Question 1

How do I deploy TacoFancy API to a cloud server like AWS?

Accepted Answer

Use the provided Docker image to containerize the API, then deploy it to services like AWS ECS or Google Cloud Run, ensuring you set environment variables like DATABASE_URL and optionally GITHUB_TOKEN for data loading.

Question 2

Can I add my own recipes to TacoFancy API?

Accepted Answer

No, the API is read-only and pulls data from the TacoFancy GitHub repo. To modify recipes, you'd need to fork the data repository and adjust the API's data source or extend its functionality yourself.

Question 3

What's the difference between TacoFancy API and Spoonacular API?

Accepted Answer

TacoFancy API is free, self-hosted, and niche-focused on taco recipes from a community repo, while Spoonacular is a commercial, comprehensive food API with paid plans, real-time data, and broader recipe coverage.

Question 4

How often does TacoFancy API update its recipe data?

Accepted Answer

Updates are not automatic; you must run 'make load-data' manually or on a schedule to fetch new data from GitHub, so it's best for static or infrequently changing datasets.

Question 5

Do I need a GitHub token to run TacoFancy API locally?

Accepted Answer

A GitHub token is optional but recommended to avoid rate limits when loading data. Without it, initial data fetch might be slower or limited, but basic API functionality still works once data is loaded.

Question 6

Is TacoFancy API good for a mobile app backend?

Accepted Answer

Yes, for prototyping or small-scale apps, but for production with high traffic, you'll need to handle scaling, caching, and ensure the self-hosted instance is reliable and performant.

tacofancy-api

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