Assume that the grades one has are:

• Assignments: 100, 100, 100, 30, 90, 50, 100, 0, 75, 80
• Final Exam/Project: 70
• Extra Credit: 500 problems

import numpy as np #import numpy

assignments = [100, 100, 100, 30, 90, 50, 100, 0, 75, 80] #assignment marks
final = 70       #final exam mark
extra = 500/1200*40 #percent of your final mark that is 100 due to extra credit
print('percentage of final mark that is 100 due to extra credit: ', extra)

percentage of final mark that is 100 due to extra credit:  16.666666666666668

#replace assignment marks that are below the final mark with the final mark. 
new_assignments = np.where(assignments > np.array(final), assignments, final)

#Print out new assignments to make sure they are sensible.
print('New assignment grades after replacement with Final', new_assignments)
print('old assignment average:', np.mean(assignments))
print('new assignment average:', np.mean(new_assignments))

New assignment grades after replacement with Final [100 100 100  70  90  70 100  70  75  80]
old assignment average: 72.5
new assignment average: 85.5

#The overall mark is 20% from the final exam/project and 80% from the (revised) assignments
mark = .2*final + .8*np.mean(new_assignments)

#However, 50/1200 percent of the mark is a 100% due to the extra credit. 
adjusted_mark = extra + (1-extra/100)*mark

print('mark without extra credit: ', mark)
print('mark with extra credit:    ', adjusted_mark)

mark without extra credit:  82.4
mark with extra credit:     85.33333333333334