Products

The Python Connector for Google BigQuery is a robust and efficient solution designed to facilitate seamless interaction between Python applications and the Google BigQuery data warehouse. Fully implementing the Python DB API 2.0 specification, this connector enables developers to perform create, read, update, and delete operations on BigQuery data with ease. Distributed as a wheel package, it supports both 32-bit and 64-bit versions of Windows and Windows Server, ensuring broad compatibility acr

PAW Python Automation Workflow is a visual platform for building Python workflows via a graphical editor. It supports conditional logic, loops, JSON transformations, HTTP requests, and sandboxed Python execution. Using a distributed architecture, it routes intensive tasks to GPU workers when available, alongside CPU processing via Celery queues. AI features include knowledge bases, retrieval-augmented generation, and AI nodes with quality checks before deployment. Multi-tenant structures enable

It is closer to Apache Lucene than to Elasticsearch or Apache Solr in the sense it is not an off-the-shelf search engine server, but rather a crate that can be used to build such a search engine. Companies like Element, Humanfirst, and Nuclia have used Tantivy to unleash the horse-powers in their search queries. There are many ways to use Tantivy. Tantivy can be run in the browser with a WASM file. For Ruby-lovers, Tantiny offers close Ruby bindings for Tantivy . Lastly, you can install

Appliku is a managed deployment platform for Django and Python teams (FastAPI, Rails, and Next.js too). You get the Heroku experience, git push to deploy, managed Postgres and Redis, background workers, automatic SSL and Nginx, but your app runs on a server you own, on any cloud (DigitalOcean, AWS, Hetzner, or any VPS). The difference from hosted platforms: you keep control of cost and avoid vendor lock-in, because you bring your own cloud account and pay the provider directly. The difference f

DataClarity Unlimited Analytics is the only free modern embeddable data and analytics platform in the world that provides a self-service, powerful, secure and seamless end-to-end experience. DataClarity Unlimited Analytics Highlights · Simplified Data Integration – Easily connect, join, curate, cache, and catalog diverse data through drag and drop experience, custom SQL builder, and AI-powered data profiling. · Interactive Storyboards – Craft compelling storyboards using 80 stunning visualizatio

EmailShield is an email verification and deliverability platform that guarantees 99.8% verified accuracy through real SMTP handshakes - not DNS-only lookups used by legacy tools. Multi-step verification includes syntax checks, MX record validation, and real-time mailbox existence confirmation without sending actual emails. Bulk processing handles up to 100,000 emails per minute. The platform runs on self-hosted proxy infrastructure with zero third-party dependencies and rotating egress IPs. Fea

CubicWeb is a semantic web application framework, licensed under the LGPL, that empowers developers to efficiently build web applications by reusing components (called cubes) and following the well known object-oriented design principles.

UEStudio is a comprehensive development environment built upon the robust foundation of UltraEdit, tailored specifically for developers and teams requiring advanced Git integration and project management capabilities. It combines powerful text editing features with native support for version control systems, streamlining the development workflow within a single application. Key Features and Functionality: - Integrated Git Support: Manage Git repositories directly within UEStudio, enabling clon

Theano, a numerical computation library for Python, and Python, a high-level programming language for general-purpose programming

The MXNet 1 Python 3.6 CPU Production environment is a pre-configured software stack that integrates Apache MXNet, an open-source deep learning framework, with Python 3.6. This setup offers a stable and tested execution environment optimized for CPU-based tasks, facilitating efficient training, inference, and deployment of deep learning models. It is designed to seamlessly integrate into continuous integration and deployment workflows, making it suitable for both short and long-running high-perf

The "Python 2.7 on Ubuntu 20.04 LTS" Amazon Machine Image (AMI) offers a pre-configured environment combining Python 2.7 with Ubuntu 20.04 LTS. This setup is tailored for users who require Python 2.7 for legacy applications while benefiting from the stability and features of Ubuntu 20.04 LTS. Key Features and Functionality: - Pre-Installed Python 2.7: Provides immediate access to Python 2.7, eliminating the need for manual installation. - Ubuntu 20.04 LTS Base: Leverages the long-term support

The "Python 2 with CentOS 7.8" Amazon Machine Image (AMI) offers a pre-configured environment combining CentOS 7.8 with Python 2.7.18. This setup is tailored for developers and organizations needing to maintain legacy Python 2 applications on a stable and widely-used Linux distribution. Key Features and Functionality: - CentOS 7.8 Base: Provides a reliable and secure operating system foundation, ensuring compatibility with a vast array of enterprise applications. - Python 2.7.18 Pre-installed

The "MXNet 1 Python 2.7 CPU Production" is an Amazon Machine Image designed to facilitate the development and deployment of deep learning models using Apache MXNet on Amazon EC2 instances. This AMI is pre-configured with MXNet version 1.x and Python 2.7, optimized for CPU-based computations, providing a ready-to-use environment for machine learning practitioners. Key Features and Functionality: - Pre-Installed MXNet Framework: The AMI comes with Apache MXNet 1.x, an open-source deep learning f

The "Python 2 with CentOS 8.2" offering provides a pre-configured Amazon Machine Image (AMI) that combines CentOS 8.2, a robust and secure Linux distribution, with Python 2.7, a widely-used programming language. This AMI is designed to facilitate the deployment of applications that depend on Python 2.7, ensuring compatibility and stability for legacy systems. Key Features and Functionality: - Pre-Installed Python 2.7: The AMI comes with Python 2.7 pre-installed, allowing immediate development

The "Caffe Python 2.7 NVidia GPU Production" is a pre-configured Amazon Machine Image (AMI) designed to facilitate the development and deployment of deep learning applications using the Caffe framework. This AMI integrates Python 2.7 and is optimized for NVIDIA GPU acceleration, providing a robust environment for training and deploying convolutional neural networks (CNNs and other deep learning models. Key Features and Functionality: - Pre-Installed Caffe Framework: Offers a ready-to-use setup

The "Caffe Python 3.6 CPU Production on Ubuntu" is an Amazon Machine Image (AMI) designed to provide a ready-to-use environment for deploying and running deep learning applications using the Caffe framework on Ubuntu. This AMI is tailored for CPU-based computations, making it suitable for users who prefer or require CPU processing over GPU acceleration. Key Features and Functionality: - Preconfigured Environment: The AMI comes with Caffe and Python 3.6 fully installed and configured, allowing

The "Python 2 with Ubuntu 20.04 LTS" offering provides a pre-configured Amazon Machine Image (AMI) that combines Python 2.7 with Ubuntu 20.04 LTS. This setup is tailored for developers and organizations that require Python 2.7 for legacy applications while benefiting from the stability and security features of Ubuntu 20.04 LTS. By deploying this AMI on AWS, users can efficiently run and maintain their Python 2-based applications in a cloud environment. Key Features and Functionality: - Pre-Con

Python 2.7 with Ubuntu 18.04 LTS, offered by Cognosys Inc., is a pre-configured Amazon Machine Image (AMI) designed to facilitate seamless development and deployment of applications. This solution combines the versatility of Python 2.7 with the stability of Ubuntu 18.04 LTS, providing developers with a robust environment for building and running various software applications. Key Features and Functionality: - Pre-Configured Environment: The AMI comes with Python 2.7 and Ubuntu 18.04 LTS pre-in

The MySQL and MariaDB Python Connector by Devart is a robust and user-friendly solution designed to facilitate seamless interaction between Python applications and MySQL or MariaDB database servers. Fully implementing the Python DB API 2.0 specification, this connector enables developers to perform create, read, update, and delete operations efficiently. Distributed as a wheel package, it supports multiple platforms, including Windows, macOS, and Linux. Key Features and Functionality: - Direct

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