This is an Android application that wraps the DeepL translation website in a WebView to provide a native-like experience. The app features text selection integration, dark mode support, popup mode for floating translations, and settings persistence. It uses a custom NestedScrollWebView to properly handle scrolling interactions within bottom sheets and other nested scrolling contexts. The architecture follows standard Android patterns with Activities, Services, and helper classes for specific functionalities like URL manipulation, cookie management, and WebView configuration.
Twikit is an asynchronous Python library that provides a comprehensive, unofficial client for the Twitter (X) API. It allows users to perform a wide range of Twitter operations—such as posting tweets, searching for tweets and users, managing bookmarks and lists, sending direct messages, uploading media, and streaming real-time events—without requiring an official API key. The library achieves this by reverse-engineering Twitter's internal GraphQL and REST v1.1 endpoints, handling authentication via login flows or guest tokens, and implementing sophisticated anti-bot evasion techniques like client-side transaction ID generation (X-Client-Transaction-Id) and UI metrics obfuscation. The architecture separates concerns into GraphQL (gql) and REST (v11) client modules, with data models for tweets, users, communities, and more. It includes optional CAPTCHA solving and cookie persistence for session reuse. The codebase is well-structured, actively maintained, and demonstrates deep reverse-engineering skill, particularly in the `x_client_transaction` module that mimics Twitter's client-side telemetry.
instagram4j is a Java library that provides an object-oriented interface to Instagram's private (undocumented) API. It supports both mobile and web API endpoints, allowing actions such as logging in with username/password or existing session tokens, fetching profiles, posts, stories, direct messages, searching, posting pictures, liking, commenting, following/unfollowing, and more. The library is structured as a multi-module Gradle project with separate 'mobile' and 'web' modules, each mirroring similar functionality but using different API endpoints (REST for mobile, GraphQL for web). It uses OkHttp for HTTP requests and a custom JSON library. The codebase demonstrates good engineering practices with clear separation of concerns, pagination iterators, and robust error handling. However, there is significant code duplication between the two modules, and the library relies on reverse-engineered endpoints that may break with Instagram updates. The last commit date appears to be in the future (2026), suggesting the repository may be stale or the timestamp is erroneous.
Integuru is a Python application that reverse-engineers API requests from browser traffic to generate runnable integration code. It takes a HAR file (HTTP archive) containing browser network requests and cookie data, then uses LLMs to analyze these requests to identify which endpoint performs a user-specified action. The system builds a dependency graph to determine what prerequisite requests are needed to gather dynamic parameters (like IDs, tokens), and finally generates Python code that can reproduce the action by making the necessary HTTP requests in the correct order. The architecture uses LangGraph for workflow orchestration, with specialized LLM-powered agents handling different aspects of the analysis (URL identification, dynamic parameter extraction, dependency resolution).