from typing import List

import csv

import math

################################################################################

# Begin constants

################################################################################

COLUMN_ID = 0

COLUMN_NAME = 1

COLUMN_HIGHWAY = 2

COLUMN_LAT = 3

COLUMN_LON = 4

COLUMN_YEAR_BUILT = 5

COLUMN_LAST_MAJOR_REHAB = 6

COLUMN_LAST_MINOR_REHAB = 7

COLUMN_NUM_SPANS = 8

COLUMN_SPAN_DETAILS = 9

COLUMN_DECK_LENGTH = 10

COLUMN_LAST_INSPECTED = 11

COLUMN_BCI = 12

INDEX_BCI_YEARS = 0

INDEX_BCI_SCORES = 1

MISSING_BCI = -1.0

EARTH_RADIUS = 6371

################################################################################

# Sample data for docstring examples

################################################################################

def create_example_bridge_1() -> list:

"""Return a bridge in our list-format to use for doctest examples.

This bridge is the same as the bridge from row 3 of the dataset.

"""

return [

1, 'Highway 24 Underpass at Highway 403',

'403', 43.167233, -80.275567, '1965', '2014', '2009', 4,

[12.0, 19.0, 21.0, 12.0], 65.0, '04/13/2012',

[['2013', '2012', '2011', '2010', '2009', '2008', '2007',

'2006', '2005', '2004', '2003', '2002', '2001', '2000'],

[MISSING_BCI, 72.3, MISSING_BCI, 69.5, MISSING_BCI, 70.0, MISSING_BCI,

70.3, MISSING_BCI, 70.5, MISSING_BCI, 70.7, 72.9, MISSING_BCI]]

]

def create_example_bridge_2() -> list:

"""Return a bridge in our list-format to use for doctest examples.

This bridge is the same as the bridge from row 4 of the dataset.

"""

return [

2, 'WEST STREET UNDERPASS',

'403', 43.164531, -80.251582, '1963', '2014', '2007', 4,

[12.2, 18.0, 18.0, 12.2], 61.0, '04/13/2012',

[['2013', '2012', '2011', '2010', '2009', '2008', '2007',

'2006', '2005', '2004', '2003', '2002', '2001', '2000'],

[MISSING_BCI, 71.5, MISSING_BCI, 68.1, MISSING_BCI, 69.0, MISSING_BCI,

69.4, MISSING_BCI, 69.4, MISSING_BCI, 70.3, 73.3, MISSING_BCI]]

]

def create_example_bridge_3() -> list:

"""Return a bridge in our list-format to use for doctest examples.

This bridge is the same as the bridge from row 33 of the dataset.

"""

return [

3, 'STOKES RIVER BRIDGE', '6',

45.036739, -81.33579, '1958', '2013', '', 1,

[16.0], 18.4, '08/28/2013',

[['2013', '2012', '2011', '2010', '2009', '2008', '2007',

'2006', '2005', '2004', '2003', '2002', '2001', '2000'],

[85.1, MISSING_BCI, 67.8, MISSING_BCI, 67.4, MISSING_BCI, 69.2,

70.0, 70.5, MISSING_BCI, 75.1, MISSING_BCI, 90.1, MISSING_BCI]]

]

def create_example_bridges() -> List[list]:

"""Return a list containing three unique example bridges.

The bridges contained in the list are from row 3, 4, and 33 of the dataset

(in that order).

"""

return [

create_example_bridge_1(),

create_example_bridge_2(),

create_example_bridge_3()

]

################################################################################

# Helper function

################################################################################

def calculate_distance(lat1: float, lon1: float,

lat2: float, lon2: float) -> float:

"""Return the distance in kilometers between the two locations defined by

(lat1, lon1) and (lat2, lon2), rounded to the nearest meter.

>>> calculate_distance(43.659777, -79.397383, 43.657129, -79.399439)

0.338

>>> calculate_distance(43.42, -79.24, 53.32, -113.30)

2713.226

"""

# This function uses the haversine function to find the

# distance between two locations. You do NOT need to understand why it

# works. You will just need to call on the function and work with what it

# returns.

# Based on code at goo.gl/JrPG4j

# convert decimal degrees to radians

lon1, lat1, lon2, lat2 = (math.radians(lon1), math.radians(lat1),

math.radians(lon2), math.radians(lat2))

# haversine formula t

lon_diff = lon2 - lon1

lat_diff = lat2 - lat1

a = (math.sin(lat_diff / 2) ** 2

+ math.cos(lat1) * math.cos(lat2) * math.sin(lon_diff / 2) ** 2)

c = 2 * math.asin(math.sqrt(a))

return round(c * EARTH_RADIUS, 3)

# Part 4 - Reading and cleaning raw data

################################################################################

def clean_length_data(raw_length: str) -> float:

"""Return the length of the bridge based on the value in raw_length.

If raw_length is an empty string, return 0.0.

Precondition:

- if raw_length is not the empty string, it can be converted to a float

>>> clean_length_data('12')

12.0

"""

def trim_from_end(raw_data: list, count: int) -> None:

"""Update raw_data so that count elements have been removed from the end.

Preconditions:

- count >= 0

- len(raw_data) >= count

>>> my_lst = [[72.3, 69.5, 70.0, 70.3, 70.5, 70.7, 72.9], '', '72.3', '', \

'69.5', '', '70', '', '70.3', '', '70.5', '', '70.7', '72.9', '']

>>> trim_from_end(my_lst, 14)

>>> my_lst

[[72.3, 69.5, 70.0, 70.3, 70.5, 70.7, 72.9]]

"""

def clean_span_data(raw_spans: str) -> List[float]:

"""Return a list of span lengths from raw_spans, in the same order that

they appear in raw_spans.

Precondition:

- raw_spans is in the appropriate format (see handout for details)

>>> clean_span_data('Total=64 (1)=12;(2)=19;(3)=21;(4)=12;')

[12.0, 19.0, 21.0, 12.0]

"""

def clean_bci_data(bci_years: List[str], start_year: int, bci_scores: list) -> \

None:

"""Update bci_years so that each element contains the year as a string,

starting from start_year and decreasing by one for each subsequent element,

until bci_years has the same length as bci_scores. Also update bci_scores

so that all non-empty string values are float values, and all empty string

values are MISSING_BCI.

Preconditions:

- len(bci_years) == 0

- len(bci_scores) > 0

- start_year - len(bci_scores) >= 0

- every value in bci_scores is either an empty string or can be

converted to a float

>>> years = []

>>> scores = ['', '72.3', '', '69.5', '', '70.0', '', '70.3', '']

>>> clean_bci_data(years, 2013, scores)

>>> years

['2013', '2012', '2011', '2010', '2009', '2008', '2007', '2006', '2005']

>>> scores

[-1.0, 72.3, -1.0, 69.5, -1.0, 70.0, -1.0, 70.3, -1.0]

"""

def clean_length_data(raw_length: str) -> float: "Return the length of the bridge based on the value in raw_length. If raw_length is an empty string, return 0.0. Precondition: - if raw_length is not the empty string, it can be converted to a float >>> clean_length_data("12') 12.0 def trim_from_end(raw_data: list, count: int) -> None: "Update raw_data so that count elements have been removed from the end. Preconditions: count >= 0 - len(raw_data) >= count 3 >>> my_1st = [[72.3, 69.5, 70.0, 70.3, 70.5, 70.7, 72.9], "', '72.3', '69.5',"', '70', ", "70.3', *70.5", ", '70.7', '72.9", "] >>> trim_from_end(my_lst, 14) >>> my_lst [[72.3, 69.5, 70.0, 70.3, 70.5, 70.7, 72.9]] TU! def clean_span_data(raw_spans: str) -> List[float]: "Return a list of span lengths from raw_spans, in the same order that they appear in raw_spans. Precondition: - raw_spans is in the appropriate format (see handout for details) >>> clean_span_data('Total=64 (1)-12;(2)=19; (3)=21;(4)=12;') [12.0, 19.0, 21.0, 12.0] EF def clean_bci_data(bci_years: List[str], start_year: int, bci_scores: list) -> None: **** "Update bci_years so that each element contains the year as a string, starting from start_year and decreasing by one for each subsequent element, until bci_years has the same length as bci_scores. Also update bci_scores so that all non-empty string values are float values, and all empty string values are MISSING_BCI. Preconditions: - len(bci_years) == 0 lenbci_scores) > 0 - start-year len(bci_scores) >= 0 every value in bci_scores is either an empty string or can be converted to a float II 3 >>> years >>> scores ['', '72.3', " '69.5', "70.0', '', '70.3', ''] >>> clean_bci_data(years, 2013, scores) >>> years ['2013', '2012', '2011', '2010', '2009', '2008', '2007', '2006', '2005'] >>> scores [-1.0, 72.3, -1.0, 69.5, -1.0, 70.0, -1.0, 70.3, -1.0] def clean_length_data(raw_length: str) -> float: "Return the length of the bridge based on the value in raw_length. If raw_length is an empty string, return 0.0. Precondition: - if raw_length is not the empty string, it can be converted to a float >>> clean_length_data("12') 12.0 def trim_from_end(raw_data: list, count: int) -> None: "Update raw_data so that count elements have been removed from the end. Preconditions: count >= 0 - len(raw_data) >= count 3 >>> my_1st = [[72.3, 69.5, 70.0, 70.3, 70.5, 70.7, 72.9], "', '72.3', '69.5',"', '70', ", "70.3', *70.5", ", '70.7', '72.9", "] >>> trim_from_end(my_lst, 14) >>> my_lst [[72.3, 69.5, 70.0, 70.3, 70.5, 70.7, 72.9]] TU! def clean_span_data(raw_spans: str) -> List[float]: "Return a list of span lengths from raw_spans, in the same order that they appear in raw_spans. Precondition: - raw_spans is in the appropriate format (see handout for details) >>> clean_span_data('Total=64 (1)-12;(2)=19; (3)=21;(4)=12;') [12.0, 19.0, 21.0, 12.0] EF def clean_bci_data(bci_years: List[str], start_year: int, bci_scores: list) -> None: **** "Update bci_years so that each element contains the year as a string, starting from start_year and decreasing by one for each subsequent element, until bci_years has the same length as bci_scores. Also update bci_scores so that all non-empty string values are float values, and all empty string values are MISSING_BCI. Preconditions: - len(bci_years) == 0 lenbci_scores) > 0 - start-year len(bci_scores) >= 0 every value in bci_scores is either an empty string or can be converted to a float II 3 >>> years >>> scores ['', '72.3', " '69.5', "70.0', '', '70.3', ''] >>> clean_bci_data(years, 2013, scores) >>> years ['2013', '2012', '2011', '2010', '2009', '2008', '2007', '2006', '2005'] >>> scores [-1.0, 72.3, -1.0, 69.5, -1.0, 70.0, -1.0, 70.3, -1.0]