martno96 / r-mapper Goto Github PK

A tool for aspiring writers to map out the core relationships in their casts of characters.

https://r-mapper.netlify.app

The user can create an account or sign in to an existing one. Users currently only have one Cast to edit.

They interact with their Cast by:

creating new Characters, which will automatically add them to the relationship map. creating new Bonds between added Characters. These too will be drawn on the map automatically. freely dragging Characters around on the map deleting Characters (see Character accordions below) deleting Bonds (see Bond accordions below) saving the Cast to the server The user can also browse their Characters in list form via the expandable Character and Bond accordions, containing character bios and fuller Bond descriptions respectively.

Tech used

React Redux JointJS diagramming library Node.js Express Heroku MongoDB Netlify

I started the project by conducting user interviews with my aspiring writer friends, the goal being to find what kind of features they’d have an interest in. I used the design methodology of Design Thinking as a basis for this. My findings were interesting, but unfortunately the resulting design ended up outside of the project scope, much due to not finding suitable and sufficiently well-documented libraries to support it.

As such I proceeded with the concept you see here, a character relationship mapping tool using the JointJS library. However, I vastly underestimated how different and more complex JointJS’s data structure is compared to React or Redux. I’ve thus had to cut back on a lot of functionality, which will have to be implemented at a later time.

Don’t underestimate the complexity of new libraries. Accurate planning is very difficult, if not impossible, before having properly familiarized myself with the tools. Building appropriate data structures is also hard before knowing how all the libraries work. In the future, I need to research and experiment with the tools more up-front before proceeding, lest I build structures ill fitted for the types of data I handle. I work better in a team than I do alone, especially over time, because the social context helps motivate me and forces me to articulate what I otherwise might not realize.