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deequ

Deequ is a library built on top of Apache Spark for defining "unit tests for data", which measure data quality in large datasets.

defending-devops

Lab Material for the Two-Day Defending Modern DevOps Environments Course

definitelytyped

The repository for high quality TypeScript type definitions.

defusedxml

delayed_deprecation

Delayed deprecation warnings

delaypropagation

Microscopic traffic flow models - Train following model

demreum

Smart contract engine for Ethereum

denco

The fast and flexible HTTP request router for Go

dendrite

Dendrite is an experimental second-generation Matrix homeserver written in Go (still in development, not recommended for use)

dep

Dealing with dependency cycles in Golang

depaware

depaware makes you aware of your Go dependencies

descheduler

Descheduler for Kubernetes

design-patterns-spring-boot

A few design pattern examples in spring boot

design-tokens

A place where OpenTable engineers and designers openly work together

designpatterns

:triangular_ruler: Design patterns for Project Orleans

desim

Discrete Event Simulations

devilution

Diablo devolved - magic behind the 1996 computer game

devsecops-cloud-custodian-rules

[WORK IN PROGRESS] A repo containing rule sets for cloud-custodian inside GSA AWS accounts. This repo does not contain cloud-custodian itself.

dex

OpenID Connect Identity (OIDC) and OAuth 2.0 Provider with Pluggable Connectors

dfa-regex-engine

simple DFA regex engine written in Go.

dflow

Dalmatiner flow processing library.

dfs-datastores

Dead-simple vertical partitioning, compression, appends, and consolidation of data on a distributed filesystem.

dgoogauth

Google Authenticator for Go

dgraph

Fast, Distributed Graph DB

dht

Golang implementation of a distributed hash table using Consul and rendezvous hashing

dhtpx

Peer exchange and discovery on top of the BitTorrent DHT Network

diagrams

:art: Diagram as Code for prototyping cloud system architectures

differentiable-plasticity

Implementations of the algorithms described in Differentiable plasticity: training plastic networks with gradient descent, a research paper from Uber AI Labs.

difficulty-algorithms

See the Issues for difficulty algorithms

diligent

Get the licenses associated with your software dependencies