Exercise: Refactoring The Bad Boids¶
Bad_Boids¶
We have written some very bad code implementing our Boids flocking example.
Here's the Github link.
Please fork it on GitHub, and clone your fork.
git clone git@github.com:yourname/bad-boids.git
# OR git clone https://github.com/yourname/bad-boids.git
For the Exercise, you should start from the GitHub repository, but here's our terrible code:
"""
A deliberately bad implementation of
[Boids](http://dl.acm.org/citation.cfm?doid=37401.37406)
for use as an exercise on refactoring.
"""
from matplotlib import pyplot as plt
from matplotlib import animation
import random
# Deliberately terrible code for teaching purposes
boids_x=[random.uniform(-450,50.0) for x in range(50)]
boids_y=[random.uniform(300.0,600.0) for x in range(50)]
boid_x_velocities=[random.uniform(0,10.0) for x in range(50)]
boid_y_velocities=[random.uniform(-20.0,20.0) for x in range(50)]
boids=(boids_x,boids_y,boid_x_velocities,boid_y_velocities)
def update_boids(boids):
xs,ys,xvs,yvs=boids
# Fly towards the middle
for i in range(len(xs)):
for j in range(len(xs)):
xvs[i]=xvs[i]+(xs[j]-xs[i])*0.01/len(xs)
for i in range(len(xs)):
for j in range(len(xs)):
yvs[i]=yvs[i]+(ys[j]-ys[i])*0.01/len(xs)
# Fly away from nearby boids
for i in range(len(xs)):
for j in range(len(xs)):
if (xs[j]-xs[i])**2 + (ys[j]-ys[i])**2 < 100:
xvs[i]=xvs[i]+(xs[i]-xs[j])
yvs[i]=yvs[i]+(ys[i]-ys[j])
# Try to match speed with nearby boids
for i in range(len(xs)):
for j in range(len(xs)):
if (xs[j]-xs[i])**2 + (ys[j]-ys[i])**2 < 10000:
xvs[i]=xvs[i]+(xvs[j]-xvs[i])*0.125/len(xs)
yvs[i]=yvs[i]+(yvs[j]-yvs[i])*0.125/len(xs)
# Move according to velocities
for i in range(len(xs)):
xs[i]=xs[i]+xvs[i]
ys[i]=ys[i]+yvs[i]
figure=plt.figure()
axes=plt.axes(xlim=(-500,1500), ylim=(-500,1500))
scatter=axes.scatter(boids[0],boids[1])
def animate(frame):
update_boids(boids)
scatter.set_offsets(list(zip(boids[0],boids[1])))
anim = animation.FuncAnimation(figure, animate,
frames=200, interval=50)
If you go into your folder and run the code:
cd bad_boids
python boids.py
You should be able to see some birds flying around, and then disappearing as they leave the window.
from IPython.display import HTML
HTML(anim.to_jshtml())
Your Task¶
Transform bad_boids gradually into better code, while making sure it still works, using a Refactoring approach.
A regression test¶
First, have a look at the regression test we made.
To create it, we saved out the before and after state for one iteration of some boids, using ipython:
import yaml
import boids
from copy import deepcopy
before = deepcopy(boids.boids)
boids.update_boids(boids.boids)
after = boids.boids
fixture = {"before": before, "after": after}
fixture_file = open("fixture.yml", 'w')
fixture_file.write(yaml.dump(fixture))
fixture_file.close()
Invoking the test¶
Then, I used the fixture file to define the test:
from boids import update_boids
from nose.tools import assert_almost_equal
import os
import yaml
def test_bad_boids_regression():
regression_data = yaml.safe_load(open(os.path.join(os.path.dirname(__file__),'fixture.yml')))
boid_data = regression_data["before"]
update_boids(boid_data)
for after, before in zip(regression_data["after"], boid_data):
for after_value, before_value in zip(after, before):
assert_almost_equal(after_value, before_value, delta=0.01)
Make the regression test fail¶
Check the tests pass:
pytest
Edit the file to make the test fail, see the fail, then reset it:
git checkout boids.py
Start Refactoring¶
Look at the code, consider the list of refactorings, and make changes.
Each time, do a git commit on your fork, and write a commit message explaining the refactoring you did.
Try to keep the changes as small as possible.
If your refactoring creates any units, (functions, modules, or classes) write a unit test for the unit: it is a good idea to get away from regression testing as soon as you can.