bwhiteley / jsonshootout Goto Github PK
View Code? Open in Web Editor NEWCompare several Swift JSON mappers.
Compare several Swift JSON mappers.
This comparaison are good, but you miss for me the better solution for converting JSON <-> Data Model in two way
You should add this solution to your test case : https://github.com/Hearst-DD/ObjectMapper
I may be misreading here, but in your section “That Thing on the Swift Blog,” you reference a Swift blog post from 2016. The concluding section (“Reflecting on Reflection”) of that post argues not against third-party frameworks, but against using reflection.
However, there’s a newer Swift blog post (well, I could have sworn I saw an official Swift blog post) that uses Swift’s JSONDecoder
, which uses reflection by default. I thought that article argued against third-party libraries, but now I just can't find it (perhaps it was not an Apple or Swift post. Here’s one). I tend to use Marshal, but I’m all for removing dependencies. I'll probably switch to JSONDecoder()
, but I was curious about its performance. it’s probably different when using reflection vs. explicit decoding.
What the title says. Made by thoughtbot. Find here: Argo
I noticed the test target runs without whole module optimization enabled (since it runs the test in debug mode). I wonder if it would be a good thing to include? Though not every developer builds with it enabled.
Hey there, thought you might be interested in this:
All the performance difference between Marshal and Mapper is because of this one commit: lyft/mapper@84b7fb4.
Basically they use their own value(forKeyPath:)
function so they don't get exceptions for type mismatches.
I'm not saying this is good or bad, just interesting.
Great comparison but you miss good reflection based object mapping library: https://github.com/evermeer/EVReflection
I see it in Pull requests.
Before I pull and run the tests myself, in the article you state:
"This graph shows time spent in each of the mappers as well as time spent in NSJSONSerialization for a reference."
However, I do not see this data point anywhere in the graph... Please help me if I'm too near-sighted to see it.
It would be great if you could include some test results for different sized JSON files. Mapping large JSON files is a very specific use case which I would argue is not that common. Most APIs typically will serve paginated data with 10-50 root level objects.
I think it would be useful to see how the parsers perform with varying sized data sets.
Full disclosure, I am the primary developer of ObjectMapper
.
Any plans to update this now that Xcode 9/Swift 4 are shipping? Curious to see if anything has changed.
There's a second pure-swift JSON parser which has been around for a while, which is my very own PMJSON. I'd love to see it included in the shootout.
What versions of Unbox, Marshall, and Argo were used in the analysis?
Any chance we could get Genome on here? I'm curious how it stacks up. 👍
How about adding this library, which is used often as well (900+ stars)
The current JSON sample uses Strings for every kind of value, for a more complete view, it may be worthwhile adding another JSON sample that covers more of what you would expect to see served from a REST API. Perhaps something like https://raw.githubusercontent.com/vdka/JSON/master/Tests/JSONTests/Fixtures/large.json.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.