Onedump is a Go-based CLI tool for database administration, specializing in backup, restore, and migration workflows. It supports MySQL (with a zero-dependency native dumper and mysqldump) and PostgreSQL (via pg_dump), and can persist backups to local files, AWS S3, Google Drive, Dropbox, or SFTP endpoints. The architecture follows a clean pipeline pattern: YAML configuration drives concurrent job execution, each job uses a dumper interface to stream database content through gzip compression and fan-out to multiple storage backends. Beyond core backup, it includes advanced features: MySQL binlog streaming to S3 with checksum-based deduplication, point-in-time restore via binlog replay, a MySQL slow query log parser with query masking and deduplication, and a resumable/concurrent SFTP file transfer utility with exponential backoff. The codebase is well-structured, heavily tested, and uses modern Go idioms, making it suitable as a reference for building database-adjacent infrastructure tooling.
Plane is an open-source, self-hosted project management platform that provides issue tracking, sprint planning (cycles), modules, pages (wiki), views, analytics, and real-time collaborative editing. The repository is a monorepo containing a Django REST API backend with Celery workers, multiple React frontends (main web app, public space app, admin panel), and a Hocuspocus-based live collaboration server. The architecture follows a service-oriented pattern with shared packages for UI components, editor extensions, types, utilities, and state management via MobX. The codebase demonstrates strong engineering practices with a rich filter system, extensible permission model, and a clean exporter pattern, though it shows signs of ongoing migration from Next.js to React Router and some code duplication across apps.
Sequelize is a mature, promise-based Node.js ORM supporting PostgreSQL, MySQL, MariaDB, SQLite, Microsoft SQL Server, DB2, IBM i, Oracle, and Snowflake. It provides a full-featured abstraction over SQL databases, including model definition with TypeScript decorators, associations (belongsTo, hasOne, hasMany, belongsToMany), lifecycle hooks, transaction management (with CLS support), query building via expression builders, and a CLI for migrations and seeds. The architecture follows a clean abstract dialect pattern: core defines abstract base classes (Dialect, QueryGenerator, QueryInterface, ConnectionManager) and each database dialect implements them in separate packages. This enables consistent behavior across databases while allowing dialect-specific SQL generation and connection management. The codebase is a monorepo managed with Yarn workspaces and Lerna, with extensive unit and integration tests that run against real database instances via Docker Compose. Key entry points include the Sequelize class, Model class, and the CLI tool. Data flows from application code through model methods (e.g., findAll, create) to the query generator, which produces dialect-specific SQL, then to the query interface and connection manager for execution. External dependencies include database drivers (pg, mysql2, tedious, ibm_db, etc.), validator.js, and utility libraries. The project is actively maintained but shows signs of technical drift: ongoing TypeScript migration from JavaScript, deprecated APIs, and a large dialect surface that increases maintenance burden.
CloudNativePG is a Kubernetes operator for managing PostgreSQL databases in production. It automates deployment, failover, scaling, backups, upgrades, and connection pooling (PgBouncer) through custom Kubernetes resources (CRDs) and reconciliation loops. The operator consists of two binaries: a manager that runs inside pods to manage PostgreSQL instances, and a kubectl plugin for administrative commands. The architecture is modular with separate reconcilers for clusters, instances, backups, roles, tablespaces, and replication slots. It includes a plugin system (CNPG-I) for extensibility via gRPC, a web server for health probes and metrics, and a Prometheus exporter for monitoring. The codebase is written in a non-standard Go dialect (using URL-like import paths, func keyword, and var type declarations), which may indicate a custom transpiler or DSL. Despite this, the project is production-grade with extensive unit and end-to-end tests, active maintenance, and support for multiple Kubernetes distributions (kind, k3d, OpenShift).
This repository is a comprehensive collection of over 1200 standalone Bash scripts for DevOps automation, cloud infrastructure management, CI/CD pipeline orchestration, and system administration. It is not a single application but a modular toolbox designed to be used interactively or integrated into CI workflows. The architecture is decentralized: each script is self-contained, sourcing shared libraries from the `lib/` directory for common functions like error handling, API authentication, and OS detection. Key entry points include the top-level `Makefile` for bootstrapping, `lib/utils.sh` as the core utility library, and numerous API wrapper scripts (e.g., `github_api.sh`, `aws_foreach_profile.sh`) that provide consistent patterns for interacting with external services. The primary data flows involve querying cloud provider APIs (AWS, GCP, Cloudflare), managing CI/CD platforms (Jenkins, BuildKite, GitHub Actions), manipulating Git repositories, and performing system tasks like disk benchmarking or SSL certificate verification. External dependencies are extensive but well-managed: the scripts assume the presence of `curl`, `jq`, and platform-specific CLIs (`aws`, `gcloud`, `kubectl`, `gh`), with many install scripts provided to bootstrap these tools. The codebase demonstrates high craftsmanship with consistent error handling (`set -euo pipefail`), input validation, and cross-platform compatibility guards. While some scripts are tailored to the author's personal environment, the core patterns and libraries are designed for reuse across projects.
dataset is a lightweight Python library that simplifies database operations by providing a dict-like interface on top of SQLAlchemy. It automatically creates tables and columns on insert, supports CRUD operations, transactions, and chunked bulk inserts/updates. The library is designed for small to medium-scale data tasks where full ORM overhead is unnecessary. It supports SQLite, PostgreSQL, and MySQL, and is fully type-annotated with mypy strict compliance. The codebase is well-organized into core modules (database, table, types, util, chunked) and has thorough test coverage across all supported backends. While the core abstraction is thin (intentionally), the implementation demonstrates solid engineering discipline with clean APIs, thread safety considerations, and proper handling of SQLAlchemy 2.x quirks.
This repository provides a production-ready, full-stack Retrieval-Augmented Generation (RAG) chat application built with Python FastAPI and React TypeScript. It demonstrates how to use Azure OpenAI (or OpenAI.com, or Ollama) to answer questions about data stored in Azure Database for PostgreSQL with the pgvector extension. The system supports both a simple RAG flow (embedding + direct search) and an advanced flow that uses OpenAI function calling to rewrite queries and apply column filters (brand, price). It features hybrid search combining full-text search and vector similarity via Reciprocal Rank Fusion. The backend is a monolith serving API endpoints and a React frontend, designed for deployment to Azure Container Apps using the Azure Developer CLI. The codebase includes comprehensive unit tests, end-to-end tests with Playwright, evaluation scripts, load testing with locust, and safety evaluation using Azure AI Red Teaming. The architecture is cleanly separated into reusable modules, making it a solid reference architecture for building RAG applications on Azure.
junixsocket is a Java/JNI library providing Unix domain socket (AF_UNIX) support and other advanced socket families (AF_TIPC, AF_VSOCK, AF_SYSTEM) to Java applications. It extends standard Java Socket and NIO APIs with features like ancillary data (file descriptor passing), peer credentials, abstract namespace, SSL/TLS, RMI, and shared memory. The architecture is modular with core modules (junixsocket-common, junixsocket-native) and protocol-specific extensions. Key entry points include factory methods in AFUNIXSocket/AFUNIXServerSocket, SSLContextBuilder, and AFUNIXNaming. Data flows involve JNI-mediated socket operations for IPC, with advanced features using native ancillary messaging. External dependencies include optional integrations (MySQL Connector/J, Jetty, Netty) and platform-specific toolchains for native builds.
Commonly is an open-source multi-agent collaboration platform where humans and AI agents work together in shared workspaces called 'pods'. The system provides real-time messaging, task management, agent runtime (native, hosted, or bring-your-own), marketplace for agent skills, and integrations with external chat platforms like Discord, Slack, Telegram, and GroupMe. The architecture is a full-stack monolith with separate external agent bridge services and a Cloudflare Workers-based agent runtime. The backend (Node.js/Express) uses a dual-database design (MongoDB for primary data, PostgreSQL for messages/tasks) with automatic sync. The frontend is a React SPA with a v2 design system. The CLI allows local agents to participate via device-code auth and polling. The MCP server provides standard tools for agents to interact with the platform. The codebase is well-structured with extensive test coverage (unit, integration, E2E), Architecture Decision Records (ADRs), and reusable packages for types, integration SDK, and MCP tools. Notable craftsmanship includes pluggable storage drivers, deterministic agent wake targeting, and a test utility that replicates the production PostgreSQL schema to catch DDL drift.
This repository is a production full-stack application for browsing, searching, downloading, and publishing galgame (visual novel) sticker packs. It is a pnpm monorepo containing a Nuxt 4 SSR frontend (`apps/web`) and a Go Fiber v3 API (`apps/api`) backed by PostgreSQL. The API exposes both internal service endpoints and a public read-only OpenAPI "face" for sticker content, while integrating with external ecosystem services: an OAuth 2.0 identity provider (PKCE, httpOnly session cookies, BFF pattern), a centralized content-addressed image service, a catalog service for games/characters, and a community service for comments, notifications, and reactions. Deployment is Docker images to GHCR via Dokploy, with versioned SQL migrations and GitHub Actions CI building all images on push to the `svelte-kit` branch. The backend is well-layered: handlers own HTTP concerns, services contain business logic without importing Fiber, repositories use GORM, and repeated cross-service communication is isolated in reusable `pkg` clients. Noteworthy engineering includes batch hydration for pack covers/tags/authors, trigram GIN search over flattened multilingual text, cursor pagination for notifications, and RFC 9457 problem-detail error responses in the public API. The frontend is organized into feature modules and includes a race-condition-safe catalog picker, OAuth PKCE utilities, and server-side OG image generation. The codebase is maintained and technically current, though some operational risks remain: dual error dialects between internal and public APIs, silent degradation when optional upstream services are down, and a few hardcoded backfill mappings in one-time scripts.
ToolJet is a comprehensive low-code/no-code application development platform designed for building internal tools, workflows, and AI agents. The system features a visual drag-and-drop editor (AppBuilder) that allows users to construct UIs using a library of widgets, connect to diverse data sources via a plugin architecture, and manage application logic through a backend NestJS service. It supports multi-tenancy, version control (Git), and enterprise-grade security features like SSO and RBAC. The architecture is a monorepo with a React-based frontend and a NestJS-based backend, utilizing PostgreSQL for persistence and Redis for caching.
Mail-Archiver is a production-grade ASP.NET Core 10 web application for archiving emails from IMAP, Microsoft 365 (Graph), and local imports (MBOX, EML). It provides a full MVC UI for searching, viewing, exporting, restoring, and managing archived emails, alongside a read-only REST API (v1) and a Model Context Protocol (MCP) server for AI agent integration. The system features background job processing for sync, batch operations, deduplication, retention policies, and audit exports, all backed by PostgreSQL with full-text search. Authentication supports local password (PBKDF2), OpenID Connect, and API keys, with two-factor authentication and role-based access control. The codebase is well-structured with clear separation of concerns: provider-specific services (IMAP, Graph, Mbox), shared utilities, and a core service layer. Extensive unit and integration tests (xUnit) cover critical paths, and Docker Compose provides a reproducible test environment. While some technical debt exists (raw SQL in core services, in-memory job tracking, German comments in places), the overall architecture is solid and the reusable components (static helpers, deduplication strategies, background job patterns) demonstrate high craftsmanship.
Liberapay is a production web application for recurrent monetary donations, operating as a non-profit platform. It allows donors to set up weekly, monthly, or yearly contributions to creators, teams, and organizations. The architecture is a monolithic Python web application built on the custom Aspen/Pando framework (a fork of Aspen), using PostgreSQL for persistence, Jinja2 for server-side rendering, and a mix of Stripe and PayPal for payment processing. Key entry points include the homepage (`www/index.html.spt`), user profile pages (`www/%username/index.html.spt`), donation management (`www/%username/giving/`), payment flows (`www/%username/giving/pay/stripe/%payin_id.spt`), and admin dashboards (`www/admin/`). Data flows involve user authentication via sessions and OAuth, tip creation and scheduling, payin execution through Stripe/PayPal, weekly payday settlement, and email notifications. External dependencies include Stripe, PayPal, Amazon SES (email), Sentry (error tracking), S3 (file storage), and multiple OAuth providers (GitHub, Twitter, Mastodon, etc.). The codebase is well-structured with reusable modules for payment prospect calculation, encryption, content security policy, currency handling, and OAuth abstraction, though it carries technical debt from a custom framework and aging dependencies.
Ibis is a federated wiki platform built entirely in Rust, enabling users to create, edit, and discuss articles across ActivityPub-enabled instances. The application follows a full-stack architecture with a Leptos-based frontend (compiled to WASM for client-side hydration) and an Axum backend serving both the API and server-side rendering. PostgreSQL is used as the database via Diesel ORM, and federation is implemented using the `activitypub-federation` crate, allowing articles, edits, comments, and user profiles to be synchronized between independent instances. The codebase is organized as a Cargo workspace with separate crates for backend, frontend, federation logic, database access, API client, markdown rendering, and reusable UI components. Key features include markdown-based article editing with custom extensions (LaTeX, table of contents, article links), edit conflict resolution via three-way merge, user authentication (JWT, OAuth, email verification), in-app and email notifications, and Wikipedia article import. The frontend uses Tailwind CSS with DaisyUI components and supports internationalization via `leptos-fluent`. Ibis demonstrates strong software engineering practices: modular crate structure, comprehensive integration tests with multi-instance federation scenarios, CI pipeline with formatting and linting, and Docker-based deployment. While the codebase is actively maintained and well-architected, it contains some production `expect` calls and relies on beta versions of key dependencies, which introduces minor risk. Overall, it is a polished, production-ready federated application with reusable patterns in frontend components, database abstractions, and ActivityPub object handling.
This is a NestJS boilerplate for building RESTful APIs with TypeScript, PostgreSQL, TypeORM, and modern DevOps practices. The system provides a modular backend architecture with authentication (JWT), user management, post management, email verification via BullMQ queues, health checks, Swagger API documentation, and comprehensive testing setup. It follows NestJS best practices with clear separation of concerns across modules for auth, users, posts, health, and background jobs. Key features include cursor-based and offset-based pagination, internationalization (i18n), Redis caching, security headers via Helmet, and environment-based configuration management. The codebase demonstrates strong engineering practices with reusable utilities for password handling, configuration validation, and sophisticated cursor pagination that could be extracted to other projects with minimal modification.
Gogs is a self-hosted Git service written in Go, providing a full-featured platform for hosting Git repositories with issue tracking, pull requests, wiki, webhooks, and Git LFS support. The backend is a monolithic Go application using a dual web framework (Macaron and Flamego) and dual ORM (XORM and GORM) during an ongoing migration. The frontend is a hybrid of legacy server-rendered templates and a modern React SPA built with TanStack Router, Radix UI, and Tailwind CSS. The system supports multiple authentication backends (LDAP, SMTP, PAM, GitHub OAuth), SSH and HTTP Git protocols, and extensive REST API. It is deployed via Docker with s6 supervisor and backup rotation scripts. The codebase demonstrates strong engineering practices with well-structured utility packages, security-conscious input validation, and comprehensive test coverage using golden files and mock stores. However, it carries technical debt from the framework migration, vendored outdated frontend plugins (CodeMirror 5.17.0), and a monolithic legacy JavaScript file.
porsager/postgres is a PostgreSQL client library for Node.js, Deno, and Cloudflare Workers. It provides a full-featured, performant interface to PostgreSQL using tagged template literals for safe, parameterized queries. The library implements the PostgreSQL wire protocol from scratch with zero runtime dependencies, supporting advanced features like connection pooling, prepared statements, cursors, COPY streams, logical replication, large objects, and custom type mapping. The architecture is a factory function that returns a `sql` tagged template function, which lazily connects to the database and pipelines queries over persistent connections. The codebase is well-structured across `src/` with separate modules for connection management, query execution, protocol message building, type serialization/parsing, and error handling. It also includes transpiled builds for CommonJS, Deno, and Cloudflare Workers, each with platform-specific polyfills. The library is actively maintained, has extensive test coverage, and is published under a public domain license.
This repository is the personal blog and knowledge base of digoal, a prominent PostgreSQL DBA and database expert. It contains over a decade of blog posts (2010–2026) covering PostgreSQL internals, performance tuning, database architecture, and related topics, along with a large collection of images, PDFs, and other attachments. The blog is organized by year and month, with each post as a markdown file. The repository also includes a 'skills' directory that defines reusable AI agent skill definitions (SKILL.md files) for various tasks such as fact-checking, stock prediction, bug hunting, and course writing. These skills are structured with agent prompts, reference materials, and supporting scripts, making them extractable and reusable in AI-assisted workflows. The repo is actively maintained and serves as both a reference for database professionals and a library of AI agent capabilities.
DefectDojo is a Django-based vulnerability management platform that aggregates, deduplicates, and tracks security findings from over 200 security scanners (SAST, DAST, SCA, container, cloud, infrastructure). The system ingests scan reports via a standardized parser interface, normalizes findings into a core data model (Product, Engagement, Test, Finding, Location), and provides advanced features such as risk-based prioritization, SLA management, JIRA/GitHub integration, notifications (Slack, Teams, email), role-based access control, and customizable reporting. The architecture is a Django monolith with a REST API (v2 using DRF, v3 using Ninja in alpha), Celery for async task processing (imports, deduplication, JIRA sync, SLA expiry), PostgreSQL with full-text search and audit logging via pghistory, and a containerized deployment with Docker Compose. Key entry points include the parser factory (dojo/tools/factory.py), API viewsets, and management commands. The codebase demonstrates strong software engineering patterns such as a modular parser contract, an abstract location manager for feature-flag-driven migration, and an authorization filter registry, but carries technical debt from a dual API surface and an incomplete migration to a new location model.
This repository provides a Docker-based tool for automatically discovering and backing up databases running in Docker containers. The core logic resides in a single Python script (`db-auto-backup.py`) that uses the Docker SDK to list running containers, identifies database containers by image name (PostgreSQL, MySQL/MariaDB, Redis), and executes native backup commands (pg_dumpall, mysqldump, redis-cli SAVE). Backups are written to a configurable directory with optional compression (gzip, lzma, bz2, zstd) and can be scheduled via cron expressions using the pycron library. The tool also supports success hooks (e.g., healthchecks.io, Uptime Kuma) and environment variable configuration. It is designed to run as a standalone Docker container with access to the Docker socket, making it a lightweight, self-contained backup solution for Docker hosts. The codebase is well-structured with type hints, linting, and a comprehensive test suite that validates backup generation and compression across multiple database types.