Search Results for "collection"

...With the Algorithms package’s initial set of sequence and collection operations, you can cycle over a collection’s elements, find combinations and permutations, create a random sample, and more. One inclusion is a pair of chunked methods, each of which break a collection into consecutive subsequences. One version tests adjacent elements to find the breaking point between chunks, you can use it to quickly separate an array into ascending runs.

The master branch follows the latest currently released version of Swift. If you need an earlier version for an older version of Swift, you can specify its version in your Podfile or use the code on the branch for that version. Older branches are unsupported. Swift Package Manager uses debug configuration for debug Xcode build, that may result in significant (up to x10000) worse performance. Performance characteristic is different in Release build. XCFrameworks require Xcode 11 or later and...

Swift Algorithm Club is a project that implements a broad collection of algorithms and data structures in the Swift programming language, with clear commentary and educational intent. Its purpose is not primarily to be a utility library, but rather to teach the how and why behind algorithms—readers can study implementations, complexity, and design choices in a Swift context. The repository includes common classic algorithms (sorting, searching, trees, graphs, dynamic programming, etc.) and structures (queues, heaps, tries, balanced trees) along with writeups explaining them. ...

A fast and flexible O(n) difference algorithm framework for Swift collection. The algorithm is optimized based on the Paul Heckel’s algorithm. This is a diffing algorithm developed for Carbon, works stand alone. The algorithm optimized based on the Paul Heckel’s algorithm. See also his paper A technique for isolating differences between files released in 1978. It allows all kind of diffs to be calculated in linear time O(n).

...The first thing sounds interesting but perhaps only abstractly useful, and the other thing is a very concretely useful thing based off the first thing. It can help you build a substantially better user experience if you have table/collection views with dynamic content in your app. There is some non-trivial index math inside of this diff algorithm that is easy to screw up. Dwifft has 100% test coverage on all of its core algorithms.

Cosmos (by OpenGenus Foundation) is your personal offline collection of every algorithm and data structure one will ever encounter and use in a lifetime. This provides solutions in various languages spanning C, C++, Java, JavaScript, Swift, Python, Go and others. This work is maintained by a community of hundreds of people and is a massive collaborative effort to bring the readily available coding knowledge offline.