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CogComp's Natural Language Processing Libraries and Demos: Modules include lemmatizer, ner, pos, prep-srl, quantifier, question type, relation-extraction, similarity, temporal normalizer, tokenizer, transliteration, verb-sense, and more.

A simple configuration library for Java applications providing a node structure, a variety of formats, and tools for transformation

  • configuration
  • java
  • json
  • yaml

Fast and Easy mapping from database and csv to POJO. A java micro ORM, lightweight alternative to iBatis and Hibernate. Fast Csv Parser and Csv Mapper

JQuick Java: a lightweight Java-like scripting language for rule engines. Declare, parse and execute business rules at runtime via XML or inline scripts—no restart needed. Java 8+, embeddable, with LSP and IDEA plugin support.

Developed to power Conveyal's web-based interface for scenario planning and land-use/transport accessibility analysis, R5 is our routing engine for multimodal (transit/bike/walk/car) networks with a particular focus on public transit

TranslatedAd-removal LSPosed module for Amap (高德)/Baidu Maps/Tencent Maps (libxposed API 102) + UI customization for Amap's home page/"Me" page/search page; new in v1.1.0: turn off the hot-word carousel in the search box, remove the taxi-hailing floating window from the home page

WebTau (web test automation) is a testing API, command line tool and a framework to write unit, integration and end-to-end tests. Test across REST-API, WebSocket, GraphQL, Browser, Database, CLI and Business Logic with a consistent set of matchers and concepts. REPL mode speeds-up tests development. Rich reporting cuts down investigation time.

The Spatial Framework for Hadoop allows developers and data scientists to use the Hadoop data processing system for spatial data analysis.

  • data-management
  • spatial-analysis

Java type safe statically compiled mustache

  • annotation-processor
  • java
  • mustache
  • template-engine

The Kinesis Scaling Utility is designed to give you the ability to scale Amazon Kinesis Streams in the same way that you scale EC2 Auto Scaling groups – up or down by a count or as a percentage of the total fleet. You can also simply scale to an exact number of Shards. There is no requirement for you to manage the allocation of the keyspace to Shards when using this API, as it is done automatically.