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Simulate evolution of dinosaurs and avocado trees

Project description

Dinosaur Dilemma

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This is the dinosaur dilemma, my first attempt at a simulation. It will involve characters, interactions, and variables that control those interactions. The characters will interact in a basic world and at the end, we will be interested to know how they turned out (evolved). You can see a verbose simulation run here, or a less verbose run below:




You can install from pip, or directly from the repository here.

pip install dinolemma


git clone
cd dinosaur-dilemma
python install

If you want to use the GUI you will need pygame. Any of the following will work.

pip install .[game]
pip install dinolemma[game]
pip install pygame


You can run a text simulation (with defaults) from the command line:

$ dinolemma run
Today is day 80 in the winter season.
There are 5 dinosaurs, and 13 avocado trees.
The temperate is 12°F, humidity 0.33

or a (more fun) graphical simulation (press enter to cycle through days):

dinolemma gui

The gui takes the same input parameters as the run.

dinolemma gui --help
usage: dinolemma gui [-h] [--ndinos NDINOS] [--ntrees NTREES]
                     [--grid_size GRID_SIZE]

optional arguments:
  -h, --help            show this help message and exit
  --ndinos NDINOS       the number of dinosaurs to simulate.
  --ntrees NTREES       the number of avocado trees to simulate.
  --grid_size GRID_SIZE
                        the size of the square grid, in units (one dimension).

If you want a more interesting simulation, try adding a lot more dinosaurs or trees!

dinolemma gui --ndinos 100 --ntrees 30

What you'll likely see given those ratios are that the dinosaurs (purple) eat one another (or starve) and then the trees (green) grow to take up the game board.


You can run a simulation from within Python, either using the defaults:

from import DinosaurDilemma                              

simulation = DinosaurDilemma()                                          
Today is day 13 in the summer season.
There are 1 dinosaurs, and 14 avocado trees.
The temperate is 59°F, humidity 0.43

or by setting any of the variables (number of dinosaurs or trees, size of grid, etc.)


The way that I'm thinking about this project is in stages.

Stage 1: Stateful

1. Environment

The first thing to design is the environment, meaning a stateful base that has a set of variables (e.g., temperature, humidity) that will vary on some regular increment and then influence the entities that live in it downstream. For example, a base environment might be defined by a season and day that leads to a particular temperature that has downstream influences on the organisms that live in it. If my environment has a function to cycle through a unit (e.g., a day) then I can update it's state, and then update the entities in it depending on the new state.

2. Entities

Once the environment is defined, the next level of stateful objects must be defined, the entities that live within the environment. The entities should first update themselves based on the changed environment, and then interact. Interaction comes down to each entity changing location on some grid, and if the location is in the vicinity of another organism, then the interaction occurs. I thought about whether I wanted all entities to move (and then interact) versus allowing them to interact as they move, and I chose the latter. The reason is because we would allow for multiple interactions for any given entity in one turn, and that's more interesting. To be fair, I have to ensure that the order of movement is randomized. And notably, avocado trees cannot move.

3. Interactions

Every entity must have defined rules for interaction with other entities. When all entities in the simulation change location, those that are within some vicinity of one another are allowed to interact. Interaction can further influence the state of the entity, or even lead to creation or destruction of said entity.

At the end of the design of stage 1, we will have developed essentially a text based, stateful simulation. We will be able to run it with some set of starting conditions, and then observe the interactions over a particular number of time steps (days) and some final outcome.

Stage 2: Graphical

Once the stateful simulation is designed, we should strive to visualize it. This means (possibly) re-implementation in a browser based language that can render objects on a canvas or via the dom (d3.js). We would want to be able to run the same text based simulation, and watch it.

Stage 3: Live

The stateful approach works for early design, but what we would really want is essentially a bunch of entities that are co-existing in an environment, and then reacting to one another. I think we could try to emulate this with something that looks more like a bunch of objects that can emit and subscribe to one another's events, and then know how to respond.



Dinosaurs are the main character in this world, and we initialize the world with some number. Specifically, a dinosaur wanders around and has the following attributes:

  • hunger: each dinosaur is hungry, and gets more hungry as the simulation progresses. If the dinosaur enconuters a ripe avocado, he will eat it and the hunger subside. Each dinosaur has a slightly different threshold for deciding to eat.
  • size: each dinosaur has a randomly set size. A larger dinosaur is obviously requiring more food than a smaller one, and a larger one is also advantaged to be able to eat a smaller dinosaur, if desperate.
  • disease: if a dinosaur is hungry and eats an avocado or another dinosaur with a disease, he can get sick. A sick dinosaur moves less, and thus has a greater chance of dying due to hunger or even being eaten by another dinosaur.
  • gender: A dinosaur has a 45% change of being male or female, and a 10% chance of being a hybrid, which can reproduce without a mate. Only mature dinosaurs (greater than or equal to 80% of their full adult size) can reproduce, and with every interaction, there is only some small percentage of it.

The dinosaur has the following actions:

  • move: for each turn of the game, the dinosaur moves, and then interacts with whatever he finds in his new spot.
  • eat: a dinosaur can choose to eat an avocado, or even another dinosaur, depending on the size and level of hunger.
  • sleep a dinosaur can choose to sleep (with some probability) if he is sick to increase the chance of getting better.
  • reproduce a dinosaur that encounters another dinosaur (mature of the opposite gender) has some percent change of reproduction.


Avocados are grown on trees that are scattered in the environment. For any given tree, it must be a certain age to produce avocados, and once it's old enough, it can only generate a certain number of avocados over a period of time. This gives us the following attributes:

  • mature: a mature tree cannot be eaten by a dinosaur, and can produce avocados. An immature tree can be eaten entirely and removed from the game.
  • avocados: once a tree is mature, it holds a certain number of avocados
  • disease: any tree can get a disease with a small probability. Getting a disease puts the tree at risk for dying, or getting a dinosaur sick.


For each of the scenarios above, there must be probabilities generated within some range (set when the game starts) and then allocated to randomly generated entities, which are also randomly placed on a game board of some size.


The game starts with a certain number of dinosaurs (number of total dinosaurs), with the following randomly set values (within some ranges):

  • size
  • hunger

The game itself (an instance of DinosaurDilemma) under dinolemma/ creates some number of dinosaurs in the following way:

from dinolemma.dinosaurs import Dinosaurs

dinosaurs = Dinosaurs()

[14 dinosaurs]

for dino in dinosaurs: 


Each is guaranteed to have a unique name, and we check that there are enough spaces on the game board to support the dinosaurs and trees created. We can also grab a random dinosaur:

dino = dinosaurs.random()


The game also starts with a certain number of avocado saplings.

from dinolemma.avocados import AvocadoTrees

trees = AvocadoTrees()
for tree in trees:


or grab a random tree:

tree = trees.random()
<dinolemma.avocados.AvocadoTree at 0x7f25347e7860>

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