Search Results for "random map generation"
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Showing 10 open source projects for "random map generation"
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1
INI
Package ini provides INI file read and write functionality in Go
...Wide-range support of variant formats includes but is not limited to my.cnf, .gitconfig, or even unparseable sections. Automatically convert to native types of Go at no cost. Let you focus on the code logic and no more tedious conversions. Map your configuration to a user-defined struct{} to be more object-oriented. Map back and save when you get the work done. Auto-type conversion, candidate value limitation, quick slice generation, in-fly data validation. More than you can ever imagine! Multiple configuration load policies, custom data validation rules, key name and value mappers. ... -
2
Lucky
A full-featured Crystal web framework that catches bugs for you
...Instead of finding bugs in QA or in production, Lucky is designed to catch as many bugs as possible at compile time. Lucky uses Action classes for handling HTTP requests and responses. The classes map the routes and parameters it handles to a response block. Lucky can generate these classes for you with ’lucky gen.action`. Using a class per action provides very solid automatic error detection, as well as the generation of routing, path, and link helpers and methods. -
3
Smallpond
A lightweight data processing framework built on DuckDB and 3FS
smallpond is a lightweight distributed data processing framework built by DeepSeek, designed to scale DuckDB workloads over clusters using their 3FS (Fire-Flyer File System) backend. The idea is to preserve DuckDB’s fast analytics engine but lift it from single-node to multi-node settings, giving you the ability to operate on large datasets (e.g. petabyte scale) without moving to a heavyweight system like Spark. Users write Python-like code (via DataFrame APIs or SQL strings) to express... -
4
json iterator
High-performance 100% compatible drop-in replacement of encoding/json
Add import "github.com/json-iterator/go" and replace json.Marshal with jsoniter.Marshal. Then the code should behave exactly the same, just much faster. Unlike easyjson or other json libaries, jsoniter does not rely on static code generation. Unmarshal, NewEncoder, NewDecoder they all works. Existing types implemented Marshaler or Unmarshaler interface will also work. Map with non-string key also work. Yes, everything just works. The default performance is already several times faster than the standard library. Use jsoniter.ConfigFastest, this will marshal the float with 6 digits precision (lossy), which is significantly faster. -
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5
SoundHelix
Versatile algorithmic random music generation software written in Java
SoundHelix is a free versatile Java framework for algorithmic random music composition. SoundHelix can generate random songs, play them (for example, on any number of MIDI devices or MIDI-capable software synthesizers) and is highly customizable using XML configuration. SoundHelix also allows writing the generated music as MIDI files. SoundHelix produces music that is actually enjoyable to listen to. -
6
Wombat
Cross platform gRPC client
Cross-platform gRPC client. -
7
XoshiroPRNG.Net
Xoshiro PRNG family implementation for .Net
The Xoshiro PRNG family contains algorithms that are both performant and passes statistical tests. This is a port of (some of the) Xoshiro PRNG algorithms into C#, written in such a way that they can act as System.Random drop-in replacement, or as fully-fledged standalone PRNG with additional methods. -
8
Happy Java Library
Multilock, Collections, Controllers, Delegates, Generators, Streams
Helps to develop and test event-based multi-threaded Java application. Because of method called as API-Evolution the Happy Java Library is fully downward compatible. The library contains following functionality: MultiLock, Parallel loops, Collections, Controllers, Generators, Delegates, Streams. -
9
RandomKit
Random data generation in Swift
RandomKit is a Swift framework that makes random data generation simple and easy. RandomKit is possibly also compatible with FreeBSD, Android, and Windows (under Cygwin) but has not been tested for those platforms. The RandomGenerator protocol defines basic methods for generating primitive values and randomizing a buffer. All provided types that conform to RandomGenerator have a static default value that can be passed as an inout argument to generation functions. ... -
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10
Accord.NET Framework
Scientific computing, machine learning and computer vision for .NET
The Accord.NET Framework provides machine learning, mathematics, statistics, computer vision, computer audition, and several scientific computing related methods and techniques to .NET. The project is compatible with the .NET Framework. NET Standard, .NET Core, and Mono.
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