Showing 3911 open source projects for "source"

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  • Go from Code to Production URL in Seconds Icon
    Go from Code to Production URL in Seconds

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  • 1
    Apache Doris

    Apache Doris

    MPP-based interactive SQL data warehousing for reporting and analysis

    Apache Doris is a modern MPP analytical database product. It can provide sub-second queries and efficient real-time data analysis. With it's distributed architecture, up to 10PB level datasets will be well supported and easy to operate. Apache Doris can meet various data analysis demands, including history data reports, real-time data analysis, interactive data analysis, and exploratory data analysis. Make your data analysis easier! Support standard SQL language, compatible with MySQL...
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  • 2
    Logan

    Logan

    Logan is a lightweight case logging system based on mobile platform

    Logan is a log platform with the ability to collect, store, upload and analyze front-end logs. We provide five components, including iOS SDK, Android SDK, Web SDK, analysis services Server SDK and LoganSite. In addition, we also provide a Flutter plugin Flutter Plugin. LoganSite provides a visualized way for developers to scan and search logs uploaded from App and Web. To put it simply, the traditional idea is to piece together the problems that appear in the logs of each system, but the new...
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  • 3
    Blue Whale Configuration Platform

    Blue Whale Configuration Platform

    Blue Whale smart cloud configuration platform

    Has accumulated experience in supporting hundreds of Tencent businesses, compatible with various complex system architectures, born in operation and maintenance, and proficient in operation and maintenance. From configuration management to job execution, task scheduling and monitoring self-healing, and then through operation and maintenance big data analysis to assist operational decision-making, it covers the full-cycle assurance management of business operations in a comprehensive manner....
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  • 4
    Cookiecutter Data Science

    Cookiecutter Data Science

    Project structure for doing and sharing data science work

    A logical, reasonably standardized, but flexible project structure for doing and sharing data science work. When we think about data analysis, we often think just about the resulting reports, insights, or visualizations. While these end products are generally the main event, it's easy to focus on making the products look nice and ignore the quality of the code that generates them. Because these end products are created programmatically, code quality is still important! And we're not talking...
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  • 5
    billboard.js

    billboard.js

    Re-usable, easy interface JavaScript chart library based on D3.js

    billboard.js is a re-usable, easy interface JavaScript chart library, based on D3.js. The name "billboard" comes from the famous "billboard chart" which everybody knows. billboard.js provides the easiest way to create a 'chart' instantly. Chart generation is super easy. With extensive options, you can create a chart instantly! Yes, billboard.js works on D3 v4+; what everybody was waiting for! All of the code was written as an ESM(ES Module) with ES6+ syntax. Combine hundreds of options to...
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  • 6
    wavesurfer.js

    wavesurfer.js

    Navigable waveform built on Web Audio and Canvas

    wavesurfer.js is a customizable audio waveform visualization, built on top of Web Audio API and HTML5 Canvas. With wavesurfer.js you can create anything from an HTML5 audio player to a sophisticated DJ application. wavesurfer.js works only in modern browsers supporting Web Audio. It will fallback to Audio Element without graphics in other browsers (IE 11 and lower). You can also try wavesurfer.swf which is a Flash-based fallback. The audio will start playing as you press play. A thin line...
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  • 7
    tsfresh

    tsfresh

    Automatic extraction of relevant features from time series

    tsfresh is a python package. It automatically calculates a large number of time series characteristics, the so called features. tsfresh is used to to extract characteristics from time series. Without tsfresh, you would have to calculate all characteristics by hand. With tsfresh this process is automated and all your features can be calculated automatically. Further tsfresh is compatible with pythons pandas and scikit-learn APIs, two important packages for Data Science endeavours in python....
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  • 8
    TensorBoardX

    TensorBoardX

    tensorboard for pytorch (and chainer, mxnet, numpy, etc.)

    The SummaryWriter class provides a high-level API to create an event file in a given directory and add summaries and events to it. The class updates the file contents asynchronously. This allows a training program to call methods to add data to the file directly from the training loop, without slowing down training. TensorboardX now supports logging directly to Comet. Comet is a free cloud based solution that allows you to automatically track, compare and explain your experiments. It adds a...
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  • 9
    ElasticJob

    ElasticJob

    Distributed scheduled job framework

    ElasticJob is a distributed scheduling solution consisting of two separate projects, ElasticJob-Lite and ElasticJob-Cloud. ElasticJob-Lite is a lightweight, decentralized solution that provides distributed task sharding services. ElasticJob-Cloud uses Mesos to manage and isolate resources. It uses a unified job API for each project. Developers only need code one time and can deploy at will. Support job sharding and high availability in distributed system. Scale out for throughput and...
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  • 10
    PULSAR

    PULSAR

    Distributed pub-sub messaging system

    Apache Pulsar is a cloud-native, distributed messaging and streaming platform originally created at Yahoo! and now a top-level Apache Software Foundation project. Easy to deploy, lightweight compute process, developer-friendly APIs, no need to run your own stream processing engine. Run in production at Yahoo! scale for over 5 years, with millions of messages per second across millions of topics. Expand capacity seamlessly to hundreds of nodes. Low publish latency (< 5ms) at scale with strong...
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  • 11
    Superstruct

    Superstruct

    A simple and composable way to validate data in JavaScript

    This project is a lightweight validation library for JavaScript and TypeScript that helps you define data “shapes” and validate runtime values against them. Instead of relying only on compile-time typing, it focuses on the reality that many apps receive unknown input from APIs, forms, and external systems, and those values need runtime checks. Its API is intentionally familiar if you’ve used TypeScript, Flow, Go structs, or GraphQL schemas, but the output is oriented around runtime...
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  • 12
    AWS SDK for pandas

    AWS SDK for pandas

    Easy integration with Athena, Glue, Redshift, Timestream, Neptune

    aws-sdk-pandas (formerly AWS Data Wrangler) bridges pandas with the AWS analytics stack so DataFrames flow seamlessly to and from cloud services. With a few lines of code, you can read from and write to Amazon S3 in Parquet/CSV/JSON/ORC, register tables in the AWS Glue Data Catalog, and query with Amazon Athena directly into pandas. The library abstracts efficient patterns like partitioning, compression, and vectorized I/O so you get performant data lake operations without hand-rolling...
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  • 13
    Searchkick

    Searchkick

    Intelligent search made easy

    Searchkick brings powerful, production-ready search to Rails by mapping Active Record models into Elasticsearch with sensible defaults and easy customization. It supports language analyzers, stemming, synonyms, misspelling tolerance, and highlighting so search results feel natural to end users. Indexing is model-centric: you declare what fields to index, add computed fields, and trigger reindexing via callbacks or background jobs, with options for zero-downtime rolling reindexes. On the...
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  • 14
    brms

    brms

    brms R package for Bayesian generalized multivariate models using Stan

    brms is an R package by Paul Bürkner which provides a high-level interface for fitting Bayesian multilevel (i.e. mixed effects) models, generalized linear / non-linear / multivariate models using Stan as the backend. It allows R users to specify complex Bayesian models using formula syntax similar to lme4 but with far more flexibility (distributions, link functions, hierarchical structure, nonlinear terms, etc.). It supports model diagnostics, posterior predictive checking, model comparison,...
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  • 15
    Every Door

    Every Door

    A dedicated app for collecting thousands of POI for OpenStreetMap

    The best OpenStreetMap editor for POIs and entrances. The best app for on-the-ground surveying for OpenStreetMap! Add shops and amenities, survey benches and trees, collect addresses, or use them as walking papers. This editor does not make you think. Just go to a mall, and start Every Door. You'll see mapped shops around you: tap on the checkmark for any that are still there, and add shops that are not on the map. That's the entire process: you can keep your entire town up-to-date thanks to...
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  • 16
    Catalyst.jl

    Catalyst.jl

    Chemical reaction network and systems biology interface

    Catalyst.jl is a symbolic modeling package for analysis and high-performance simulation of chemical reaction networks. Catalyst defines symbolic ReactionSystems, which can be created programmatically or easily specified using Catalyst's domain-specific language (DSL). Leveraging ModelingToolkit and Symbolics.jl, Catalyst enables large-scale simulations through auto-vectorization and parallelism. Symbolic ReactionSystems can be used to generate ModelingToolkit-based models, allowing the easy...
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  • 17
    pointblank

    pointblank

    Data quality assessment and metadata reporting for data frames

    With the pointblank package it’s really easy to methodically validate your data whether in the form of data frames or as database tables. On top of the validation toolset, the package gives you the means to provide and keep up-to-date with the information that defines your tables. For table validation, the agent object works with a large collection of simple (yet powerful!) validation functions. We can enable much more sophisticated validation checks by using custom expressions, segmenting...
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  • 18
    Cleanlab

    Cleanlab

    The standard data-centric AI package for data quality and ML

    cleanlab helps you clean data and labels by automatically detecting issues in a ML dataset. To facilitate machine learning with messy, real-world data, this data-centric AI package uses your existing models to estimate dataset problems that can be fixed to train even better models. cleanlab cleans your data's labels via state-of-the-art confident learning algorithms, published in this paper and blog. See some of the datasets cleaned with cleanlab at labelerrors.com. This package helps you...
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  • 19
    Acl

    Acl

    A powerful server and network library, including coroutine

    The Acl (Advanced C/C++ Library) project a is powerful multi-platform network communication library and service framework, supporting LINUX, WIN32, Solaris, FreeBSD, MacOS, AndroidOS, iOS. Many applications written by Acl run on these devices with Linux, Windows, iPhone and Android and serve billions of users. There are some important modules in Acl project, including network communcation, server framework, application protocols, multiple coders, etc. The common protocols such as...
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  • 20
    JuiceFS

    JuiceFS

    JuiceFS is a distributed POSIX file system built on top of Redis

    A POSIX, HDFS and S3 compatible distributed file system for cloud. JuiceFS is designed to bring back the gold-old memories and experience of file systems in local disks to the cloud. JuiceFS is POSIX compliant and is fully compatible with HDFS and S3. Cloud app building or migrating, file sharing cross-geo and cross-cloud has become easier than ever before. Whether it's a public cloud, private cloud, or hybrid cloud, JuiceFS is available on any cloud of your choice and delivers flexibility,...
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  • 21
    AutoGluon

    AutoGluon

    AutoGluon: AutoML for Image, Text, and Tabular Data

    AutoGluon enables easy-to-use and easy-to-extend AutoML with a focus on automated stack ensembling, deep learning, and real-world applications spanning image, text, and tabular data. Intended for both ML beginners and experts, AutoGluon enables you to quickly prototype deep learning and classical ML solutions for your raw data with a few lines of code. Automatically utilize state-of-the-art techniques (where appropriate) without expert knowledge. Leverage automatic hyperparameter tuning,...
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  • 22
    PySyft

    PySyft

    Data science on data without acquiring a copy

    Most software libraries let you compute over the information you own and see inside of machines you control. However, this means that you cannot compute on information without first obtaining (at least partial) ownership of that information. It also means that you cannot compute using machines without first obtaining control over those machines. This is very limiting to human collaboration and systematically drives the centralization of data, because you cannot work with a bunch of data...
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  • 23
    HugeGraph

    HugeGraph

    A graph database that supports more than 100+ billion data

    HugeGraph is a convenient, efficient, and adaptable graph database compatible with the Apache TinkerPop3 framework and the Gremlin query language. HugeGraph supports fast import performance in the case of more than 10 billion Vertices and Edges Graph, millisecond-level OLTP query capability, and can be integrated into big data platforms like Hadoop or Spark for OLAP analysis. The main scenarios of HugeGraph include correlation search, fraud detection, and knowledge graph. Not only supports...
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  • 24
    SPX

    SPX

    A simple & straight-to-the-point PHP profiling extension

    SPX, which stands for Simple Profiling eXtension, is just another profiling extension for PHP. It differentiates itself from other similar extensions as being totally free and confined to your infrastructure (i.e. no data leaks to a SaaS). Very simple to use: just set an environment variable (command line) or switch on a radio button (web request) to profile your script. Thus, you are free of manually instrumenting your code (Ctrl-C a long running command line script is even supported)....
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  • 25
    SageMaker Training Toolkit

    SageMaker Training Toolkit

    Train machine learning models within Docker containers

    Train machine learning models within a Docker container using Amazon SageMaker. Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. To train a model, you can include your training script and dependencies in a Docker container that runs your training code. A container provides an effectively isolated environment, ensuring a consistent runtime and...
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