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Tech Stack

This tech stack provides powerful and scalable tools for building and managing applications, databases, workflows, and user interfaces. Additionally, it simplifies dependency management, improves consistency in design, and provides features for data science, making it an efficient and effective solution for our business needs.

🐳 Containerization​

  • Docker: An open platform for developing, shipping, and running applications.
  • Docker Compose: A tool for defining and running multi-container Docker applications.
  • Kubernetes: An open-source container-orchestration system for automating application deployment, scaling, and management.

🗄️ Databases​

  • PostgreSQL: A powerful, open-source relational database system known for its scalability, reliability, and extensive features that support advanced database functionality.
  • sqlite3: A lightweight and easy-to-use database engine that is ideal for small-scale or embedded applications.
  • Redis: An open-source, in-memory data structure store, used as a database, cache, and message broker.
  • Neo4j: A graph database management system that uses graph structures to store and manage data, allowing for efficient querying and analysis of complex relationships.

🐍 Backend Frameworks​

  • Django: A high-level Python web framework that enables rapid development of secure and maintainable websites, providing a robust set of tools for building web applications.
  • prefect: An open-source workflow management system that helps users build, schedule, and monitor data pipelines.
  • FastAPI: A modern, fast (high-performance), web framework for building APIs with Python 3.6+ based on standard Python type hints.
  • Dask: A flexible library for parallel computing in Python that makes scaling out your workflow smooth and simple.

📦 Package Managers​

  • poetry: A modern package manager for Python that simplifies dependency management and project distribution.
  • yarn: A fast, reliable, and secure package manager for JavaScript that optimizes the installation and update process of packages.
  • conda: A package manager that specializes in managing dependencies for data science and machine learning projects.

🌐 Frontend Frameworks​

  • React: A popular JavaScript library for building user interfaces that allows developers to create reusable components and manage state efficiently.
  • Next.js: A React framework that provides server-side rendering and automatic code splitting, making it easy to build performant and SEO-friendly web applications.
  • docusaurus: A tool for building, deploying, and maintaining documentation websites.
  • Vite: A build tool that serves your code via native ES Module imports during development for a faster and leaner development experience. It also offers a production build that bundles your code with Rollup for maximum performance.

🎨 CSS Frameworks​

  • Tailwind CSS: A utility-first CSS framework that provides a set of pre-defined styles and classes to simplify the styling process and improve the consistency of the design.
  • PrimeReact: A collection of rich UI components for React that provides a robust set of features, including accessibility, internationalization, and customization options.
  • daisyui: A CSS framework that provides a set of pre-defined styles and classes to simplify the styling process and improve the consistency of the design, specifically for Tailwind CSS.

🛠️ Development Tools​

  • Storybook: A tool for developing UI components in isolation for React, Vue, and Angular.

🔬 Data Science​

  • Jupyter Notebooks: A web application that allows users to create and share documents that contain live code, equations, visualizations, and narrative text.
  • panel: A Python library that provides a high-level app and dashboarding solution for Python that lets users build complex, reactive, and customizable apps entirely in Python.
  • Pandas: A Python library that provides high-performance, easy-to-use data structures and data analysis tools.
  • NumPy: A Python library that provides a high-performance multidimensional array object and tools for working with these arrays.
  • scikit-learn: A Python library that provides a range of supervised and unsupervised learning algorithms for data mining and data analysis.