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broccoli - Browser compilation library – an asset pipeline for applications that run in the browser
A fast, reliable asset pipeline, supporting constant-time rebuilds and compact build definitions. Comparable to the Rails asset pipeline in scope, though it runs on Node and is backend-agnostic. For background and architecture, see the introductory blog post.For the command line interface, see broccoli-cli.
builder build frontend browser asset pipelinestreamjs - Lazy Object Streaming Pipeline for JavaScript
Stream.js is a lightweight (2.6 KB minified, gzipped), intensely tested (700+ assertions, 97% coverage) functional programming library for operating upon collections of in-memory data. It requires EcmaScript 5+, has built-in support for ES6 features and works in all current browsers, Node.js and Java 8 Nashorn. Before explaining how Stream.js works in detail, here's a few real world code samples.
stream streaming-api stream-pipeline functional collection pipeline lazy utils arraygo_spider - [爬虫框架 (golang)] An awesome Go concurrent Crawler(spider) framework
A crawler of vertical communities achieved by GOLANG. Latest stable Release: Version 1.2 (Sep 23, 2014).
spider crawler schedule pipelinedata-integration - A lightweight opinionated ETL framework, halfway between plain scripts and Apache Airflow
Data integration pipelines as code: pipelines, tasks and commands are created using declarative Python code. PostgreSQL as a data processing engine.
etl data-integration postgresql pipeline datagulp - The streaming build system
This file will give you a taste of what gulp does. Node already supports a lot of ES2015, to avoid compatibility problem we suggest to install Babel and rename your gulpfile.js as gulpfile.babel.js.
build stream system make tool asset pipeline series parallel streamingpipeline - PipelineAI: Real-Time Enterprise AI Platform
Each model is built into a separate Docker image with the appropriate Python, C++, and Java/Scala Runtime Libraries for training or prediction. Use the same Docker Image from Local Laptop to Production to avoid dependency surprises.
machine-learning artificial-intelligence tensorflow kubernetes elasticsearch cassandra ipython spark kafka netflixoss presto airflow pipeline jupyter-notebook zeppelin docker redis neural-network gpu microservicespapermill - 📚 Parameterize, execute, and analyze notebooks
Papermill is a tool for parameterizing, executing, and analyzing Jupyter Notebooks. To parameterize your notebook designate a cell with the tag parameters.
jupyter notebooks notebook-generator nteract publishing pipelinegaia - Build powerful pipelines in any programming language.
Develop powerful pipelines with the help of SDKs and simply check-in your code into a git repository. Gaia automatically clones your code repository, compiles your code to a binary and executes it on-demand. All results are streamed back and formatted to a user-friendly graphical output. Automation Engineer, DevOps, SRE, Cloud Engineer, Platform Engineer - they all have one in common: The majority of tech people are not motivated to take up this work and they are hard to recruit.
pipeline automation cplusplus build deployment kubernetes continuous-integration continuous-delivery continuous-testing devops devops-toolsfirebase-queue
There may continue to be specific use-cases for firebase-queue, however if you're looking for a general purpose, scalable queueing system for Firebase then it is likely that building on top of Google Cloud Functions for Firebase is the ideal route. A fault-tolerant, multi-worker, multi-stage job pipeline built on the Firebase Realtime Database.
job task queue worker firebase realtime pipelinehttpx - httpx is a fast and multi-purpose HTTP toolkit allows to run multiple probers using retryablehttp library, it is designed to maintain the result reliability with increased threads
httpx is a fast and multi-purpose HTTP toolkit allow to run multiple probers using retryablehttp library, it is designed to maintain the result reliability with increased threads. This will display help for the tool. Here are all the switches it supports.
http osint pipeline cybersecurity ssl-certificate bugbounty pentest-toolgreat_expectations - Always know what to expect from your data.
Always know what to expect from your data. Great Expectations helps data teams eliminate pipeline debt, through data testing, documentation, and profiling.
data-science pipeline exploratory-data-analysis eda data-engineering data-quality data-profiling datacleaner exploratory-analysis cleandata dataquality datacleaning mlops pipeline-tests pipeline-testing dataunittest data-unit-tests exploratorydataanalysis pipeline-debt data-profilersMLJ.jl - A Julia machine learning framework
New to MLJ? Start here. Wanting to integrate an existing machine learning model into the MLJ framework? Start here.
data-science machine-learning statistics pipeline clustering julia pipelines regression tuning classification ensemble-learning predictive-modeling tuning-parameters stackingvector - A high-performance, highly reliable, observability data pipeline.
Vector is a high-performance, end-to-end (agent & aggregator) observability data pipeline that puts you in control of your observability data. Collect, transform, and route all your logs, metrics, and traces to any vendors you want today and any other vendors you may want tomorrow. Vector enables dramatic cost reduction, novel data enrichment, and data security where you need it, not where is most convenient for your vendors. Additionally, it is open source and up to 10x faster than every alternative in the space. To get started, follow our quickstart guide or install Vector.
parser events router pipeline metrics vector logs stream-processing forwarder observabilitygollum - An n:m message multiplexer written in Go
Gollum is an n:m multiplexer that gathers messages from different sources and broadcasts them to a set of destinations.Gollum originally started as a tool to MUL-tiplex LOG-files (read it backwards to get the name). It quickly evolved to a one-way router for all kinds of messages, not limited to just logs. Gollum is written in Go to make it scalable and easy to extend without the need to use a scripting language.
gollum logging logger stream log logs message-bus multiplexer pipeline messaging pub-sub message-queuedatakit - Connect processes into powerful data pipelines with a simple git-like filesystem interface
DataKit is a tool to orchestrate applications using a Git-like dataflow. It revisits the UNIX pipeline concept, with a modern twist: streams of tree-structured data instead of raw text. DataKit allows you to define complex build pipelines over version-controlled data.DataKit is currently used as the coordination layer for HyperKit, the hypervisor component of Docker for Mac and Windows, and for the DataKitCI continuous integration system.
datakit filesystem-api data-flow database docker pipelinesyntax_sugar_python - A library adding some anti-Pythonic syntatic sugar to Python
This lib adds some anti-Pythonic "syntactic sugar" to Python. NOTE: This is merely an experimental prototype to show some potential of operator overloading in Python. Only tested under Python 3.6.0. Anything may evolve without announcement in advance.
syntax-sugar pipeline parallelism functionallambdacd - a library to define a continuous delivery pipeline in code
I'd love to hear from you! If you have a question, a bug report or feature request please reach out. LambdaCD is built in Clojure and ClojureScript with Leiningen as a build-tool. The ./go script is your main entry-point that wraps all important development tasks. Call it without arguments to see all the options.
pipeline lambdacd pipelines-as-code continuous-integration continuous-delivery ci tool library cd build-pipelines delivery-pipelinesnextflow - A DSL for data-driven computational pipelines
With the rise of big data, techniques to analyse and run experiments on large datasets are increasingly necessary. Parallelization and distributed computing are the best ways to tackle this kind of problem, but the tools commonly available to the bioinformatics community traditionally lack good support for these techniques, or provide a model that fits badly with the specific requirements in the bioinformatics domain and, most of the time, require the knowledge of complex tools or low-level APIs.
bioinformatics workflow-engine pipeline pipeline-framework nextflow cloud data-flow sge slurm aws docker singularity hpc singularity-containers reproducible-science reproducible-researchgalaxy - Data intensive science for everyone.
You may wish to make changes from the default configuration. This can be done in the config/galaxy.ini file. Note that not all dependencies for the tools provided in the tool_conf.xml.sample are included. To install them please visit "Manage dependencies" in the admin interface.
bioinformatics workflow genomics science sequencing ngs dna usegalaxy docker pipeline workflow-engine
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