9 projects for "json-cpp" with 2 filters applied:

  • Gen AI apps are built with MongoDB Atlas Icon
    Gen AI apps are built with MongoDB Atlas

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  • 1
    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 boilerplate. It also supports Redshift, OpenSearch, and other services, enabling ETL tasks that blend SQL engines and Python transformations. ...
    Downloads: 0 This Week
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  • 2
    Acl

    Acl

    A powerful server and network library, including coroutine

    ...There are some important modules in Acl project, including network communcation, server framework, application protocols, multiple coders, etc. The common protocols such as HTTP/SMTP/ICMP//MQTT/Redis/Memcached/Beanstalk/Handler Socket are implemented in Acl, and the codec library such as XML/JSON/MIME/BASE64/UUCODE/QPCODE/RFC2047/RFC1035, etc., are also included in Acl. Acl also provides a unified abstract interface for popular databases such as Mysql, Postgresql, Sqlite. Using Acl library users can write database applications more easily, quickly and safely.
    Downloads: 4 This Week
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  • 3

    GETL

    ETL engine based on Groovy

    P.S. Dear friends. Repository migration to https://github.com/ascrus/getl . You can download jar file from this site or maven. GETL - based package in Groovy, which automates the work of loading and transforming data. His name is an acronym for «Groovy ETL». GETL is a set of libraries of pre-built classes and objects that can be used to solve problems unpacking, transform and load data into programs written in Groovy, or Java, as well as from any software that supports the work with...
    Downloads: 9 This Week
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  • 4
    HiPlot

    HiPlot

    HiPlot makes understanding high dimensional data easy

    ...Its core view is a parallel-coordinates plot that lets you brush, filter, and highlight runs to spot trade-offs, correlations, and Pareto fronts at a glance. You can load results from simple CSV/JSON logs or programmatically push “experiments” with typed fields, metrics, and tags. The UI supports dynamic filtering, color mapping, and tooltip details so you can iteratively narrow to the most promising configurations. Because it renders as self-contained HTML, you can embed the visualization in notebooks, export it, or serve it as a lightweight web app for teammates. ...
    Downloads: 0 This Week
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  • Keep company data safe with Chrome Enterprise Icon
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    Protect your business with AI policies and data loss prevention in the browser

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  • 5
    CloverDX

    CloverDX

    Design, automate, operate and publish data pipelines at scale

    ...Data integration platform; can be used to transform/map/manipulate data in batch and near-realtime modes. Suppors various input/output formats (CSV,FIXLEN,Excel,XML,JSON,Parquet, Avro,EDI/X12,HL7,COBOL,LOTUS, etc.). Connects to RDBMS/JMS/Kafka/SOAP/Rest/LDAP/S3/HTTP/FTP/ZIP/TAR. CloverDX offers 100+ specialized components which can be further extended by creation of "macros" - subgraphs - and libraries, shareable with 3rd parties. Simple data manipulation jobs can be created visually. More complex business logic can be implemented using Clover's domain-specific-language CTL, in Java or languages like Python or JavaScript. ...
    Downloads: 3 This Week
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  • 6
    apache spark data pipeline osDQ

    apache spark data pipeline osDQ

    osDQ dedicated to create apache spark based data pipeline using JSON

    This is an offshoot project of open source data quality (osDQ) project https://sourceforge.net/projects/dataquality/ This sub project will create apache spark based data pipeline where JSON based metadata (file) will be used to run data processing , data pipeline , data quality and data preparation and data modeling features for big data. This uses java API of apache spark. It can run in local mode also. Get json example at https://github.com/arrahtech/osdq-spark How to run Unzip the zip file Windows : java -cp ....
    Downloads: 0 This Week
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  • 7
    XAware Data Integration Project

    XAware Data Integration Project

    Create XML and JSON data services from any data source

    Create services to integrate applications & move data of any type. Build data views across DBMS, SOAP, HTTP/REST, Salesforce, SAP, Microsoft, SharePoint, Text, LDAP, FTP sources to read, write & transfer data. Eclipse designer & run-time engine.
    Downloads: 0 This Week
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  • 8
    OpenSearchServer Extractor

    OpenSearchServer Extractor

    A RESTFul/JSON Web Service for text and metata extraction

    An open source RESTFul Web Service for text , meta-data extraction and analysis. oss-text-extractor supports various binary formats: Word processor (doc, docx, odt, rtf) Spreadsheet (xls, xlsx, ods) Presentation (ppt, pptx, odp) Publishing (pdf, pub) Web (rss, html/xhtml) Medias (audio, images) Others (vsd, text)
    Downloads: 0 This Week
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  • 9
    MixDEM
    MixDEM a web based ETL tools meant for Web integration, Data transformation and Mashup edition. It include MixDEM ETL Engine created using ZEND Framework, and MixDEM GUI Editor an AJAX IDE that enable developers to quickly and easily create applications.
    Downloads: 0 This Week
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  • Junie, the AI coding agent by JetBrains Icon
    Junie, the AI coding agent by JetBrains

    Your smart coding agent

    Junie is an AI-powered coding agent developed by JetBrains designed to enhance developer productivity by integrating directly into popular IDEs such as IntelliJ IDEA, PyCharm, and Android Studio. It supports developers by assisting with code completion, testing, and inspections, ensuring code quality and reducing debugging time.
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