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Test Automation Frameworks
Test automation frameworks are sets of tools, components, and practices that automate the process of testing software applications. These frameworks enable testers to write, execute, and manage test scripts for various types of software testing, including functional, regression, load, and performance testing. They often provide features such as reusable test scripts, integration with continuous integration/continuous deployment (CI/CD) tools, reporting, and test result tracking. Test automation frameworks help improve test efficiency, reduce manual errors, and speed up the overall testing process, especially in large and complex software environments.
Development Frameworks
Development frameworks are code libraries and development tools that streamline the development process for developers that build applications. Development frameworks simplify the process of programming in different languages. There are a variety of different types of development frameworks including web development frameworks, mobile app development frameworks, frontend and backend frameworks, and more.
Agentic Frameworks Software
Agentic frameworks are systems designed to build and manage autonomous or semi-autonomous artificial intelligence (AI) agents that can make decisions, interact with their environment, and perform tasks without constant human oversight. These frameworks provide the underlying structure for designing, training, and optimizing AI agents, enabling them to learn from experience, adapt to new situations, and make decisions based on predefined goals or objectives.
Mobile App Development Frameworks Software
Mobile app development frameworks are tools and libraries designed to streamline the creation of mobile applications by providing pre-written code, templates, and components. These frameworks can target different platforms, such as iOS, Android, or cross-platform environments, enabling developers to write once and deploy to multiple devices. Popular mobile development frameworks offer flexibility, efficiency, and robust user experiences.
Data Science Software
Data science software is a collection of tools and platforms designed to facilitate the analysis, interpretation, and visualization of large datasets, helping data scientists derive insights and build predictive models. These tools support various data science processes, including data cleaning, statistical analysis, machine learning, deep learning, and data visualization. Common features of data science software include data manipulation, algorithm libraries, model training environments, and integration with big data solutions. Data science software is widely used across industries like finance, healthcare, marketing, and technology to improve decision-making, optimize processes, and predict trends.
Augmented Reality Software
Augmented reality software is used to create interactive computer-generated 3D models and simulations that can be projected and manipulated.
Computer Vision Software
Computer vision software allows machines to interpret and analyze visual data from images or videos, enabling applications like object detection, image recognition, and video analysis. It utilizes advanced algorithms and deep learning techniques to understand and classify visual information, often mimicking human vision processes. These tools are essential in fields like autonomous vehicles, facial recognition, medical imaging, and augmented reality, where accurate interpretation of visual input is crucial. Computer vision software often includes features for image preprocessing, feature extraction, and model training to improve the accuracy of visual analysis. Overall, it enables machines to "see" and make informed decisions based on visual data, revolutionizing industries with automation and intelligence.
AI Coding Assistants
AI coding assistants are software tools that use artificial intelligence to help developers write, debug, and optimize code more efficiently. These assistants typically offer features like code auto-completion, error detection, suggestion of best practices, and code refactoring. AI coding assistants often integrate with integrated development environments (IDEs) and code editors to provide real-time feedback and recommendations based on the context of the code being written. By leveraging machine learning and natural language processing, these tools can help developers increase productivity, reduce errors, and learn new programming techniques.
Scrum Software
Scrum software provides IT project managers with the tools to manage projects, solve issues, and optimize the productivity of developer teams.
Integrated Risk Management Software
Integrated risk management (IRM) software helps organizations identify, assess, and manage risks across various departments and operations in a centralized system. It combines tools for risk assessment, compliance management, incident reporting, and risk mitigation into one platform, enabling seamless data sharing and collaboration. IRM software allows businesses to prioritize risks based on their potential impact and likelihood, offering real-time insights into risk trends. With features like automated workflows, dashboards, and analytics, it helps organizations streamline decision-making and enhance their risk response strategies. Ultimately, IRM software provides a comprehensive view of risk across the enterprise, enabling businesses to proactively address threats and ensure regulatory compliance.
No-Code Development Platforms
No-code development platforms provide a way for users to design, build, and develop software applications without the need for traditional coding. They are built in such a way that users can rely on simple visual interfaces with drag and drop type tools, allowing them to rapidly develop applications with minimal technical knowledge. This makes no-code development platforms ideal for any user regardless of programming experience, from hobbyists to entrepreneurs. Furthermore, modern no-code platforms allow complex mobile apps or web projects to be created more quickly than ever before.
Serverless Platforms
Serverless platforms are cloud computing services that allow developers to build and deploy applications without managing the underlying infrastructure, such as servers or virtual machines. These platforms automatically handle the scaling, provisioning, and maintenance of resources, allowing developers to focus on writing code and implementing business logic. Serverless platforms typically provide a pay-as-you-go pricing model, where users only pay for the actual resources used during execution rather than for idle time. Features of serverless platforms include automatic scaling, event-driven architecture, and support for various programming languages and services. Popular serverless platforms are commonly used for web applications, microservices, APIs, and data processing.
Code Search Engines
Code search engines are specialized search tools that allow developers to search through codebases, repositories, or libraries to find specific functions, variables, classes, or code snippets. These tools are designed to help developers quickly locate relevant parts of code, analyze code quality, and identify reusable components. Code search engines often support various programming languages, providing search capabilities like syntax highlighting, filtering by file types or attributes, and even advanced search options using regular expressions. They are particularly useful for navigating large codebases, enhancing code reuse, and improving overall productivity in software development projects.
Load Testing Tools
Load testing tools are used to test and verify the quality and performance of an application under workload in order to get rid of problems.
Component Libraries
Component libraries are preconfigured sets of components, designs, styles, and code that enable developers and designers to build and design applications in a more efficient and streamlined way. A component library, also known as a UI component library, can be used across programming languages and frameworks to speed up and simplify design and development.
Package Managers
Package managers are software tools that automate the process of installing, upgrading, configuring, and removing software packages. They simplify dependency management by ensuring that required libraries and modules are downloaded and updated correctly. Many package managers connect to online repositories, allowing developers and system administrators to access large ecosystems of software quickly. By standardizing installations and updates, they reduce errors, improve consistency, and save time in both development and production environments. Package managers are widely used across programming languages, operating systems, and frameworks to streamline software distribution and maintenance.
System Utilities
System utilities are specialized software tools designed to maintain, manage, and optimize computer systems. They assist with essential tasks such as file management, disk cleanup, backup, performance monitoring, and troubleshooting. Unlike applications built for end-user productivity, system utilities work behind the scenes to improve efficiency, stability, and security of the operating system. They can be built into the OS or installed as third-party tools to extend functionality. By automating maintenance and diagnostic tasks, system utilities help prolong system lifespan and ensure smooth day-to-day operations.
View more categories (17) for "python framework"

8 Products for "python framework" with 1 filter applied:

  • 1
    Conda

    Conda

    Conda

    ...It was created for Python programs, but it can package and distribute software for any language. Conda as a package manager helps you find and install packages. If you need a package that requires a different version of Python, you do not need to switch to a different environment manager, because conda is also an environment manager. With just a few commands, you can set up a totally separate environment to run that different version of Python, while continuing to run your usual version of Python in your normal environment.
    Starting Price: Free
  • 2
    PyPI

    PyPI

    PyPI

    PyPI is the official repository for Python software packages, hosting hundreds of thousands of projects that developers can publish and users can discover and install. It supports both source distributions (“sdists”) and pre-built binary “wheels”, allowing packages to include native extensions for different platforms. Projects on PyPI consist of multiple releases, each of which can include various files for different operating systems or Python versions.
    Starting Price: Free
  • 3
    pkgsrc

    pkgsrc

    pkgsrc

    ...It can be easily used to complement the software on an existing system. pkgsrc is very versatile and configurable, supporting building packages for an arbitrary installation prefix, allowing multiple branches to coexist on one machine, a build options framework, and a compiler transformation framework, among other advanced features. Unprivileged use and installation are also supported. NetBSD already contains the necessary tools for using pkgsrc; on other platforms, you need to bootstrap pkgsrc to get the package management tools installed.
    Starting Price: Free
  • 4
    fpm

    fpm

    fpm

    ...Some package formats require other tools to be installed on your machine to be built; especially if you are building a package for another operating system/distribution. FPM takes your program and builds packages that can be installed easily on various operating systems. It can take any nodejs package, ruby gem, or even a python package and turn it into a deb, rpm, pacman, etc. package.
    Starting Price: Free
  • 5
    AWS CodeArtifact
    ...Only pay for software packages stored, number of requests made, and data transferred out of Region with pay-as-you-go pricing. Configure CodeArtifact to fetch from public repositories such as the npm Registry, Maven Central, Python Package Index (PyPI), and NuGet. Securely share private packages across organizations by publishing them to a central organizational repository. Build automated approval workflows with CodeArtifact APIs and Amazon EventBridge, with visibility into your packages using AWS CloudTrail. Pull dependencies from CodeArtifact in AWS CodeBuild and publish new versions of your private packages secured with AWS Identity and Access Management (IAM).
    Starting Price: $0.05 per GB per month
  • 6
    Google Cloud Artifact Registry
    Artifact Registry is Google Cloud’s unified, fully managed package and container registry designed for high-performance artifact storage and dependency management. It centralizes host­ing of container images (Docker/OCI), Helm charts, language packages (Java/Maven, Node.js/npm, Python), and OS packages, offering fast, scalable, reliable, and secure handling with built-in vulnerability scanning and IAM-based access control. Integrated seamlessly with Google Cloud CI/CD tools like Cloud Build, Cloud Run, GKE, Compute Engine, and App Engine, it supports regional and virtual repositories with granular security via VPC Service Controls and customer-managed encryption keys. ...
  • 7
    Posit

    Posit

    Posit

    Posit builds tools that help data scientists work more efficiently, collaborate seamlessly, and share insights securely across their organizations. Its Positron code editor provides the speed of an interactive console combined with the power to build, debug, and deploy data-science workflows in Python and R. Posit’s platform enables teams to scale open-source data science, offering enterprise-ready capabilities for publishing, sharing, and operationalizing applications. Companies rely on Posit’s secure infrastructure to host Shiny apps, dashboards, APIs, and analytical reports with confidence. Whether using open-source packages or cloud-based solutions, Posit supports reproducible, high-quality work at every stage of the data lifecycle. ...
  • 8
    Rudix

    Rudix

    Rudix

    ...The build system (also called "ports") provides step-by-step instructions for building third-party software, entirely from source code. Rudix provides more than a pure ports framework, it comes with packages, and precompiled software bundled up in a nice format (files *.pkg) for easy installation on your Mac. If you want to collaborate on the project, visit us at GitHub/rudix-mac or at our mirror at GitLab/rudix. Use the GitHub issue tracker to submit bugs or request features. Similar projects or alternatives to Rudix are Fink, MacPorts, pkgsrc, and Homebrew. ...
    Starting Price: Free
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