30 open-source projects similar to chancejs/chancejs, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best Chancejs alternative.
gofakeit is a Go library for creating realistic synthetic datasets and populating Go structs with mock information. It functions as a deterministic data generator, allowing for seedable random number generation to ensure reproducible datasets for software testing. The project distinguishes itself by providing a mock data API server that exposes generation functions as HTTP endpoints and a synthetic dataset exporter for producing files in CSV, JSON, and XML formats. It also includes a command-line interface for generating mock data directly from the terminal. The library covers a wide array o
Faker is a PHP library for creating realistic synthetic data used for testing, prototyping, and populating database entities. It serves as a test data generator and localized mocking tool capable of producing synthetic names, addresses, and identifiers specific to various countries and languages. The library provides mechanisms to ensure data consistency and quality, including deterministic seeding to produce identical data sequences across executions and stateful uniqueness tracking to prevent duplicate values. It also supports probability-weighted optionality to simulate missing data and cu
Factory Boy is a dynamic test fixture framework and data generation tool for Python. It serves as a replacement for static fixtures by providing a system to create complex Python objects and database models through programmable blueprints. The project differentiates itself by offering specialized integration with Object Relational Mappers to manage persistence within database sessions. It enables the creation of complex object hierarchies using sub-factories and recursive composition to resolve dependent related objects. The framework provides capabilities for synthesizing realistic random d
Mimesis is a Python synthetic data generator used to create realistic fake datasets and mock data for software testing and development. It functions as a schema-based dataset generator capable of producing structured records and relational datasets, while also serving as a production data anonymizer to replace sensitive information with synthetic values. The library distinguishes itself through comprehensive multilingual support, allowing for the generation of locale-specific information to simulate regional user profiles. It ensures reproducibility through deterministic data generation using
Faker is a PHP fake data generator and testing utility used to produce realistic randomized values for populating databases and test applications. It serves as a localization library that generates data tailored to specific languages and regional formats, providing a framework for extending data generation through custom classes and domain-specific formatters. The library ensures repeatability in testing environments through deterministic random seeding. It includes mechanisms to control output quality, such as enforcing value uniqueness and simulating missing data by occasionally producing n
fast-check is a property-based testing framework and random data generator designed to verify software invariants by producing a wide range of randomized input data. It functions as a test data fuzzer that executes predicates against high volumes of random inputs to uncover edge cases and critical bugs. The project is distinguished by its ability to perform input-shrinking searches, which reduce complex failing inputs to their simplest form to isolate the exact cause of failure. It provides deterministic seed replay to exactly reproduce specific test failures and includes a concurrency testin
Alice is a PHP test data generator and fixture library used to automate the creation of large sets of fake objects and entities. It functions as an object hydrator and random data provider, allowing users to define the structure and attributes of dummy test data in markup or arrays to simulate specific application states. The library distinguishes itself through a template-based system that supports fixture inheritance to reduce data duplication. It utilizes a flexible instantiation model that allows for custom factory integration, method invocation, and property hydration via reflection or c
Simplex-noise.js is a mathematical noise generator and graphics library implemented in TypeScript. It computes smooth pseudo-random values across two, three, and four dimensions, producing organic patterns and spatial effects without relying on static image assets. The library operates through a stateless mathematical engine that uses precomputed coordinate lookup tables and typed array buffers to manage numeric data. It supports deterministic seed injection, accepting custom pseudo-random number generator functions to initialize permutation tables with reproducible values for repeatable outp
xtensor is a C++ multidimensional array library for numerical computing that provides N-dimensional containers with an interface mirroring the NumPy API. It utilizes a lazy evaluation expression engine to defer numerical computations until assignment, which minimizes memory allocations and intermediate copies. The library features a foreign memory array adaptor that allows it to wrap external buffers, such as NumPy arrays, to perform numerical operations in-place without duplicating data. It further optimizes performance through lazy broadcasting and a system that manages the lifetime of temp
collect.js is a dependency-free JavaScript library that provides a fluent, chainable interface for manipulating arrays and objects. It mirrors the Laravel Collection API, offering a consistent set of methods for data transformation across JavaScript and Laravel backend environments. The library stores collection data as plain arrays internally and supports fluent method chaining, where each method returns a new collection instance. The library distinguishes itself by closely replicating the Laravel Collection API in JavaScript, mapping each PHP method to an equivalent JavaScript implementatio
money.js is a tiny (1kb) javascript currency conversion library, for web & nodeJS. (MOVED)
A lightweight JavaScript library for number, money and currency formatting. (MOVED)
The RAW Complex.js is a complex numbers library written in JavaScript
The RAW JavaScript library to work with polynomials
The RAW rational numbers library written in JavaScript
Numeral-js is a JavaScript number formatting library used to convert raw numeric values into human-readable strings for currencies, percentages, and abbreviations. It includes a numeric string parser to extract raw values from formatted strings by removing symbols and delimiters. The library provides locale-aware formatting to adjust decimal separators and currency symbols based on regional language settings. It also features a data size converter that transforms byte values into readable measurements using base-1000 or base-1024 standards. The system supports the registration of custom form
Odometer is a JavaScript number animation library and frontend UI tool designed to create fluid counting effects. It functions as a numerical transition component that updates numbers on a page using animated rolling or sliding transitions. The library focuses on numerical value animation and data transition effects, allowing users to transition smoothly between two numerical values. This is used for updating metrics and key performance indicators in dynamic dashboard visualizations to avoid abrupt jumps in data displays.
ZIO is a functional effect system for the JVM that models asynchronous and concurrent programs as pure, composable values with typed error handling and dependency injection. Its core identity is built on fiber-based concurrency, where lightweight, non-blocking fibers execute millions of concurrent tasks with structured lifecycle management, and a dual-channel error model that separates expected business failures from unexpected system defects at compile time. The system provides effect-typed dependency injection through a layer-based dependency graph, pull-based reactive stream processing with
VisiData is a terminal-based interactive data analysis tool and browser designed for exploring, filtering, and sorting large tabular datasets. It functions as a structured data inspector that loads and flattens complex formats like JSON, XML, and PCAP into interactive sheets, as well as a terminal file manager for navigating directories and performing staged filesystem operations. The project distinguishes itself by rendering data visualizations, such as scatter plots and histograms, directly in the terminal using Unicode Braille characters. It provides a Python-based data wrangling environme
Orange3 is a visual data mining platform that provides an interactive canvas for building data analysis workflows without writing code. At its core, it offers a widget-based visual programming environment where users connect configurable components to perform data preprocessing, machine learning model training, statistical evaluation, and interactive visualization. The platform is built on NumPy-backed data tables with domain descriptors that define variable names, types, and roles, and includes a lazy SQL query proxy for working with database tables without loading all data into memory. The
Faker is a Python library designed to generate realistic synthetic data for software testing, database prototyping, and privacy-preserving anonymization. It provides a comprehensive suite of tools to create diverse information types, including personal identities, financial records, geographic locations, and technical system metadata, allowing developers to populate environments with mock data that mimics real-world structures. The library is built on a modular provider architecture that supports dynamic method dispatch, enabling users to extend functionality by registering custom data genera
This project is a scientific computing framework for the .NET ecosystem, providing a comprehensive suite of libraries for numerical analysis, statistics, and mathematical optimization. It serves as a foundational toolkit for developing applications in machine learning, digital signal processing, and computer vision. The framework provides specialized toolkits for training and deploying predictive models, including neural networks, support vector machines, and decision trees. It further distinguishes itself with deep integrations for real-time visual analysis, such as object tracking and facia
Dask is a parallel computing framework and distributed task scheduler designed to scale Python data science workflows from single machines to large clusters. It functions as a cluster resource manager that orchestrates computational logic by representing tasks and their dependencies as directed acyclic graphs. This architecture allows the system to automate the distribution of workloads across available hardware while managing complex execution requirements. The project distinguishes itself through a lazy evaluation engine that defers data operations until they are explicitly requested, enabl
DataFrame is a C++ tabular data library and manipulation engine designed for managing heterogeneous data in contiguous memory. It functions as a statistical analysis framework and time series analysis toolkit, providing the means to store, index, and transform multidimensional datasets. The project distinguishes itself through a high-performance execution model that utilizes column-major storage, SIMD-aligned memory allocation, and a thread-pool for parallel computations. It employs a visitor-based algorithm dispatch system and policy-driven transformations to decouple data processing logic f
CodeIgniter is a PHP web framework built on the Model-View-Controller pattern, designed for building full-stack web applications. It provides a lightweight toolkit with minimal configuration, organizing application logic into controllers, models, and views for clean separation of concerns. The framework includes a fluent query builder for constructing SQL statements programmatically, PSR-4 autoloading with namespace mapping, and a service-based dependency injection container for managing shared class instances. The framework distinguishes itself through its comprehensive set of built-in tools
Java-faker is a synthetic data generator and mock data library for Java applications. It provides utilities to create randomized, believable fake records such as names and addresses to populate test environments and verify application logic without using real user information. The library specializes in localized data generation, producing synthetic content tailored to specific languages and regional formats. This allows for the verification of application accuracy across different global locales. The tool covers broad capabilities for automated testing mocking, including the generation of m
Hypothesis is a property-based testing library for Python that automatically generates randomized input data to identify bugs and edge cases. It functions as an automated edge case finder and test data generator, creating diverse synthetic datasets based on defined strategies to stress test application logic. The library includes a failing case shrinker that simplifies complex failing test inputs into the smallest possible examples to accelerate debugging. It also provides a mechanism for bug reproduction simplification by reducing the size of the input that triggers a failure. The project c
Faker is a Ruby library used to generate randomized, realistic placeholder information for testing and development. It produces synthetic data to populate databases and test application logic without the use of real user information. The library provides localized data generation, using region-specific formats and strings for names, addresses, and phone numbers. It supports deterministic output through seedable random number generation, ensuring that sequences of fake data can be repeated across different test runs. The generator covers a wide range of domains, including personal identity, f