119 Repositories
Swift neural-network Libraries
Swift Paging is a framework that helps you load and display pages of data from a larger dataset from local storage or over network.
Swift Paging is a framework that helps you load and display pages of data from a larger dataset from local storage or over network. This approach allows your app to use both network bandwidth and system resources more efficiently. It's built on top of Combine, allowing you to harness its full power, handle errors easily, etc.
A generic network layer written in swift
SwiftyNet 1.0.0 A generic network layer written in swift. you can use it as an abstraction layer above Alamofire with generic returned types. Installa
This package is meant to make http request of an easy way inspiren in the architecture of Moya package
NetworkAgent This package is meant to make http request of an easy way inspiren in the architecture of Moya package. This package is 100% free of depe
MLKit is a simple machine learning framework written in Swift.
MLKit (a.k.a Machine Learning Kit) π€ MLKit is a simple machine learning framework written in Swift. Currently MLKit features machine learning algorit
BrainCore is a simple but fast neural network framework written in Swift.
BrainCore is a simple but fast neural network framework written in Swift. It uses Metal which makes it screamin' fast. If you want to see it
Stub your network requests easily! Test your apps with fake network data and custom response time, response code and headers!
OHHTTPStubs OHHTTPStubs is a library designed to stub your network requests very easily. It can help you: test your apps with fake network data (stubb
Network testing for Swift
DVR DVR is a simple Swift framework for making fake NSURLSession requests for iOS, watchOS, and OS X based on VCR. Easy dependency injection is the ma
iOS network debugging, like a wizard π§ββοΈ
Start debugging iOS network calls like a wizard, without extra code! Wormholy makes debugging quick and reliable. What you can do: No code to write an
Lightweight network abstraction layer, written on top of Alamofire
TRON is a lightweight network abstraction layer, built on top of Alamofire. It can be used to dramatically simplify interacting with RESTful JSON web-
Elegant network abstraction layer in Swift.
Elegant network abstraction layer in Swift. δΈζ Design Features Requirements Communication Installation Usage Base Usage - Target - Request - Download
π A Swift HTTP / HTTPS networking library just incidentally execute on machines
Thus, programs must be written for people to read, and only incidentally for machines to execute. Harold Abelson, "Structure and Interpretation of Com
A type-safe, high-level networking solution for Swift apps
What Type-safe network calls made easy Netswift offers an easy way to perform network calls in a structured and type-safe way. Why Networking in Swift
A lightweight, one line setup, iOS / OSX network debugging library! π¦
Netfox provides a quick look on all executed network requests performed by your iOS or OSX app. It grabs all requests - of course yours, requests from
A toolkit for Network Extension Framework
NEKit NEKit is deprecated. It should still work but I'm not intent on maintaining it anymore. It has many flaws and needs a revamp to be a high-qualit
Network abstraction layer written in Swift.
Moya 14.0.0 A Chinese version of this document can be found here. You're a smart developer. You probably use Alamofire to abstract away access to URLS
Dratini is a neat network abstraction layer.
Dratini Dratini is a neat network abstraction layer. If you are looking for a solution to make your network layer neat, Dratini is your choice. Dratin
π Makes Internet connectivity detection more robust by detecting Wi-Fi networks without Internet access.
Connectivity is a wrapper for Apple's Reachability providing a reliable measure of whether Internet connectivity is available where Reachability alone
Telegram Bot Framework written in Swift 5.1 with SwiftNIO network framework
Telegrammer is open-source framework for Telegram Bots developers. It was built on top of Apple/SwiftNIO
Accelerated tensor operations and dynamic neural networks based on reverse mode automatic differentiation for every device that can run Swift - from watchOS to Linux
DL4S provides a high-level API for many accelerated operations common in neural networks and deep learning. It furthermore has automatic differentiati