Python & Streamlit Expert-Python & Streamlit development help

Example

Optimizing a Python-based data pipelinePython Streamlit Expert Overview processing large datasets using Pandas. Instead of using inefficient loops, Python & Streamlit Expert would suggest vectorized operations, minimizing memory usage and maximizing processing speed.

Scenario

Imagine a company handling large-scale customer transaction data. The pipeline initially uses loops to process and analyze the data, causing significant delays. Python & Streamlit Expert would recommend transitioning to vectorized operations or the use of Dask for distributed computing, thus speeding up the process and handling larger datasets more efficiently.

Example

In a data-heavy project, Python & Streamlit Expert would suggest breaking the app into modular components—using the Model-View-Controller (MVC) design pattern to improve maintainability and scalability.

Scenario

A startup is building a product recommendation system with Streamlit for the front end and Python for the backend. As the app grows, the architecture becomes increasingly hard to manage. Python & Streamlit Expert would guide them in re-organizing the code, separating concerns by using MVC architecture and integrating microservices to make the system more scalable.

Example

A messy codebase with deep nesting and long functions would be refactored to follow the SOLID principles, breaking down complex functions into smaller, reusable components.

Scenario

A team is working on a Streamlit app that predicts stock prices. Over time, the codebase becomes cluttered, making it difficult to add new features. Python & Streamlit Expert would guide the team in refactoring the code to follow SOLID principles, improving the readability and maintainability of the code while making it easier to scale the app with new features.