Search Results for "speed test"
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Showing 8 open source projects for "speed test"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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1
WebP Codec
Library to encode and decode images in WebP format
...As a widely deployed codec, libwebp balances compression efficiency, speed, and integration simplicity across platforms. -
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php-file-iterator
FilterIterator implementation that filters files
...It also plays nicely with glob patterns and SPL iterators, so you can combine it with other filesystem utilities. As part of the PHPUnit tooling suite, it’s optimized for speed and predictable behavior across platforms. -
3
KaTeX
Fast math typesetting for the web.
KaTeX is a fast, easy-to-use JavaScript library for TeX math rendering on the web. Fast: KaTeX renders its math synchronously and doesn't need to reflow the page. See how it compares to a competitor in this speed test. Print quality: KaTeX's layout is based on Donald Knuth's TeX, the gold standard for math typesetting. Self contained: KaTeX has no dependencies and can easily be bundled with your website resources. Server side rendering: KaTeX produces the same output regardless of browser or environment, so you can pre-render expressions using Node.js and send them as plain HTML. ... -
4
GoNB
GoNB, a Go Notebook Kernel for Jupyter
Go is a compiled language, but with very fast compilation, that allows one to use it in a REPL (Read-Eval-Print-Loop) fashion, by inserting a "Compile" step in the middle of the loop -- so it's a Read-Compile-Run-Print-Loop — while still feeling very interactive. GoNB leverages that compilation speed to implement a full-featured (at least it's getting there) Jupyter notebook kernel. As a side benefit it works with packages that use CGO — although it won't parse C code in the cells, so it... -
Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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Union Pandera
Light-weight, flexible, expressive statistical data testing library
The open-source framework for precision data testing for data scientists and ML engineers. Pandera provides a simple, flexible, and extensible data-testing framework for validating not only your data but also the functions that produce them. A simple, zero-configuration data testing framework for data scientists and ML engineers seeking correctness. Access a comprehensive suite of built-in tests, or easily create your own validation rules for your specific use cases. Validate the functions... -
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JavaScript & Node.js Testing
Comprehensive and exhaustive JavaScript & Node.js testing
This project compiles practical advice for testing JavaScript applications across the stack, emphasizing clarity, speed, and reliability over dogma. It distinguishes between different kinds of tests—unit, integration, end-to-end—and shows when each is appropriate given time and risk constraints. The guide focuses on removing flakiness by isolating side effects, controlling randomness, and stabilizing async code paths. It also demonstrates test design techniques like arranging test data, using expressive assertions, and structuring test suites for readability and discoverability. ... -
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OkReplay
Record and replay OkHttp network interaction in your tests
OkReplay is a tool for recording and replaying HTTP interactions (specifically via OkHttp) in Android tests to improve determinism, test speed, and reliability. During the first run of a test annotated with @OkReplay, the library records outgoing HTTP requests and their responses into tape files. On subsequent runs, it intercepts those requests and serves the recorded responses instead of making real network calls. This allows tests to be executed offline, reduces flakiness due to network variability, and isolates the test environment from external dependencies. ... -
8
benchm-ml
A benchmark of commonly used open source implementations
This repository is designed to provide a minimal benchmark framework comparing commonly used machine learning libraries in terms of scalability, speed, and classification accuracy. The focus is on binary classification tasks without missing data, where inputs can be numeric or categorical (after one-hot encoding). It targets large scale settings by varying the number of observations (n) up to millions and the number of features (after expansion) to about a thousand, to stress test different implementations. ...
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