What is the difference between stochastic process and random variable? I am having a hard time grasping the core difference between a random variable and a stochastic process.

A random variable assigns a number to every outcome of an experiment.
A random process assigns a function of time to every outcome of an experiment.
But the values of this function of time can be represented with ONE SINGLE random variable as well. So what is the point in having a stochastic process when you can represent an experiment with only random variables? Could somebody make one or two examples where the difference is clear?

Appreciate it
A stochastic process is a family of random variables indexed by some set, usually $\mathbb{Z}^{n}$ or $\mathbb{R}^{n}$.
It's additional structure over random variables that let you establish notions of trajectories, association over a space and other interesting properties.
In empirical studies, the set may represent discrete time ($\mathbb{Z}$), continuous time ($\mathbb{R}$), geographical location in a map on a given discrete time ($\mathbb{R}^2 \times \mathbb{Z}$) and et cetera.
A random process is a function, for instance a random walk over the plane.
A random variable has a value, for instance the average distance of the random walk after a specified number of steps.