Displaying 1 to 13 from 13 results

deck.gl - WebGL based visualization layers


Provides tested, highly performant layers for data visualization, such as scatterplots, arcs, geometries defined in GeoJSON, etc...To learn how to use deck.gl through examples coming with the deck.gl repo, please clone the latest release branch.

react-map-gl - React friendly API wrapper around MapboxGL JS


In addition to exposing MapboxGL functionality to React apps, react-map-gl also integrates seamlessly with deck.gl.browserify - react-map-gl is extensively tested with browserify and works without configuration.

react-vis - Data-Visualization oriented components


A collection of react components to render common data visualization charts, such as line/area/bar charts, heat maps, scatterplots, contour plots, pie and donut charts, sunbursts, radar charts, parallel coordinates, and tree maps.Install react-vis via npm.

luma.gl - A JavaScript WebGL Framework for Data Visualization


luma.gl's provides efficient and easy-to-use WebGL2-based building blocks enabling high-performance GPU-based data visualizations and computations on your browser.See Examples and Documentation. Change Log.




AutoDispose - Automatic binding+disposal of RxJava 2 streams.


AutoDispose is an RxJava 2 tool for automatically binding the execution of RxJava 2 streams to a provided scope via disposal/cancellation.Often (especially in mobile applications), Rx subscriptions need to stop in response to some event (for instance, when Activity#onStop() executes in an Android app). In order to support this common scenario in RxJava 2, we built AutoDispose.

AthenaX - SQL-based streaming analytics platform at scale


AthenaX is a streaming analytics platform that enables users to run production-quality, large scale streaming analytics using Structured Query Language (SQL). AthenaX was released and open sourced by Uber Technologies. It is capable of scaling across hundreds of machines and processing hundreds of billions of real-time events daily.Apache 2.0 License.

Pyro - Deep universal probabilistic programming with Python and PyTorch


Pyro is a universal probabilistic programming language (PPL) written in Python and supported by PyTorch on the backend. Pyro enables flexible and expressive deep probabilistic modeling, unifying the best of modern deep learning and Bayesian modeling.

horovod - Distributed training framework for TensorFlow.


Horovod is a distributed training framework for TensorFlow. The goal of Horovod is to make distributed Deep Learning fast and easy to use.Internally at Uber we found that it's much easier for people to understand an MPI model that requires minimal changes to source code than to understand how to set up regular Distributed TensorFlow.



lint-trap - JavaScript linter module for Uber projects


This module contains standardized linting rules to be used across all projects at Uber that contain JavaScript.... and then you can invoke it by executing npm run lint.

NEAL - Automate your code reviews with custom syntactic rules


NEAL (Not Exactly A Linter) is a language-independent code analysis tool that aims to enable more people to write quality enforcement rules.A forced-value consists of any expression that results in an optional value followed by the forced-unwrapping operator (!). Here's a contrived example that would result in a runtime crash.

react-vis-force - d3-force graphs as React Components.


react-vis-force applies the react-vis and d4-style component approach to the d3-force library. This allows users to declaratively provide links and nodes as children of a ForceGraph component.

uberscriptquery - UberScriptQuery, a SQL-like DSL to make writing Spark jobs super easy


UberScriptQuery is a script query wrapper to run Spark SQL jobs.Why did we build this? Apache Spark is a great tool to do data processing, yet people usually end up writing many similar Spark jobs. There is substantial development cost to write and maintain all these jobs. Additionally, Spark is still mostly for developers, and other people such as data analysts or data scientists may still feel that Spark has a steep learning curve.

auto-value-bundle - Extends Autovalue to extract data from a bundle into a value object.


An extension for Google's AutoValue that supports Android Bundle object.Bundles are used to pass data along with intents and services, between activities, and from GCM, among other reasons. However, converting that data from a bundle to a Java object involves a lot of repetitive and error-prone code.