Due Monday Feb 13 at 9pm. Upload to Desire 2 Learn dropbox for homework 4.
For this programming assignment, you are going to design and implement a class that models cars. To test your car class, you will need to open and read a json encoded file containing data about cars. For each json item you will create a Car object with the information in the json object then store the new object in a list. Thus, after reading the file your test program should have an array of “car objects”. Below are the requirements for your Car class as well as your test program.
self._yearYour Car class must implement the following methods:
__init__(self) contructor should take three parameters corresponding to each attribute. Please provide default values.
__repr__(self) Returns a string representation of the Car.
get_year(self) Returns the year attribute of a car object.
get_make(self) Returns the make attribute of a car object.
get_odometer(self) Returns the odometer attribute of a car object.
get_status(self) Returns “NEW” (odometer < 50K), “USED” (odometer < 150K), or “JUNK” (odometer >= 150K) depending on the odometer value.
data.txtDownload data.txt
For each json item in the data, create a car object with data points in the object then add the car object to a list.
Once you have loaded your list, implement the following functions:
a. Determine then print the average odometer reading from all the car objects in the list. Must produce floating point result.
b. Compute then print the most frequent make in the car data list.
c. Compute then print the least frequent make in the car data list.
d. Compute then print the most frequent ocurring status. E.g., “The data contains mostly USED cars.”
json module. Import this at the top of your program. You can then use json.loads(string) to read in a json string and convert it to a python list of dictionary items.import json
json_data = json.loads(somejsonencodedstringhere)c = {"status": 99634, "make": "Infiniti", "year": 2012}
print c['status'] # prints 99634# Example: open a json encoded file for reading, then decode with json.
fp = open('data.txt', 'r')
s = fp.read()
jin = json.loads(s) # this decodes into python data structure
# jin is an actual python list containing dictionaries.
# This can handled with python list processing techniques
for i in jin:
print i['year']# solution.py
import json
class Car(object):
def __init__(self, year=1900, make="model-t", odometer=0):
self.__year = year
self.__make = make
self.__odometer = odometer
def __repr__(self):
return ' '.join([str(self.__year), self.__make, str(self.__odometer)])
def get_year(self):
return self.__year
def get_make(self):
return self.__make
def get_odometer(self):
return self.__odometer
def get_status(self):
if self.__odometer < 50000:
return 'NEW'
if self.__odometer < 150000:
return 'USED'
else:
return 'JUNK'
""" Not required for assigned homework """
def serialize_json(self):
"""Returns a json encodable representation of a Car object."""
return {'year': self.__year, 'make': self.__make, 'odometer':self.__odometer}
""" Not required for assigned homework """
@staticmethod
def deserialize_json(json_data):
""" A static method for constructing a Car object from a dictionary object (json generated)"""
return Car(year=json_data['year'], make=json_data['make'], odometer=json_data['odometer'])
# End of Car class
"""Test Car class methods in 'main' method"""
if __name__=="__main__":
def get_avg_odometer(carlist):
if not carlist:
print 'There appear to be no cars in the list!'
return
total = 0
for car in carlist:
total += car.get_odometer()
avg = float(total) / len(carlist)
print 'Average odometer reading for', len(carlist), 'cars \t ==>', avg
def get_least_most_makes(carlist):
if not carlist:
print 'There appear to be no cars in the list!'
return
aggregator = {} # key=make of a car, value=number of occurrences of that make
for car in carlist:
try:
aggregator[car.get_make()] += 1
except KeyError:
aggregator[car.get_make()] = 1
init_key = aggregator.keys()[0] # get first key returned from dictionary
max_count = (init_key, aggregator[init_key]) # get initial key, value pair as tuple
min_count = max_count
for make, count in aggregator.items():
if count > max_count[1]:
max_count = (make, count)
if count < min_count[1]:
min_count = (make, count)
print 'Highest frequency make \t\t\t\t ==>', max_count[1], max_count[0]
print 'Lowest frequency make \t\t\t\t ==>', min_count[1], min_count[0]
def get_most_freq_status(carlist):
if not carlist:
print 'There appear to be no cars in the list!'
return
aggregator = {} # key=status (USED, NEW, or JUNK), value=number of occurrences of that status
for car in carlist:
try:
aggregator[car.get_status()] += 1
except KeyError:
aggregator[car.get_status()] = 1
init_key = aggregator.keys()[0] # get first key returned from dictionary
max_count = (init_key, aggregator[init_key]) # get initial key, value pair as tuple
for status, count in aggregator.items():
if count > max_count[1]:
max_count = (status, count)
print 'Cars in list are mostly \t\t\t ==>', max_count[0], max_count[1], 'junkers'
def load_data():
fp = open('data.txt')
datastr = fp.read() # read in the entire data file as a string
data = json.loads(datastr) # decode the json string into python data structure
fp.close()
# comprehension that returns n car objects from each dictionary item in data
return [Car(year=json_dict['year'], make=json_dict['make'], odometer=json_dict['odometer']) for json_dict in data]
# Alternative comprehension that uses static method for Car class
# return [Car.deserialize_json(i) for i in data]
"""Run the tests..."""
print '\n*****************\n'
carlist = load_data()
get_avg_odometer(carlist)
get_least_most_makes(carlist)
get_most_freq_status(carlist)
print '\n*****************\n'