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── 99095 repos indexed ── | filtered by tag: #uiautomator
KasperskyLab/Kaspresso ★ 1924 180 APPLICATION

Kaspresso is a comprehensive Android UI testing framework built on top of Espresso (via Kakao) and UI Automator (via Kautomator), providing a Kotlin DSL for writing stable, readable tests. It offers extensive built-in reliability mechanisms: flaky safety (automatic retries with configurable timeouts), auto-scroll fallback, system dialog handling, and element reloading. The framework includes a modular interceptor architecture for customizing test behavior, device manipulation APIs (network, location, phone, permissions, logcat, screenshots, video recording), and integration with Allure for reporting and Jetpack Compose for modern UI testing. Additionally, it provides an ADB server for executing shell commands on the device and a command-line tool for generating page objects from UI dumps. The codebase is well-structured with multi-module Gradle projects, convention plugins, and extensive sample apps demonstrating real-world usage.

RATING: 8.2/10 MAINT: active DRIFT: medium
▸ 4 reusable components found
openatx/uiautomator2 ★ 8424 1606 APPLICATION

This repository provides the Python library `uiautomator2` for Android UI automation. It allows scripts to control Android devices by sending HTTP/JSON-RPC requests to an on-device server (either a Java-based UiAutomator2 jar or the older atx-agent). The core functionality includes element selection via selectors and XPath, gesture simulation (click, swipe, drag), text input via an IME, screenshot capture, UI hierarchy dumps, and app management. It also ships a CLI tool (`u2cli`) with subcommands for device inspection, app operations, and an agent server that exposes a persistent API for LLM/agent-based interactions. The architecture follows a client-server pattern where the Python client communicates over ADB-forwarded ports. The repository includes extensions for HTML reports, performance monitoring, and device info lookups, as well as archived modules for OCR and image recognition. It is widely used for automated testing of Android applications.

RATING: 7.7/10 MAINT: active DRIFT: medium
▸ 4 reusable components found
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