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d3-scale - Encodings that map abstract data to visual representation.
Encodings that map abstract data to visual representation.
d3 d3-module scale visualizationlwip - Light Weight Image Processor for NodeJS
This module provides comprehensive, fast, and simple image processing and manipulation capabilities.There are no external runtime dependencies, which means you don't have to install anything else on your system.
image buffer manipulate process resize scale rotate jpeg jpg png gif crop blur sharpen batch flip mirror border padding hue saturation lightness alpha transparency fade opacity contain coverpica - Resize image in browser with high quality and high speed
Resize images in browser without pixelation and reasonably fast. Autoselect the best of available technologies: webworkers, webassembly, createImageBitmap, pure JS.Note. Old browsers may need Promise polyfill to work. For example, lie.
image resize scale lanczos canvascropper - A simple jQuery image cropping plugin.
A simple jQuery image cropping plugin.The cdnjs provides CDN support for Cropper's CSS and JavaScript. You can find the links here.
crop-image cropper jquery-plugin image-cropper image crop cropping move zoom rotate scale plugin html css front-end web development jquerycropperjs - JavaScript image cropper.
JavaScript image cropper.The cdnjs provides CDN support for Cropper.js's CSS and JavaScript. You can find the links here.
image cropper crop-image image-cropper crop cropping move zoom rotate scale cropperjs cropper.js html css front-end web developmenttonal - A functional music theory library for Javascript
tonal is a small (20kb minified, 6kb gzipped) javascript modular music theory library. It provides functions to manipulate tonal elements of music (pitches, chords, scales, keys). It deals with abstractions (not actual music). It uses a functional programing style: all functions are pure, there is no data mutation, entities are represented by data structures instead of objects, and lot of functions accept partial application.
music-theory music functional scale chords key-signaturesRTImageAssets - A Xcode plugin to automatically generate @2x, @1x image from @3x image for you, or upscale to @3x from @2x
Clone this Repo, build it in Xcode, and restart your Xcode. Install Package Manager for Xcode, search: RTImageAssets.
xcode-plugin icons assets scalesnappydata - SnappyData - The Spark Database. Stream, Transact, Analyze, Predict in one cluster
Apache Spark is a general purpose parallel computational engine for analytics at scale. At its core, it has a batch design center and is capable of working with disparate data sources. While this provides rich unified access to data, this can also be quite inefficient and expensive. Analytic processing requires massive data sets to be repeatedly copied and data to be reformatted to suit Spark. In many cases, it ultimately fails to deliver the promise of interactive analytic performance. For instance, each time an aggregation is run on a large Cassandra table, it necessitates streaming the entire table into Spark to do the aggregation. Caching within Spark is immutable and results in stale insight. At SnappyData, we take a very different approach. SnappyData fuses a low latency, highly available in-memory transactional database (GemFireXD) into Spark with shared memory management and optimizations. Data in the highly available in-memory store is laid out using the same columnar format as Spark (Tungsten). All query engine operators are significantly more optimized through better vectorization and code generation. The net effect is, an order of magnitude performance improvement when compared to native Spark caching, and more than two orders of magnitude better Spark performance when working with external data sources.
snappydata spark memory-database analytics stream transaction scaleDepth - Add some Depth to your fragments
Add some Depth to your fragments
android fragment depth 3d material design animation transition translation scaleCitus - Scalable PostgreSQL for multi-tenant and real-time workloads
Citus is a distributed database that scales across commodity servers using transparent sharding and replication. Citus extends the underlying database rather than forking it, giving developers and enterprises the power and familiarity of a relational database. As an extension, Citus supports new PostgreSQL releases, and allows you to benefit from new features while maintaining compatibility with existing PostgreSQL tools.
database citus multi-tenant postgresql scale sharding sql distributed-database postgresreframe.js - 🖼 Reframe unresponsive elements responsively.
Elements that have been wrapped with reframe will not be wrapped twice. Reframe.js wraps a specified element in a div that is an intrinsic ratio of the original element. This plugin is great for embedded content like iframes or videos.
ratio scale elements-scale iframe-embeds embeds iframes js fluid responsive video fitvids youtube padding-topheimdall - An enhanced HTTP client for Go
All HTTP methods are exposed as a fluent interface. This package can be used by adding the following import statement to your .go files.
circuit-breaker hystrix retries backoff scale distributed-systems httpclientflutter_screenutil - Flutter screen adaptation, font adaptation, get screen information
Note: This plugin is still under development, and some APIs might not be available yet. Please check the latest version before installation.
flutter dart screenutil screen scalesnappydata - Project SnappyData - memory optimized analytics database, based on Apache Spark™ and Apache Geode™
SnappyData (aka TIBCO ComputeDB) is a distributed, in-memory optimized analytics database. SnappyData delivers high throughput, low latency, and high concurrency for unified analytics workload. By fusing an in-memory hybrid database inside Apache Spark, it provides analytic query processing, mutability/transactions, access to virtually all big data sources and stream processing all in one unified cluster. One common use case for SnappyData is to provide analytics at interactive speeds over large volumes of data with minimal or no pre-processing of the dataset. For instance, there is no need to often pre-aggregate/reduce or generate cubes over your large data sets for ad-hoc visual analytics. This is made possible by smartly managing data in-memory, dynamically generating code using vectorization optimizations and maximizing the potential of modern multi-core CPUs. SnappyData enables complex processing on large data sets in sub-second timeframes.
spark stream scale analytics transaction memory-database snappydataJimp - An image processing library written entirely in JavaScript for Node
An image processing library for Node written entirely in JavaScript, with zero native dependencies. It supports image manipulation methods like Blit an image, Blur an image, Various color manipulation methods, Resize, Scale and Rotate the image, Apply a dither effect to an image, Mask one image with another, Print text onto an image (watermark) and lot more.
image image-processing image-manipulation png jpg jpeg bmp resize scale crop image-analysis rotatesvg-mesh-3d - :rocket: converts a SVG path to a 3D mesh
A high-level module to convert a SVG <path> string into a 3D triangulated mesh. Best suited for silhouettes, like font icon SVGs.Built on top of cdt2d by @mikolalysenko, and various other modules.
svg triangulate mesh path normalize scalechartify - React.js plugin for building simple animated draggable charts
The source for this module is in the main repo.Container prop is a class that will be added to the chart container element. This is important in case you have more than one chart on your page.
chart charts react barchart linechart timeline timesheet films music-library music-visualizer react-plugins customizable-charts cinematography movie-collection visualization draggable-elements draggable film-ratings rank reactjs react-js react-chart scale items dataset kinopoisk line-chart bar-chart marks axis calendar-view pyramid progress-chart showreel visualisation diagram graphperformance-optimization - Guidance on how to observe, measure, and correct common issues in a cloud-based system
This repo contains sample code for a set of performance antipatterns. Documentation and guidance for these patterns can be found on the Azure Architecture Center. For each antipattern, the documentation describes why the antipattern typically occurs, symptoms of the antipattern, and techniques for resolving the problem. The corresponding sample code shows (1) the problem and (2) a recommended way to fix the problem.
anti-patterns performance-optimization cloud-application scale c-sharp
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