ungleich-learning-circle/youngjin.han/python-the-hard-way/ex39.py

66 lines
1.6 KiB
Python

# create a mapping of state to abbreviation
states = {
'Oregon': 'OR',
'Florida': 'FL',
'California': 'CA',
'New York': 'NY',
'Michigan': 'MI',
'Texas': 'TX'
}
# create a basic set of states and some cities in them
cities = {
'CA': 'San Francisco',
'MI': 'Detroit',
'FL': 'Jacksonville',
'Gyeonggi-do': 'Sungnam',
'Chungcheongbuk-do': 'Cheongju'
}
# add some more cities
cities['NY'] = 'New York'
cities['OR'] = 'Portland'
cities['TX'] = 'Houston'
# print out some cities
print('-' * 10)
print("NY State has: ", cities['NY'])
print("OR State has: ", cities['OR'])
# print some states
print('-' * 10)
print("Michigan's abbreviation is: ", states['Michigan'])
print("Florida's abbreviation is: ", states['Florida'])
# do it by using the state then cities dict
print('-' * 10)
print("Michigan has: ", cities[states['Michigan']])
print("Florida has: ", cities[states['Florida']])
# print every state abbreviation
print('-' * 10)
for state, abbrev in list(states.items()):
print(f"{state} is abbreviated {abbrev}")
# print every city in state
print('-' * 10)
for abbrev, city in list(cities.items()):
print(f"{abbrev} has the city {city}")
# now do both at the same time
print('-' * 10)
for state, abbrev in list(states.items()):
print(f"{state} state is abbreviated {abbrev}")
print(f"and has city {cities[abbrev]}")
print('-' * 10)
# safely get a abbreviation by state that might not be there
state = states.get('Texas')
if not state:
print("Sorry, no Texas.")
# get a city with a default value
city = cities.get('TX', 'Does Not Exist')
print(f"The city for the state 'TX' is: {city}")