Inspiration & About the Project:

Finding the right healthcare service can be confusing and time-consuming, especially for people who aren't sure where to go (AKA me). Many communities struggle to locate nearby hospitals, clinics, or specialists quickly. "Healthcare Helper" solves this problem by providing an easy-to-use application that allows users to search for nearby healthcare services and view essential details such as distance, address, and type of service. This helps users make informed decisions and access care faster.

How I Built It:

Using Python and Streamlit, alongside Geopy and Geoapify APIs, I developed an application that finds nearby healthcare services based on a user's city, zip code, or address. Copilot and ChatGPT were utilized to make planning, designing, implementing, and testing the application easy and efficient. They assisted with debugging, generating ideas, and explaining code when needed. Additionally, API and Streamlit documentation, along with general research, were consulted to complete the project.

Challenges & Solutions:

Many challenges arose during this project. The main obstacles included identifying a problem in the community and addressing it through the application, utilizing specific Streamlit features, connecting with APIs, ensuring correct results from the API, and handling edge cases. Various tools were used to overcome these challenges. Extensive research, careful planning and designing, and consulting with knowledgeable individuals were extremely helpful. Additionally, thoroughly reading the documentation made understanding and implementing the code much easier. As the project progressed, new edge cases emerged, which required careful consideration to prevent issues for end users.

What I Learned:

I learned a lot from developing this project on my own and accomplished quite a bit. Not only does my project work (yay!), but it's also useful to the community, simple to use, powered by real-world data, and, of course, looks great.

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