AutoFilterer is a .NET library that automatically generates LINQ expressions from Data Transfer Objects (DTOs) for filtering, sorting, and pagination on IQueryable collections. It is designed to be compatible with OpenAPI 3.0 specifications, unlike oData or GraphQL. The core architecture revolves around filter DTOs that inherit from FilterBase or its derivatives (PaginationFilterBase, OrderableFilterBase). Properties in these DTOs are decorated with attributes (e.g., StringFilterOptions, OperatorComparison, CompareTo) or use special types (StringFilter, OperatorFilter<T>, Range<T>) to define filtering rules. The library builds expression trees at runtime and applies them via the ApplyFilter extension method. It also provides a Swagger integration package (AutoFilterer.Swagger) to expose filter parameters in Swagger UI, and a source generator (AutoFilterer.Generators) to automatically create filter DTOs from entity classes. The codebase is well-structured with clear separation of concerns: abstractions (IFilter, IFilterableType), attributes, types, extensions, and a dynamic filter variant. It includes comprehensive unit tests, benchmark tests, and a sandbox application demonstrating usage with a Northwind database. The library targets netstandard2.0, netstandard2.1, and net9.0, making it broadly compatible. While the core library is mature and actively maintained, some ancillary packages (e.g., Swagger integration) use slightly outdated dependencies (Swashbuckle 5.x), and the documentation has some TODO sections. Overall, it is a solid, reusable filtering framework with high craftsmanship in expression tree manipulation.
This is the swagger-codegen-generators repository, a Java library that provides code generation for client and server stubs from OpenAPI (formerly Swagger) specifications. It is not a standalone application but a library consumed by the swagger-codegen v3 tool (or used programmatically). The codebase implements a template-driven architecture where language-specific generators extend abstract base classes (e.g., AbstractJavaCodegen, AbstractTypeScriptClientCodegen) and use Handlebars/Mustache templates to produce output. It supports a wide range of languages including Java, C#, Go, Python, Ruby, Swift, TypeScript, Kotlin, Dart, PHP, Scala, R, and Node.js, with frameworks like Spring, JAX-RS, Micronaut, Vert.x, ASP.NET Core, and more. Key file patterns include feature interfaces for composable generator capabilities (e.g., BeanValidationFeatures, GzipFeatures), Handlebars helper lambdas for template logic, and schema handlers for composed schemas (allOf/oneOf/anyOf). The project has extensive test coverage with unit and integration tests for model and API generation. While the core architecture is solid, the base class DefaultCodegenConfig is monolithic and the hundreds of template files pose maintenance drift risks. The project is actively maintained with CI workflows, issue templates, and recent commits.
Knife4j is an enhanced Swagger/OpenAPI user interface and aggregation toolkit for the Java Spring ecosystem. In production it deploys as a set of Spring Boot auto-configuration starters: openapi2 (springfox), openapi3 (springdoc), aggregation from disk/cloud/Nacos/Eureka/Polaris sources, and Spring Cloud Gateway discovery, plus an optional standalone `knife4j-insight` server and multiple frontend UIs (Vue 2, Vue 3, React/Ant Design Pro). The core data flow is: a Spring Boot service exposes OpenAPI JSON via springdoc/springfox; Knife4j customizers and plugins enrich that JSON with API ordering, markdown docs, global parameters, and enhanced metadata; the frontend consumes the OpenAPI document and renders API lists, debug consoles, OAuth2 flows, and offline export pages. Aggregation starters fetch and merge specs from remote registries or local files, cache them in memory, and proxy or route requests to upstream services.
This repository contains a full-stack web application deployed on AWS ECS with a CI/CD pipeline. The frontend is a Vue.js application that retrieves product data from a backend Node.js/Express API. The backend scans a DynamoDB table and returns product information, including image URLs stored in S3. Infrastructure is provisioned via Terraform, including networking, ECS cluster/services, ECR repositories, IAM roles, CodePipeline/CodeBuild/CodeDeploy for Blue/Green deployments, autoscaling, and supporting resources (S3, DynamoDB, SNS). The architecture separates concerns with modular Terraform modules and implements production-grade practices like health checks, Swagger documentation, and stress testing.