Download JAR files tagged by client with all dependencies

Set of various Utils: stacktrace noise filter, String to/from unicode sequence converter, simple Http client JSON parser/serializer, Silent String parsing to Integer and other numeric types, Parsing String to time intervals with support for time unit suffixes, JSON parser that provides serialization/deserialization of classes to JSON, Version comparator and Version ranges operations, Self-throttling binary reader from Http request, File reader, A utility that automatically initiates a Factory with instances of all classes that implement user provided interface. An infrastructure for writing Scheduled Task classes where time interval for task execution is provided in humanly readable format (such as "9h" for 9 hours)

The matching web service client library for the server in this example project to connect to the server. This library is ideally provided by the service provider of the server, so that users can go ahead and hack their userland code against this client library, without having to worry about the transport. Whether the client library uses REST or SOAP is up to the implementor, both are possible. A user of the client library usually does not care what technology is used underneath (as long as things are working correctly).

Azure Video Analyzer provides a platform to build intelligent video applications that span the edge and the cloud. The platform offers the capability to capture, record, and analyze live videos along with publishing the results, video, and video analytics, to Azure services in the cloud or the edge. It is designed to be an extensible platform, enabling you to connect different video analysis edge modules such as Cognitive services containers, custom edge modules built by you with open-source machine learning models or custom models trained with your own data. You can then use them to analyze live video without worrying about the complexity of building and running a live video pipeline. Use the client library for Video Analyzer Edge to simplify interactions with the Microsoft Azure IoT SDKs (https://github.com/azure/azure-iot-sdks) and programmatically construct pipeline topologies and live pipelines.

Leveraging Tencent's 21 years of experience in network and audio/video technologies, Tencent Real-Time Communication (TRTC) offers multi-person audio/video calls and low-latency interactive live streaming solutions. With TRTC, you can quickly develop cost-effective, low-latency, and high-quality interactive audio/video services. Audio/Video Call Solution TRTC provides a client SDK that works across platforms and regions. This solution can be easily used on webpages to enable audio and video call capability for all applications. Low-Latency Interactive Live Streaming Solution TRTC leverages Tencent Cloud's high-quality node resources, industry-leading network and audio/video technologies to helps you build interactive live streaming services with minimal lags and a latency below 1 second, taking live streaming into the era of CDN 2.0.腾讯实时音视频（Tencent Real-Time Communication，TRTC）将腾讯21年来在网络与音视频技术上的深度积累，以多人音视频通话和低延时互动直播两大场景化方案，通过腾讯云服务向开发者开放，致力于帮助开发者快速搭建低成本、低延时、高品质的音视频互动解决方案。

1) This module contains various Zookeeper recipe implementations. 2) The recipe directory name should specify the name of the recipe you are implementing - eg. zookeeper-recipes-lock. 3) It would be great if you can provide both the java and c recipes for the zookeeper recipes. C recipes go in to zookeeper-recipes/zookeeper-recipes-[recipe-name]/src/c Java implementation goes into zookeeper-recipes/zookeeper-recipes-[recipe-name]/src/java. 4) The recipes hold high standards like our zookeeper c/java libraries, so make sure that you include some unit testing with both the c and java recipe code. 5) Also, please name your c client public methods as zkr_recipe-name_methodname (eg. zkr_lock_lock in zookeeper-recipes-lock/src/c) 6) To run the c tests in all the recipes, - make sure the main zookeeper c libraries in zookeeper-client-c are compiled. Run autoreconf -if;./configure; make. The libraries will be installed in {top}/src/c/.libs. - run autoreconf if;./configure;make run-check in zookeeper-recipes/$recipename/src/c

This is client side library for forker, and the one you most likely want to use in your own applications. It provides the ProcessBuilder replacement, ForkerBuilder, as well the helpers in OSCommand. ForkerBuilder is capable of launching processes using non-blocking I/O or attached to a PTY. It has many additional features not available in the standard process builder including permission elevation, daemonize, processor affinity and more. Parts of the non-blocking API are based on NuProcess (https://github.com/brettwooldridge/NuProcess)

This library allows your Java program to interface very easily with the Python world. It uses the Pyro protocol to call methods on remote objects. (See https://pyro5.readthedocs.io/). Pyrolite only implements part of the client side Pyro library, hence its name 'lite'... So if you don't need Pyro's full feature set, Pyrolite may be a good choice to connect java or .NET and python. Version 5.0 changes: support Pyro5 wire protocol. Dropped support of Pyro4 (stick to version 4.xx for that).

The Zello Channels SDK allows you to integrate Zello push-to-talk into your own application. The SDK communicates with a Zello server over a web socket connection using a JSON-based protocol, and offers a simple API to send and receive audio, images, and text over Zello channels. Supported features include: Send voice messages from the device microphone Play incoming voice messages through the device speaker Send voice messages from your own audio code, e.g. from a file Receive voice message data with your own audio code with optional pass-through to the device speaker Send and recieve text messages Send and receive images Send the device's current location, and receive location messages from other users The protocol specification is also available if you prefer to develop your own client in-house.