual editor, and parallel execution across browsers.

Core strengths

• Codeless creation: Record and edit tests visually.

• Cross-browser: Runs on Chromium, Firefox, and WebKit engines.

• Stable selectors: Selector strategies designed for maintainability.

• Integrated tools: Visual debugging and reporting.

How it compares to Behave

• TestCafe Studio optimizes for fast authoring and execution rather than BDD collaboration. If you need non-technical contributors to author web tests without managing Gherkin and step code, it provides a lower-friction path than Behave. Behave remains preferable for teams invested in Gherkin workflows.

TestComplete

TestComplete is a commercial end-to-end testing tool from SmartBear supporting desktop, web, and mobile. It offers record/playback and scripting in JavaScript, Python, and other languages.

Core strengths

• Cross-platform coverage: Desktop, web, and mobile in one suite.

• Codeless + scripted: Start with recording and enhance with code.

• Object recognition: Object spy and name mapping for stable tests.

• Enterprise features: Data-driven testing, reporting, and CI plugins.

How it compares to Behave

• TestComplete is an all-in-one automation suite with strong tooling, while Behave is a lightweight BDD layer that requires pairing with automation libraries. If you want an integrated environment and can accept licensing costs, TestComplete reduces glue work. For BDD and open-source alignment, Behave remains compelling.

Waldo

Waldo is a commercial, codeless mobile test platform for iOS and Android with a focus on recorder-driven authoring and cloud device execution.

Core strengths

• No-code: Create tests quickly without programming.

• Cloud execution: Run on real devices with parallelism.

• Visual focus: Assertions and flows centered on screen states.

• CI integration: Trigger runs and retrieve results programmatically.

How it compares to Behave

• Waldo accelerates mobile UI testing for teams without Python or mobile automation expertise. It does not provide BDD-style specifications, so if readable requirements are key, Behave fits better. If you need quick, scalable mobile coverage, Waldo offers speed and simplicity.

Things to consider before choosing a Behave alternative

Before you commit, weigh the following:

• Project scope and test levels: Are you doing unit, API, UI, performance, or visual testing? Many tools excel at one layer; avoid stretching tools beyond their strengths.

• Language and stack alignment: Do you want pure Python, or are you open to mixed stacks? Consider developer familiarity and hiring realities.

• Authoring model: BDD (Gherkin), keyword-driven, low-code/codeless, or code-first APIs each impact collaboration and maintenance.

• Setup and execution speed: How fast can you get to a reliable green build? Consider local dev ergonomics, parallelism, and test startup overhead.

• CI/CD integration: Look for first-class CLI support, containerization, and artifacts (reports, videos, traces) that fit your pipeline.

• Debugging and observability: Traces, screenshots, logs, network captures, and step-by-step replay can drastically cut triage time.

• Platform coverage: Web, mobile, desktop, embedded, and game UIs all require different capabilities and selectors.

• Ecosystem and community: Plugins, libraries, community recipes, and active maintenance matter over the long term.

• Scalability: Parallel execution, distributed runners, and cloud device/browser grids impact throughput.

• Cost and licensing: Evaluate total cost of ownership, including hosting, training, maintenance, and vendor lock-in.

• Team skill mix: Will QA, developers, or business analysts author and maintain tests? Choose an authoring model that matches your contributors.

Conclusion

Behave remains a solid, open-source BDD framework for Python, especially when your organization benefits from readable Given–When–Then specifications that align developers, QA, and business stakeholders. Its strengths are clarity and collaboration, not necessarily speed or breadth of platform support.

If your pain points are around UI flakiness, execution speed, or coverage outside web back ends, consider specialized alternatives:

• For fast and reliable web E2E: Playwright or Selene.

• For desktop or Windows apps: Pywinauto or PyAutoGUI.

• For mobile and games: Airtest + Poco, Airtest Project, Repeato, or Waldo.

• For visual regressions: Applitools Eyes.

• For performance: Locust.

• For low-code or all-in-one suites: Mabl, TestCafe Studio, or TestComplete.

• For keyword-driven acceptance tests with broad libraries: Robot Framework + SeleniumLibrary.

In many teams, the best solution is a combination: use a code-first tool for fast, robust UI and API tests, add a visual testing layer where it matters, and keep BDD for high-value acceptance criteria. Start by clarifying who writes the tests, what platforms you must cover, and how quickly you need feedback in CI. With those answers, the right alternative to Behave—or the right mix—will become clear.