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FlatBuffers instead of JSON (or Protocol Buffers)

FlatBuffers is an efficient cross platform serialization library for C++, Java, C#, Go, Python and JavaScript (C, PHP & Ruby in progress). It was originally created at Google for game development and other performance-critical applications.

Why use FlatBuffers?

  • Access to serialized data without parsing/unpacking - What sets FlatBuffers apart is that it represents hierarchical data in a flat binary buffer in such a way that it can still be accessed directly without parsing/unpacking, while also still supporting data structure evolution (forwards/backwards compatibility).
  • Memory efficiency and speed - The only memory needed to access your data is that of the buffer. It requires 0 additional allocations (in C++, other languages may vary). FlatBuffers is also very suitable for use with mmap (or streaming), requiring only part of the buffer to be in memory. Access is close to the speed of raw struct access with only one extra indirection (a kind of vtable) to allow for format evolution and optional fields. It is aimed at projects where spending time and space (many memory allocations) to be able to access or construct serialized data is undesirable, such as in games or any other performance sensitive applications. See the benchmarks for details.
  • Flexible - Optional fields means not only do you get great forwards and backwards compatibility (increasingly important for long-lived games: don't have to update all data with each new version!). It also means you have a lot of choice in what data you write and what data you don't, and how you design data structures.
  • Tiny code footprint - Small amounts of generated code, and just a single small header as the minimum dependency, which is very easy to integrate. Again, see the benchmark section for details.
  • Strongly typed - Errors happen at compile time rather than manually having to write repetitive and error prone run-time checks. Useful code can be generated for you.
  • Convenient to use - Generated C++ code allows for terse access & construction code. Then there's optional functionality for parsing schemas and JSON-like text representations at runtime efficiently if needed (faster and more memory efficient than other JSON parsers). Java and Go code supports object-reuse. C# has efficient struct based accessors.
  • Cross platform code with no dependencies - C++ code will work with any recent gcc/clang and VS2010. Comes with build files for the tests & samples (Android .mk files, and cmake for all other platforms).
Why not use Protocol Buffers, or .. ?

Protocol Buffers is indeed relatively similar to FlatBuffers, with the primary difference being that FlatBuffers does not need a parsing/ unpacking step to a secondary representation before you can access data, often coupled with per-object memory allocation. The code is an order of magnitude bigger, too. Protocol Buffers has neither optional text import/export nor schema language features like unions.

FlatBuffers on GitHub

Improving Facebook's performance on Android with FlatBuffers
FlatBuffers is a data format that removes the need for data transformation between storage and the UI. In adopting it, we have also driven additional architectural improvements in our app like Flat Models. The mutation extensions that we built on top of FlatBuffers allow us to track server data, mutations, and local state all in a single structure, which has allowed us to simplify our data model and expose a unified API to our UI components.

In last six months, we have transitioned most of Facebook on Android to use FlatBuffers as the storage format. Some performance improvement numbers include:

  • Story load time from disk cache is reduced from 35 ms to 4 ms per story.
  • Transient memory allocations are reduced by 75 percent.
  • Cold start time is improved by 10-15 percent.
  • We have reduced storage size by 15 percent.

FlatBuffersSwift on GitHub
Infrastructure for FlatBuffers, contains a reader and a builder


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Engineering the architecture behind Uber's new rider app

Not being held back by our extensive codebase and previous design choices gave us the freedom where we otherwise would have made compromises. The outcome is the sleek new app you see today, which implements a new mobile architecture across both iOS and Android. Read on to learn why we felt the need to create this new architecture pattern, called Riblets, and how it helps us reach our goals.

The platforms share:

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How to link to TestFlight App in iOS

There are two things you need to do. First, check to see if TestFlight is installed. Then create a new link to your app.

NSURL *customAppURL = [NSURL URLWithString:@"itms-beta://"];
if ([[UIApplication sharedApplication] canOpenURL:customAppURL]) {

    // TestFlight is installed

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Finally, if you are using iOS 9 (or later), you need to make an addition to your Info.plist to get the canOpenURL: method to work.

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Have you ever thought when writing or maintaining UI tests, there must be a better way?

Take a look at screenshot tests provided by Google Firebase and Facebook:

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Combining a strong colour with a blurred and translucent UINavigationBar in iOS 7.

// cheers to @stroughtonsmith for helping out with this one
UIColor *barColour = [UIColor colorWithRed:0.13f green:0.14f blue:0.15f alpha:1.00f];

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And also
myView.backgroundColor = [UIColor clearColor];
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Outline for this article:

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Hier kurz eine Übersicht und meine 5 cents:
Alpha Apps
Die chinesische App WeChat geht noch weiter: Neben einem Messenger, vergleichbar mit WhatsApp, bietet sie einen Lieferdienst à la Lieferando, die Möglichkeit etwa das eigene Konto zu checken (wie sonst bei der Bank-App) und gleichzeitig die Chance etwa Promis zu folgen, wie es Twitter bietet.

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