Search Results for "data bin 6"
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Showing 7 open source projects for "data bin 6"
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jsonschema
An implementation of the JSON Schema specification for Python
jsonschema is an implementation of the JSON Schema specification for Python. Full support for Draft 2020-12, Draft 2019-09, Draft 7, Draft 6, Draft 4 and Draft 3. Lazy validation that can iteratively report all validation errors. Programmatic querying of which properties or items failed validation. -
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simdjson
Parsing gigabytes of JSON per second
JSON is everywhere on the Internet. Servers spend a *lot* of time parsing it. We need a fresh approach. The simdjson library uses commonly available SIMD instructions and microparallel algorithms to parse JSON 4x faster than RapidJSON and 25x faster than JSON for Modern C++. The simdjson library uses three-quarters less instructions than state-of-the-art parser RapidJSON. To our knowledge, simdjson is the first fully-validating JSON parser to run at gigabytes per second (GB/s) on commodity... -
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Add schemaless attributes
Add schemaless attributes to Eloquent models
Wouldn't it be cool if you could have a bit of the spirit of NoSQL available in Eloquent? This package does just that. It provides a trait that when applied to a model, allows you to store arbitrary values in a single JSON column. -
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gSOAP Toolkit
Development toolkit for Web Services and XML data bindings for C & C++
The gSOAP toolkit is an extensive suite of portable C and C++ software to develop XML Web services with powerful type-safe XML data bindings. Easy-to-use code-generator tools allow you to directly integrate XML data in C and C++. Serializes native application data in XML. Includes WSDL/XSD schema binding and auto-coding tools, stub/skeleton compiler, Web server integration with Apache module and IIS extension, high-performance XML processing with schema validation, fast MIME/MTOM streaming,... -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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5
JSON2YOLO
Convert JSON annotations into YOLO format.
Explore our state-of-the-art AI architecture to train and deploy your highly accurate AI models like a pro. This directory contains label import/export software developed by Ultralytics LLC, and is freely available for redistribution under the GPL-3.0 license. Ultralytics is a U.S.-based particle physics and AI startup with over 6 years of expertise supporting government, academic, and business clients. We offer a wide range of vision AI services, spanning from simple expert advice up to the... -
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fast-serialization
FST: fast java serialization drop in-replacement
Up to 10 times faster 100% JDK Serialization compatible drop-in replacement (Ok, might be 99% ..). As an example: Lambda Serialization which came with 1.8 worked instantly. Android compatible since version 2.17 (use FSTConfiguration.createAndroidDefaultConfiguration() both on the server and client side. The configuration object has to be passed into FSTObjectIn/Output constructors) FSTStructs is very similar to IBM's packed objects. The difference is you can run it with Oracle JDK today.... -
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Occursions
Fast customizable time series web database for big data like log files
Our goal is to create the world's fastest extendable, non-transactional time series database for big data (you know, for kids)! Log file indexing is our initial focus. For example append only ASCII files produced by libraries like Log4J, or containing FIX messages or JSON objects. Occursions was built by a small team sick of creating hacks to remotely copy and/or grep through tons of large log files. We use it to index around a terabyte of new log data per day. You can use it too. Who...
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