Streamlit

Streamlit is an open-source Python framework that enables rapid development of interactive web applications for data analysis, visualization, and machine learning model presentation. Thanks to its simplicity and intuitive syntax, Streamlit is widely used by analysts, data scientists, and research teams.

1. Rapid Prototyping – Enables quick application development without requiring knowledge of HTML, CSS, or JavaScript.
2. Python Ecosystem Integration – Easy integration with popular libraries (Pandas, NumPy, Matplotlib, Plotly, scikit-learn, TensorFlow, PyTorch).
3. Interactivity – Ability to add interactive widgets (sliders, buttons, forms) without complex code.
4. Automatic Refresh – Code changes are immediately visible in the application through hot-reload functionality.
5. Easy Deployment – Simple deployment to Streamlit Community Cloud, on-premises servers, or cloud platforms (AWS, GCP, Azure).
6. Openness and Development – Active community, rapid development, and regular framework updates.

1. UI Customization Limitations – Fewer options for advanced appearance customization compared to frontend frameworks (React, Vue).
2. Limited Support for Advanced Web Applications – Streamlit works best for prototypes, dashboards, and analytical tools, but is not designed for building large, complex production systems.
3. Performance with High User Load – Performance limitations may arise with high traffic and multiple simultaneous users.
4. Python Ecosystem Dependency – The framework is primarily designed for Python-based applications.

Streamlit integrates with libraries for data analysis, machine learning, visualization, and model deployment tools (MLflow, DVC). Functionality can be extended using custom components (Streamlit Components) and integration with APIs and databases. Streamlit Community Cloud enables easy online application sharing.

• Dash: Dash (Plotly) offers greater customization capabilities and supports more complex applications, but Streamlit is simpler and faster for prototyping.
• Shiny: Shiny (R) is popular in the R environment, while Streamlit is the leader among Python tools.
• Gradio: Gradio focuses on rapid interface creation for ML models, while Streamlit is more versatile.

• IT Systems Maintenance and Development (web applications, internet services)
• Design and Programming Work (creating new functionalities, expanding existing systems)
• User Support and Software Engineering Consulting
• Software Quality Assessment (testing, audits, optimization)
• IT Project Management (project leadership, consultations, workshops)
• DevOps Services (server monitoring, updates, security, infrastructure maintenance)
• Custom Solution Design and Implementation (including system integrations)
• Business and Technology Consulting (analysis, recommendations, process optimization)
• Post-implementation and Service Support (hypercare, rapid response to issues, SLA)
• Graphic and UX/UI Work (for application and service development)