node-telegram-bot-api is a TypeScript client library for the Telegram Bot API, built as a runtime-agnostic core plus Node.js and Bun adapters. It exposes a Bot class with koa-style middleware, Context helpers, generated Api methods that map 1:1 to Telegram endpoints, and both long-polling and webhook update ingestion. The package targets Node 18+, Bun, Deno, Cloudflare Workers, and Vercel Edge by restricting src/core to Web-standard APIs and enforcing these boundaries with CI gates. It is a library, not a standalone app; consumers embed it to build Telegram bots. In production, the library receives updates either from getUpdates long polling (an AsyncGenerator with retry, backoff, and conflict handling) or from webhook callbacks (Web-standard Request to Response handlers plus adapters for Express, Next.js App Router, and Node HTTP). It includes a resilient transport layer with timeouts, retries, token-bucket rate limiting, and streaming multipart uploads, plus optional session middleware with pluggable stores (memory, file, SQLite, Redis) and a reply/callback tracking layer for structured conversations. The full Telegram type surface is auto-generated from live Bot API documentation by scripts/api-parser.ts, producing schemas.ts and api.ts, and the e2e suite exercises real Telegram endpoints. Architecturally, the most reusable patterns are generic middleware composition, an injectable fetch transport with backoff, a token-bucket rate limiter with per-key LRU state, and a streaming multipart encoder that avoids buffering whole uploads in memory. Session stores are deliberately minimal string-keyed KV contracts, with versioned envelopes allowing optional layers to extend state. The codebase is well tested, documented with 18 examples, and under active maintenance. This is not a data_research repository; the code generation pipeline is a build-time tool, not the product itself.
python-telegram-bot is a pure Python, asynchronous library that provides both low-level bindings to the Telegram Bot API and a high-level application framework for building Telegram bots. In production, it handles authentication, message sending/receiving, update processing, and bot lifecycle management. The library is used by developers to create bots that can respond to commands, messages, inline queries, callback queries, and other Telegram events, with support for payments, passports, polls, and more. The architecture is organized into three layers: the core `telegram` package containing data models for all Telegram API types (Chat, User, Message, etc.) with consistent serialization and equality semantics; the `telegram.ext` extension framework providing handlers (CommandHandler, MessageHandler, ConversationHandler), an Application class for orchestrating update processing, job queues, persistence, and rate limiting; and the `telegram.request` layer using httpx for async HTTP communication. The library uses async/await throughout and follows a handler-based event-driven pattern. Key entry points include `telegram.ext.Application` (built via `ApplicationBuilder`), `telegram.Bot` for direct API calls, and various handler classes. The primary data flow involves receiving updates from Telegram via polling or webhook, parsing them into `Update` objects, dispatching to registered handlers based on filters, and executing callback functions that can call Bot methods to respond. The library supports custom context types, persistent storage of bot/user/chat data, and scheduled jobs. External dependencies are minimal: `httpx` is the only required runtime dependency. Optional features require additional packages: `cryptography` for Telegram Passport, `APScheduler` for job queues, `cachetools` for callback data caching, `tornado` for webhook server, `aiolimiter` for rate limiting, and `pytz`/`zoneinfo` for timezone support. The library is extensively tested with both offline unit tests and online integration tests against the live Telegram API.
tqdm is a fast, extensible progress bar library for Python and CLI. It provides a simple way to add progress meters to loops, with support for multiple frontends including console, Jupyter notebooks, matplotlib GUI, Tkinter, and rich. The core implementation in `tqdm/std.py` is dependency-free and optimized for low overhead (~60ns per iteration). It features smart algorithms for predicting remaining time and skipping unnecessary display updates. The library integrates with pandas, keras, dask, asyncio, and concurrent.futures. The CLI mode allows piping data through tqdm for progress monitoring. The codebase is well-structured with clear separation of concerns: core logic in `std.py`, frontends in separate modules (`notebook.py`, `gui.py`, `tk.py`, `rich.py`), and integrations in `contrib/`. Extensive test suite covers performance, correctness, and edge cases. The project is actively maintained with regular releases and CI.
This repository implements a local MTProto proxy for Telegram Desktop, designed to bypass network censorship by wrapping Telegram's protocol in WebSocket connections, often routed through Cloudflare. It is a fully-featured desktop application with CLI and GUI modes, providing a robust solution for circumventing DPI-based blocking. The architecture is a monolithic asyncio application with a clear separation of concerns: the `proxy/` package handles the core protocol translation (MTProto to WebSocket, Fake TLS, HTTP/2 multiplexing), the `ui/` package provides a cross-platform tray interface using CustomTkinter, and `utils/` contains supporting infrastructure like update management and diagnostics. The system employs a sophisticated fallback chain (WebSocket pool -> Cloudflare Proxy -> Cloudflare Worker -> Direct TCP) to ensure reliability. The codebase demonstrates high engineering craftsmanship. It features several genuinely reusable components, including a custom `httpx` HTTP/2 transport, a robust connection pool with exponential backoff, and an atomic self-update mechanism with rollback. While tightly coupled to Telegram's specific protocol, the underlying patterns for network resource management, protocol obfuscation, and desktop application lifecycle are well-isolated and could be extracted for other projects. The extensive test suite and professional CI/CD pipeline further attest to its quality.
RSSHub is the world's largest open-source RSS feed generator, aggregating content from thousands of external websites into standardized RSS, Atom, JSON, and RSS3 feeds. It is a TypeScript application built on the Hono web framework, with a modular architecture where each source (news site, social platform, university notice board, government agency, etc.) is implemented as a self-contained 'route' module that fetches pages or APIs, parses HTML with Cheerio, and optionally renders rich descriptions using JSX. The project supports multiple deployment targets including Node.js, Docker, Vercel, and Cloudflare Workers, and integrates caching (Redis/LRU), middleware for access control, ETag/conditional requests, error tracking (Sentry, Honeybadger), and anti-hotlinking. The codebase is highly organized with consistent route definitions, extensive utility functions (date parsing, HTTP caching, header generation), and a strong emphasis on type safety. While the sheer volume of routes (thousands) introduces maintenance burden and some inconsistency (legacy `got` vs modern `ofetch`), the overall architecture is clean, well-tested for core infrastructure, and exhibits strong engineering practice. This is not a data-research repository; it is a production-grade web service for feed aggregation.
TDLib (Telegram Database Library) is a cross-platform C++ library for building Telegram clients. It implements the full MTProto protocol stack, including encryption, transport (TCP, HTTP, TLS), and proxy support (SOCKS5, HTTP). The library manages all Telegram data types (messages, users, dialogs, files, etc.) with local persistence via SQLite and a custom binary log for crash-safe state. It provides a clean JSON-based API (td_json_client) for usage from any language, along with native bindings for Java, .NET, C, and more. The architecture is actor-based (tdactor), enabling high concurrency without explicit thread management. The codebase also includes code generation tools that produce serialization code from Telegram's Type Language (TL) schema, ensuring type safety and protocol compliance.
The repository is a Kotlin library for the Telegram Bot API, providing a type-safe and easy-to-use wrapper for building Telegram bots. It features a dispatcher-based update handling system, custom Gson adapters for polymorphic types, and support for both polling and webhook approaches. The library is well-structured with clear separation of concerns, comprehensive test coverage, and modern Kotlin practices. The architecture includes network layer (Retrofit/OkHttp), data models (Kotlin data classes), dispatcher/handler system for update processing, and a DSL for declarative bot configuration.
This repository is a Java/Kotlin client library for the Telegram Bot API, providing type-safe wrappers for all bot API methods and models. The architecture is a classic library with a fluent builder pattern: users create request objects (e.g., `SendMessage`, `GetUpdates`), execute them via the `TelegramBot` class, and receive typed responses. The library handles both synchronous and asynchronous execution, supports long-polling and webhook modes, and includes Telegram Passport encryption/decryption utilities. The codebase is well-structured, with clear separation into model, request, response, and utility packages. It features custom Gson adapters for polymorphic API types (e.g., reaction types, chat boost sources) that demonstrate a clean discriminated union deserialization pattern. The library is actively maintained, tracking Telegram Bot API updates closely, and includes Kotlin extension functions for idiomatic usage. It is not a data research project; it is purely an integration library.
TelegramRSS is a PHP web service that acts as a proxy between clients and a Telegram API server, providing RSS and JSON feeds of Telegram channel content. Built with AMPHP for asynchronous handling, it features rate limiting, IP-based access control, and middleware-based request processing. The service fetches messages from Telegram via a backend API server and formats them as RSS or JSON responses with media support.
AstrBot is a production-grade, multi-platform LLM chatbot framework and development platform. It connects to 10+ instant messaging platforms (QQ, Telegram, Discord, Slack, WeChat, Lark, etc.) via adapter pattern, integrates with 20+ LLM providers (OpenAI, Anthropic, Gemini, DashScope, etc.), and provides a plugin system (Stars) with command/regex/filter decorators. The architecture is a modular monolith: a FastAPI backend serves a Vue 3 dashboard for management, while a pipeline of stages processes incoming messages through waking checks, rate limiting, content safety, LLM interaction, and response delivery. It includes a knowledge base with RAG (FAISS vector store, chunking, hybrid retrieval), agent runners (Dify, Coze, DeerFlow), sandboxed code execution (computer use), TTS/STT, cron jobs, and a CLI. The codebase is well-structured with extensive test coverage, but its broad scope introduces some duplication and deprecated modules.
Diun is a Go-based CLI daemon that monitors container image registries and notifies users when new versions or updates are available. It operates by polling container runtime environments (Docker, Swarm, Kubernetes, Nomad, containerd), or reading from YAML or Dockerfiles, to discover images, then compares their registry digests (or manifest list platform-specific digests) against a local bbolt database. When a change is detected, it sends notifications through one or more of 20+ channels (Slack, Discord, Telegram, email, webhook, MQTT, etc.). The system also exposes Prometheus metrics, a gRPC interface for image lifecycle management, and supports health checks via healthchecks.io. The architecture is modular: a scheduler component (cron-based with jitter and worker pool) triggers jobs that walk through configured providers (each implementing a `Handler` interface returning a list of `model.Image`), then for each image the registry client fetches the latest manifest (with tag sorting and filtering), compares it against the stored digest, updates the database, and dispatches notification entries through a notifier chain. The design cleanly separates provider discovery, registry inspection, state persistence, and notification delivery into independent packages. External dependencies include container runtime SDKs (Docker, containerd, Kubernetes, Nomad), the OCI distribution registry API, and each notification service's client library. The codebase is well-structured with strong test coverage, configuration via YAML and environment variables, and comprehensive CI/CD including e2e tests, static analysis, and vulnerability scanning. It is actively maintained with frequent releases and responsive issue triage. Primary entry points are `cmd/serve.go` (main daemon), `cmd/healthcheck.go`, `cmd/image.go` (gRPC-based image management), and `cmd/notif.go` (test notifications).
This repository is a comprehensive Node-RED package for building multi-platform chatbots with minimal coding. It provides a visual flow editor (Node-RED) with over 100 custom nodes for message handling, conversation management, AI integration (OpenAI, Dialogflow), and platform adapters for Telegram, Facebook Messenger, WhatsApp, Slack, Viber, Sinch, DeepChat, and more. The package also includes Mission Control, a React-based admin dashboard for managing users, content, messages, plugins, and device tracking, with a GraphQL API and WebSocket real-time updates. The architecture follows a middleware pattern (ChatExpress) for message normalization and platform abstraction, with a plugin system (code-plug) for extending the admin UI. While primarily an application, it includes some data persistence (SQLite via Sequelize) for chat logs, user records, and content management, but no data science or analytics pipelines.
Universal Notifier is a Home Assistant custom integration that acts as a centralized notification router. It exposes a single `universal_notifier.send` service that fans out messages to multiple channels—text (Telegram, mobile app) and voice (Alexa, Google Home via TTS)—with context-aware features: time-of-day greetings, per-slot volume control, weekday/weekend Do Not Disturb schedules, priority bypass, and a FIFO async queue for serialized voice announcements. The integration also provides monitoring entities (volume sensor, family presence sensor, DND binary sensor) and runtime controls (priority volume select, text format select, voice buffer number, DND override switch, last-message text). Configuration is fully UI-driven via a multi-step config flow and an options menu for post-setup edits. Architecturally, the component is a typical Home Assistant custom component with modular entity platforms (sensor, binary_sensor, select, number, switch, text) and a core `__init__.py` that registers the service, manages the voice queue worker, and handles snapshot/resume of media players. The code is well-organized, uses standard HA patterns (config entries, entity registry, service registrations), and includes a solid test suite with high coverage. The main service handler is long and somewhat monolithic, but it is subdivided into labeled sections and handles many edge cases (e.g., `notify.send_message` target kwargs, Telegram chat IDs, MarkdownV2 escaping, SSML preservation for TTS). The utils module contains genuinely reusable text-processing and time-slot helper functions. Dependencies are minimal (only HA core), and the project uses `uv` for Python management and CI with GitHub Actions (tests, HACS validation, hassfest). It targets Python 3.13+ and requires HA 2025.12.1 or newer, indicating an up-to-date stack. External integrations like Telegram, Alexa Media Player, or TTS must be installed separately; this component merely routes to them. The repository is actively maintained with frequent releases and a changelog, and it supports multiple languages (READMEs and translations).
Telemirror is a Telegram message mirroring application that uses the client API (Telethon) to forward messages between channels, chats, and topics in real-time. It supports one-to-one, many-to-one, and many-to-many mappings with per-direction filter pipelines. The system handles new messages, edits, deletions, and albums, and can operate with either an in-memory cache (backed by an LRU dict) or a PostgreSQL database for persisting message ID mappings. It includes a plugin-based filter system for message transformation (URL removal, keyword replacement, forward formatting, content skipping) and patches Telethon's sending functions to support topic replies. The application is designed to run as a long-lived service with a health endpoint for PaaS deployment (Heroku, Docker). The codebase is well-structured with clean separation of concerns, async-first design, and modern Python features (dataclasses, protocols, enums, pattern matching).
This repository implements a curated directory of Chinese-language Telegram channels, groups, and bots. It combines a Python-based data pipeline (scraping, filtering, categorization, and README generation) with a modern Astro static site that provides search, category browsing, and PWA features. The system ingests links from multiple sources (existing README, tg-nav, GitHub Issues), applies strict filtering rules (language, harmful keywords, subscriber thresholds), and outputs both a human-readable README and a structured JSON consumed by the frontend. The architecture is a hybrid of data engineering and web application, with the data pipeline being the core value proposition. The frontend is well-crafted with SEO, analytics, offline support, and a clean UI. The codebase demonstrates solid engineering practices, including reusable filtering logic, component-based UI, and automated build steps.
SmsForwarder is an Android application written in Kotlin that monitors SMS messages, incoming calls, and app notifications on a device and forwards them to multiple third-party channels such as DingTalk, WeChat Work, Feishu, Telegram, email, Bark, Webhook, and others. It also provides a local HTTP server for remote control (query/send SMS, call logs, contacts, battery status, location, and Wake-on-LAN) and an automation engine with configurable conditions (cron, battery, network, Bluetooth, location, screen state, etc.) and actions (forward, send SMS, trigger alarm, control frpc tunnels, etc.). The architecture follows a standard Android pattern with Room database, WorkManager for background tasks, XUI for UI components, and a fragment-based navigation system. The codebase is large and feature-rich, with over 15 sender channels and a flexible rule engine, but exhibits some technical debt such as deprecated API usage, hardcoded vendor-specific intents, and a few large monolithic fragments.
Jimmy is a command-line and terminal UI tool for converting notes from 50+ note-taking applications (Evernote, Obsidian, Joplin, Notion, Bear, etc.) into a unified Markdown format. It uses an intermediate representation (Notebook/Note/Resource/Tag objects) decoupled from input parsing and output writing, allowing clean extensibility. The architecture is a plugin-style converter framework with a rich set of format-specific parsers, markdown preprocessing libraries, and a resource deduplication system. The tool is distributed as standalone binaries bundling Pandoc and other dependencies. While the core abstractions are well-crafted, the vast majority of the codebase consists of tightly coupled format converters that are specific to each app's export schema, limiting general reuse. The project has extensive integration tests via a test data submodule, but many converters lack unit tests. Its requirement for Python 3.14 (a very recent version) and reliance on external binaries (Pandoc, one2html) introduce drift risks.
KIAUH (Klipper Installation And Update Helper) is a text-based user interface (TUI) and CLI tool for managing the Klipper 3D printer firmware ecosystem. It automates installation, update, removal, and backup of core components (Klipper, Moonraker, Mainsail, Fluidd, KlipperScreen, Crowsnest) and a wide range of community extensions (OctoPrint, Telegram Bot, Obico, Spoolman, etc.). The tool runs on Linux systems (primarily Raspberry Pi and similar SBCs) and handles systemd services, Python virtual environments, git repositories, nginx configuration, and system package management. Architecturally, KIAUH is a Python package with a modular design: a core framework provides menu navigation, logging, spinner animations, and a backend abstraction layer for command execution and filesystem operations. Components and extensions are implemented as classes inheriting from BaseExtension, each with install/update/remove methods. The tool supports multiple printer instances via an InstanceManager and uses a custom SimpleConfigParser for round-trip safe manipulation of Klipper-style configuration files. A headless CLI mode enables scripted, non-interactive operation. The codebase demonstrates solid engineering practices: dependency injection for testability, a plugin architecture for extensions, extensive test coverage (pytest with fake backends), and a well-organized package structure. Key reusable assets include the SimpleConfigParser (a standalone, comment-preserving config parser), the backend abstraction (enabling deterministic testing), and the BaseExtension plugin interface. While the tool is actively maintained and widely used, some areas show technical debt such as singleton proliferation, direct subprocess calls in places, and a Python 3.8 baseline that may limit future compatibility.
This repository is the `pyTelegramBotAPI` Python library, providing both synchronous (`TeleBot`) and asynchronous (`AsyncTeleBot`) implementations for building Telegram bots. It acts as a wrapper around the Telegram Bot API, handling all message types, inline queries, payments, webhooks, polling, and more. The library's architecture is layered: a user-facing bot class that exposes method calls to a core API helper module (`apihelper.py` / `asyncio_helper.py`), which performs HTTP requests to Telegram servers. Bot logic is structured via message handlers (decorator-based), custom filters, middleware hooks, and a state machine with pluggable storage backends (memory, Redis, pickle). Key entry points include `TeleBot` and `AsyncTeleBot` classes, with webhook support via `SyncWebhookListener` and `AsyncWebhookListener` in the `ext` module. The library relies on `requests` (sync) and `aiohttp` (async) for HTTP, with optional dependencies `redis`, `Pillow`, `fastapi`, `uvicorn`, and `watchdog`. It is extensively tested and documented, with over 50 examples covering typical bot patterns. While the codebase is mature and well-maintained, it exhibits some technical drift: duplicated sync/async helper modules, deprecated API parameters maintained for backward compatibility, and incomplete localization files. Overall, it is a solid, production-ready library for Telegram bot development.
This repository is an Android application that bridges device events (SMS, MMS, missed calls, battery changes, app notifications) to a Telegram bot for monitoring and remote control. It uses the Telegram Bot API to forward events and long-polls for incoming commands to send SMS, USSD, list/read/delete SMS, fetch logcat, and more. The architecture is a monolith with multiple background services, broadcast receivers, and job scheduler jobs, all within a single Android app. It uses MMKV for key-value storage, OkHttp for HTTP, Gson for serialization, and libsodium for encryption. The codebase is well-structured with reusable utility classes (e.g., custom Mustache template engine, Telegram API wrapper, encryption helpers) and has unit tests for several components. It supports multi-language, QR code configuration import, and carbon-copy forwarding to external services via HAR format.