PawMate

The app was inspired as I have a dog myself and have often used the Rover app to connect with petsitters. I was inspired to use a similar approach to address the growing issue of pet adoption in the United States. Many pets are left without homes and are not adopted. Before using this project I had experience in only Python and Java. The developer workflow was very new to me and I had to learn a lot very fast. I had to learn some html and css, how to use apis, how to use github for collaboration, and how to implement databases using the flask library. I previously only had very elementary experience with working with data using filters so this was definitely a step up for me and a good learning opportunity. The app is built using Flask and backed by a SQLite database named pets.db. It provides two main user experiences: one for adoption centers and one for petsitters. On the adoption center side, users can post pets available for adoption by filling out details like name, age, breed, behavior, care level, and an address. That address is automatically converted into latitude and longitude using the Google Geocoding API, so we can store the pet’s location in a structured way. On the petsitter side, users can search for pets based on preferences like pet type, size, hypoallergenic status, breed, behavior, care level, and age. They also have the option to either let the app detect their location via their IP address — using a simple IP geolocation service — or manually enter an address or ZIP code. To match petsitters with nearby pets, the app uses the Google Distance Matrix API, which calculates the real driving distance between the petsitter’s location and each pet’s shelter address. The user can specify a search radius in either miles or kilometers. Behind the scenes, the database stores all the pet details along with their location coordinates, and each query filters pets based on both user-selected preferences and distance. Altogether, this app simplifies the process of finding compatible, nearby pets for petsitters who want to help out — and it gives adoption centers a more dynamic way to share their listings with local caregivers. The biggest challenge I faced during the development process was getting the google api to properly work and debugging the code. Another big problem I faced during the development process was ideating. We changed our idea 5 times till we decided on how we were going to set it up. Originally I was trying to look for a database of adoption center pets before realizing this was futile as a lot of shelters are unlikely to have this data available online. I then decided on a database approach where our pet data is user inputted and generated. This approach is far more dynamic and applicable on a larger scale as if this project is expanded then pet shelters can have a direct interface for getting their pets out there.

Built With

• css
• flask
• google-cloud
• html
• javascript
• python
• sqlite