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I’ve been drawing up an overview of pure vs GraphQL fragmentized [React] UI components, different ways to propagate data through the tree, and the associated maintenance/performance considerations.
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28.318"/></g><g class="L D"><path d="M4050.811 2810.91l480.077.351m-479.08-.807l478.965-.11m1.335 2.149c-.468 25.762-2.396 56.618-.738 83.326m-.843-85.113l-.033 85.816m.049-.217l-479.654 1.566m479.813-1.165l-479.557.084m.343-.993c-.05-26.435-1.088-57.865-2.042-85.652m2.097 85.948c-1.901-25.885-.69-50.796.134-86.447"/><path d="M4050.375 2851.123l-410.011-.633m411.721 2.887c-68.748.038-344.162-1.409-412.876-1.948"/></g><g transform="matrix(1 0 0 1 3743.810963 2913.560041)" class="B C E G"><text y="18" x="0">Because the data requirements are entirely</text><text y="43" x="0">colocated with the components, it is trivial</text><text y="68" x="0">to re-compose the tree without needing to</text><text y="93" x="0">understand all of the tree’s data requirements</text><text y="118" x="0">again and/or executing waterfall operations.</text></g><g class="D J"><path d="M3619.076 2421.196c-9.71 16.307-43.758 30.655-58.18 96.163s-23.471 247.617-28.352 296.886m85.649-393.742c-9.456 16.586-40.727 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2.997 28.396 5.151m-18.733-20.526c7.214 4.845 12.929 12.14 21.273 21.815m-20.47-24.09c5.947 5.954 10.363 13.358 17.929 22.803"/></g><text y="3184.035" x="291.263" class="B E G K">By: Eloy Duran - @alloy</text><path d="M527.631 3166.777l8.766-2.914m-7.17 2.112l9.267-3.7" stroke-width="2" class="D J"/><text y="121.121" font-size="28" x="2437.615" class="B E G">v1.0.0</text><text x="4927.274" y="3227.035" font-size="16" fill="#adb5bd" text-anchor="end" class="B E">Made with Excalidraw</text></svg>
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alloy commented Mar 11, 2021

Use the raw link to see a full-size version.

Here’s the original tweet, which is the best place to discuss (if you have a twitter account).

NOTE: GitHub does not render the embedded custom [hand-drawn] font. If you download the SVG and open locally you should get to see the original version.

@nodkz
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nodkz commented Apr 12, 2022

If somebody needs more context about fragment models - you may see brilliant Matt's talk https://www.youtube.com/watch?v=Vo8nqjiKI3A

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