Simply LINQ your remote resources...

A dynamic expression builder that can be used to dynamically sort and/or filter LINQ/EF queries

A convention object to object or DataReader to object mapper in .NET Core 2.0.

Extensions to System.CodeAnalysis (Roslyn) and System.Reflection.

Create .NET DataTable using projections

Dino 🦕 A lightweight Domain Specific Language (DSL) for Entity Framework Core that allows you to write SQL-like queries as strings while maintaining the full power and safety of EF Core.

This Repository contains code implementation for all the Data Structures and Algorithms

Simple predicate string parser

The Expression Tree Toolkit is a collection of helper functions, extension methods, and ready-to-use classes. It simplifies common developer tasks manipulating expression trees.

Embeddable Query Language

Boolean Expression Truth Table Builder

High-performance .NET object-to-object mapping library with zero runtime reflection and zero extra allocations. Faster than AutoMapper, Mapster, and AgileMapper on every benchmark.

Wrapper around Expression Trees to provide statically typed experience and easier, less error prone enviroment for writing runtime compiled code

Exercício de Estruturas de Dados. Calculadora de expressões usando árvore de expressões.

Demo from 2022: a fluent LINQ builder serializes Where/OrderBy/Skip/Take expression trees, posts them to a generic ASP.NET Core controller, and rebuilds the query against EF Core + SQLite. Same query code runs from Blazor WebAssembly and a console app.

DynamicFilter allows to use essential linq filtering methods in web api apps

Create dynamic filters using a fluent syntax. based on expression trees

Simple C# code to ExpressionTree converter using Roslyn

simple AST implementation for a rules engine i developed for a job. only has the bare minimum because only that is needed in a couple places

A small compiler that translates human-intuitive mathematical intentions into executable expression trees built from a single binary operation: eml(x, y) = exp(x) − ln(y).