Graphaello
fquery
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| Graphaello | fquery | |
|---|---|---|
| 3 | 5 | |
| 494 | 10 | |
| - | - | |
| 0.0 | 0.0 | |
| almost 2 years ago | over 2 years ago | |
| Swift | Python | |
| MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Graphaello
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SwiftGraphQL - A GraphQL client for Swift lovers.
Graphaello seemed like a viable option; it is type-safe, I can programmatically make selections, and it looks like it could scale well. However, Graphaello tightly binds me to my schema, and I can only use structures to represent my data.
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SwiftGraphQL – A GraphQL client that lets you forget about GraphQL
There's also:
- Relay-swift: A port of Relay to Swift - https://relay-tools.github.io/Relay.swift/docs/
- Graphaello: Inspired by Relay, but deviates a bit more from the patterns than Relay-swift - https://github.com/nerdsupremacist/Graphaello
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SwiftUI + GraphQL = 😍🚀🙌
Very nice writeup and tool. I've not been happy with Apollo, but using Graphaello on top of it makes for a nice interface.
fquery
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Solving the double (quintuple) declaration Problem in GraphQL Applications
Similar benefits without codegen (based on decorator magic) for a python based stack:
https://github.com/adsharma/fquery
* Use dataclasses for both database schema and the user facing operations
- Cut Out the Middle Tier: Generating JSON Directly from Postgres
- Against SQL
- Django for Startup Founders: A better software architecture for SaaS startups
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SwiftGraphQL – A GraphQL client that lets you forget about GraphQL
Re: Conways law at Facebook
I was at Facebook when GraphQL was invented, maintaining a backend storage service where a core assumption was that storage should be reorganized based on access patterns and that predicates should be pushed down to storage where they can be executed more efficiently.
GraphQL was hard to push predicates down, because you don't know which of the edges were written in PHP.
My response was fquery[1], which is like what's being discussed here but with python as the source language instead of swift and amenable to preserving the largest possible query structure for backend optimizers, including SQL optimizers.
It has some early demos converting a GraphQL/fquery into SQL where possible. It should be possible to add enough metadata to fquery to identify if an edge is non-trivial (calls into another microservice) or trivial (can be optimized to a storage backend or SQL).
[1] https://github.com/adsharma/fquery