chris-tapley-rt

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chris-tapley-rt

Failed Tests

optimisation_2023_11_16

from timeit import timeit
from math import floor

# 1. Can you implement another optimised function (sum_even_numbers2) using purely native python?
#    Can you timeit to show it's faster and describe why it is.
#    Can you also state if there are any pros or cons to how it is implemented?

# 2. Can you implement another optimised function (sum_even_numbers3) using third party packages?
#    Can you timeit to show it's faster and describe why it is.
#    Can you also state if there are any pros or cons to how it is implemented?

def sum_even_numbers1(numbers: list[int]) -> int:
    total = 0
    for num in numbers:
        if floor(num/2) == num/2:
            total += num
    return total
import codewars_test as test
import solution # or from solution import example

@test.describe("Example")
def test_group():
    @test.it("test case")
    def test_case():
        iterations = 100
        list_length = 100000

        input_data = [i for i in range(0, list_length)]    

        print(timeit(lambda: sum_even_numbers1(input_data), number=iterations))

chris-tapley-rt

Failed Tests

optimisation_sabin

from timeit import timeit
from math import floor

# 1. Can you implement another optimised function (sum_even_numbers2) using purely native python?
#    Can you timeit to show it's faster and describe why it is.
#    Can you also state if there are any pros or cons to how it is implemented?

# 2. Can you implement another optimised function (sum_even_numbers3) using third party packages?
#    Can you timeit to show it's faster and describe why it is.
#    Can you also state if there are any pros or cons to how it is implemented?

def sum_even_numbers1(numbers: list[int]) -> int:
    total = 0
    for num in numbers:
        if floor(num/2) == num/2:
            total += num
    return total
import codewars_test as test
import solution # or from solution import example

@test.describe("Example")
def test_group():
    @test.it("test case")
    def test_case():
        iterations = 100
        list_length = 100000

        input_data = [i for i in range(0, list_length)]    

        print(timeit(lambda: sum_even_numbers1(input_data), number=iterations))

chris-tapley-rt

Failed Tests

equipment_test_sabin

"""Test equipment positions."""
from __future__ import annotations
from collections import Counter, defaultdict
import datetime as dt
import math
import numpy as np
import pandas as pd
from typing import Any


def data_dict() -> defaultdict[str, Any]:
    """Return all equipment positions."""
    d = defaultdict(list)
    d["T123"].append({"position": {"x": 42, "y": 24, "z": 0.42}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=0)})
    d["T456"].append({"position": {"x": 21.0, "y": 34, "z": 0.289}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=0)})
    d["T789"].append({"position": {"x": 17, "y": 39, "z": 0.789}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=0)})
    d["T456"].append({"position": {"x": 91.0, "y": 114, "z": 0.489}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=3)})
    d["T123"].append({"position": {"x": 43, "y": 25, "z": 0.43}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=1)})
    d["T789"].append({"position": {"x": 19., "y": 79, "z": 0.991}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=6)})
    d["T123"].append({"position": {"x": 46, "y": 29, "z": 0.44}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=2)})
    d["T456"].append({"position": {"x": 24.0, "y": 37, "z": 0.297}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=4)})
    d["T123"].append({"position": {"x": 49.0, "y": 32, "z": 0.451}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=3)})
    d["T789"].append({"position": {"x": 23., "y": 81, "z": 1.103}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=7)})
    return d


def latest_snapshot() -> dict[str, Any]:
    """Return a snapshot of latest equipment."""
    return {
        "T123": {"position": {"x": 49.0, "y": 32, "z": 0.451}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=3)},
        "T456": {"position": {"x": 24.0, "y": 37, "z": 0.297}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=4)},
        "T789": {"position": {"x": 23.0, "y": 81, "z": 1.103}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=7)},
    }


def counts() -> dict[str, int]:
    """Return counts per equipment."""
    return {
        "T123": 4,
        "T456": 3,
        "T789": 3
    }


def speeds() -> defaultdict[str, Any]:
    """Return speeds of equipment."""
    d = defaultdict(list)
    d["T123"].append({"speed": 4.242654947082074, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=3)})
    d["T123"].append({"speed": 5.00000999999, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=2)})
    d["T123"].append({"speed": 1.4142489172702237, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=1)})
    d["T123"].append({"speed": None, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=0)})
    d["T456"].append({"speed": 102.0687849638664, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=4)})
    d["T456"].append({"speed": 35.43388209045123, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=3)})
    d["T456"].append({"speed": None, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=0)})
    d["T789"].append({"speed": 4.473538196997986, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=7)})
    d["T789"].append({"speed": 6.6750796998987205, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=6)})
    d["T789"].append({"speed": None, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=0)})
    return d

  
def find_furthest_west(d: defaultdict) -> str:
    """
    Find the name of the truck that is furthest west. That is,
    the truck with the smallest easting position component.
    """
    pass

def get_latest_snapshot(d: defaultdict) -> dict[str, Any]:
    """
    Return a snapshot of the latest positional updates for the
    equipment.
    """
    pass

def get_counts(d: defaultdict) -> dict[str, int]:
    """Return a dict of trucks and the times they have provided updates."""
    pass

  
def calculate_speeds(d: defaultdict) -> defaultdict[str, Any]:
    """Return a dict of equipment and the speeds they are travelling at."""
    pass
import codewars_test as test
import solution # or from solution import example

# test.assert_equals(actual, expected, [optional] message)
@test.describe("Example")
def test_group():
    @test.it("test find_furthest_west")
    def test_cases():
        d = data_dict()
        test.assert_equals(find_furthest_west(d), "T789")
        
    @test.it("test get_latest_snapshot")
    def test_get_latest_snapshot():
        d = data_dict()
        snapshot = latest_snapshot()
        test.assert_equals(get_latest_snapshot(d), snapshot)
        
    @test.it("test get_counts")
    def test_get_count():
        d = data_dict()
        the_counts = counts()
        test.assert_equals(get_counts(d), the_counts)
        
    @test.it("test calculate_speeds")
    def test_calculate_speeds():
        d = data_dict()
        the_speeds = speeds()
        test.assert_equals(calculate_speeds(d), the_speeds)

chris-tapley-rt

Failed Tests

optimisation_alphons

from timeit import timeit
from math import floor

# 1. Can you implement another optimised function (sum_even_numbers2) using purely native python?
#    Can you timeit to show it's faster and describe why it is.
#    Can you also state if there are any pros or cons to how it is implemented?

# 2. Can you implement another optimised function (sum_even_numbers3) using third party packages?
#    Can you timeit to show it's faster and describe why it is.
#    Can you also state if there are any pros or cons to how it is implemented?

def sum_even_numbers1(numbers: list[int]) -> int:
    total = 0
    for num in numbers:
        if floor(num/2) == num/2:
            total += num
    return total
import codewars_test as test
import solution # or from solution import example

@test.describe("Example")
def test_group():
    @test.it("test case")
    def test_case():
        iterations = 100
        list_length = 100000

        input_data = [i for i in range(0, list_length)]    

        print(timeit(lambda: sum_even_numbers1(input_data), number=iterations))

chris-tapley-rt

Failed Tests

optimisation_bhushan

from timeit import timeit
from math import floor

# 1. Can you implement another optimised function (sum_even_numbers2) using purely native python?
#    Can you timeit to show it's faster and describe why it is.
#    Can you also state if there are any pros or cons to how it is implemented?

# 2. Can you implement another optimised function (sum_even_numbers3) using third party packages?
#    Can you timeit to show it's faster and describe why it is.
#    Can you also state if there are any pros or cons to how it is implemented?

def sum_even_numbers1(numbers: list[int]) -> int:
    total = 0
    for num in numbers:
        if floor(num/2) == num/2:
            total += num
    return total
import codewars_test as test
import solution # or from solution import example

@test.describe("Example")
def test_group():
    @test.it("test case")
    def test_case():
        iterations = 100
        list_length = 100000

        input_data = [i for i in range(0, list_length)]    

        print(timeit(lambda: sum_even_numbers1(input_data), number=iterations))

chris-tapley-rt

Failed Tests

equipment_test_alphons

"""Test equipment positions."""
from __future__ import annotations
from collections import Counter, defaultdict
import datetime as dt
import math
import numpy as np
import pandas as pd
from typing import Any


def data_dict() -> defaultdict[str, Any]:
    """Return all equipment positions."""
    d = defaultdict(list)
    d["T123"].append({"position": {"x": 42, "y": 24, "z": 0.42}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=0)})
    d["T456"].append({"position": {"x": 21.0, "y": 34, "z": 0.289}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=0)})
    d["T789"].append({"position": {"x": 17, "y": 39, "z": 0.789}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=0)})
    d["T456"].append({"position": {"x": 91.0, "y": 114, "z": 0.489}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=3)})
    d["T123"].append({"position": {"x": 43, "y": 25, "z": 0.43}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=1)})
    d["T789"].append({"position": {"x": 19., "y": 79, "z": 0.991}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=6)})
    d["T123"].append({"position": {"x": 46, "y": 29, "z": 0.44}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=2)})
    d["T456"].append({"position": {"x": 24.0, "y": 37, "z": 0.297}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=4)})
    d["T123"].append({"position": {"x": 49.0, "y": 32, "z": 0.451}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=3)})
    d["T789"].append({"position": {"x": 23., "y": 81, "z": 1.103}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=7)})
    return d


def latest_snapshot() -> dict[str, Any]:
    """Return a snapshot of latest equipment."""
    return {
        "T123": {"position": {"x": 49.0, "y": 32, "z": 0.451}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=3)},
        "T456": {"position": {"x": 24.0, "y": 37, "z": 0.297}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=4)},
        "T789": {"position": {"x": 23.0, "y": 81, "z": 1.103}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=7)},
    }


def counts() -> dict[str, int]:
    """Return counts per equipment."""
    return {
        "T123": 4,
        "T456": 3,
        "T789": 3
    }


def speeds() -> defaultdict[str, Any]:
    """Return speeds of equipment."""
    d = defaultdict(list)
    d["T123"].append({"speed": 4.242654947082074, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=3)})
    d["T123"].append({"speed": 5.00000999999, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=2)})
    d["T123"].append({"speed": 1.4142489172702237, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=1)})
    d["T123"].append({"speed": None, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=0)})
    d["T456"].append({"speed": 102.0687849638664, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=4)})
    d["T456"].append({"speed": 35.43388209045123, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=3)})
    d["T456"].append({"speed": None, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=0)})
    d["T789"].append({"speed": 4.473538196997986, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=7)})
    d["T789"].append({"speed": 6.6750796998987205, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=6)})
    d["T789"].append({"speed": None, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=0)})
    return d

  
def find_furthest_west(d: defaultdict) -> str:
    """
    Find the name of the truck that is furthest west. That is,
    the truck with the smallest easting position component.
    """
    pass

def get_latest_snapshot(d: defaultdict) -> dict[str, Any]:
    """
    Return a snapshot of the latest positional updates for the
    equipment.
    """
    pass

def get_counts(d: defaultdict) -> dict[str, int]:
    """Return a dict of trucks and the times they have provided updates."""
    pass

  
def calculate_speeds(d: defaultdict) -> defaultdict[str, Any]:
    """Return a dict of equipment and the speeds they are travelling at."""
    pass
import codewars_test as test
import solution # or from solution import example

# test.assert_equals(actual, expected, [optional] message)
@test.describe("Example")
def test_group():
    @test.it("test find_furthest_west")
    def test_cases():
        d = data_dict()
        test.assert_equals(find_furthest_west(d), "T789")
        
    @test.it("test get_latest_snapshot")
    def test_get_latest_snapshot():
        d = data_dict()
        snapshot = latest_snapshot()
        test.assert_equals(get_latest_snapshot(d), snapshot)
        
    @test.it("test get_counts")
    def test_get_count():
        d = data_dict()
        the_counts = counts()
        test.assert_equals(get_counts(d), the_counts)
        
    @test.it("test calculate_speeds")
    def test_calculate_speeds():
        d = data_dict()
        the_speeds = speeds()
        test.assert_equals(calculate_speeds(d), the_speeds)

chris-tapley-rt

Failed Tests

codewars_bhushan

"""Test equipment positions."""
from __future__ import annotations
from collections import Counter, defaultdict
import datetime as dt
import math
import numpy as np
import pandas as pd
from typing import Any


def data_dict() -> defaultdict[str, Any]:
    """Return all equipment positions."""
    d = defaultdict(list)
    d["T123"].append({"position": {"x": 42, "y": 24, "z": 0.42}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=0)})
    d["T456"].append({"position": {"x": 21.0, "y": 34, "z": 0.289}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=0)})
    d["T789"].append({"position": {"x": 17, "y": 39, "z": 0.789}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=0)})
    d["T456"].append({"position": {"x": 91.0, "y": 114, "z": 0.489}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=3)})
    d["T123"].append({"position": {"x": 43, "y": 25, "z": 0.43}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=1)})
    d["T789"].append({"position": {"x": 19., "y": 79, "z": 0.991}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=6)})
    d["T123"].append({"position": {"x": 46, "y": 29, "z": 0.44}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=2)})
    d["T456"].append({"position": {"x": 24.0, "y": 37, "z": 0.297}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=4)})
    d["T123"].append({"position": {"x": 49.0, "y": 32, "z": 0.451}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=3)})
    d["T789"].append({"position": {"x": 23., "y": 81, "z": 1.103}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=7)})
    return d


def latest_snapshot() -> dict[str, Any]:
    """Return a snapshot of latest equipment."""
    return {
        "T123": {"position": {"x": 49.0, "y": 32, "z": 0.451}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=3)},
        "T456": {"position": {"x": 24.0, "y": 37, "z": 0.297}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=4)},
        "T789": {"position": {"x": 23.0, "y": 81, "z": 1.103}, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=7)},
    }


def counts() -> dict[str, int]:
    """Return counts per equipment."""
    return {
        "T123": 4,
        "T456": 3,
        "T789": 3
    }


def speeds() -> defaultdict[str, Any]:
    """Return speeds of equipment."""
    d = defaultdict(list)
    d["T123"].append({"speed": 4.242654947082074, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=3)})
    d["T123"].append({"speed": 5.00000999999, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=2)})
    d["T123"].append({"speed": 1.4142489172702237, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=1)})
    d["T123"].append({"speed": None, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=0)})
    d["T456"].append({"speed": 102.0687849638664, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=4)})
    d["T456"].append({"speed": 35.43388209045123, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=3)})
    d["T456"].append({"speed": None, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=0)})
    d["T789"].append({"speed": 4.473538196997986, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=7)})
    d["T789"].append({"speed": 6.6750796998987205, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=6)})
    d["T789"].append({"speed": None, "timestamp": dt.datetime(2022, 1, 1, hour=12, minute=0, second=0)})
    return d

  
def find_furthest_west(d: defaultdict) -> str:
    """
    Find the name of the truck that is furthest west. That is,
    the truck with the smallest easting position component.
    """
    pass

def get_latest_snapshot(d: defaultdict) -> dict[str, Any]:
    """
    Return a snapshot of the latest positional updates for the
    equipment.
    """
    pass

def get_counts(d: defaultdict) -> dict[str, int]:
    """Return a dict of trucks and the times they have provided updates."""
    pass

  
def calculate_speeds(d: defaultdict) -> defaultdict[str, Any]:
    """Return a dict of equipment and the speeds they are travelling at."""
    pass
import codewars_test as test
import solution # or from solution import example

# test.assert_equals(actual, expected, [optional] message)
@test.describe("Example")
def test_group():
    @test.it("test find_furthest_west")
    def test_cases():
        d = data_dict()
        test.assert_equals(find_furthest_west(d), "T789")
        
    @test.it("test get_latest_snapshot")
    def test_get_latest_snapshot():
        d = data_dict()
        snapshot = latest_snapshot()
        test.assert_equals(get_latest_snapshot(d), snapshot)
        
    @test.it("test get_counts")
    def test_get_count():
        d = data_dict()
        the_counts = counts()
        test.assert_equals(get_counts(d), the_counts)
        
    @test.it("test calculate_speeds")
    def test_calculate_speeds():
        d = data_dict()
        the_speeds = speeds()
        test.assert_equals(calculate_speeds(d), the_speeds)

chris-tapley-rt

Failed Tests

2023-01-12 Interview Questions

Python interview questions

from __future__ import annotations

from collections import defaultdict
import datetime as dt
from typing import Any

import numpy as np

DataDictType = dict[str, list[dict[str, Any]]]


def data_dict() -> DataDictType:
    """Return all equipment positions."""
    d = defaultdict(list)
    d["T123"].append({'position': { "x": 42, "y": 24, "z": 0.42 }, 'last_updated': dt.datetime(2022, 1, 1, hour=12, minute=0, second=0)})
    d["T456"].append({"position": { 'x': 21., 'y': 34, 'z': 0.289 }, 'last_updated': dt.datetime(2022, 1, 1, hour=12, minute=0, second=0)})
    d["T789"].append({"position": { 'x': 17., 'y': 39, 'z': 0.789 }, 'last_updated': dt.datetime(2022, 1, 1, hour=12, minute=0, second=0)})
    d["T456"].append({"position": { 'x': 91., 'y': 74, 'z': 0.389 }, 'last_updated': dt.datetime(2022, 1, 1, hour=12, minute=0, second=3)})
    d["T123"].append({'position': { "x": 43, "y": 25, "z": 0.43 }, 'last_updated': dt.datetime(2022, 1, 1, hour=12, minute=0, second=1)})
    d["T789"].append({"position": { 'x': 19., 'y': 79, 'z': 0.991 }, 'last_updated': dt.datetime(2022, 1, 1, hour=12, minute=0, second=7)})
    d["T123"].append({'position': { "x": 44, "y": 26, "z": 0.43 }, 'last_updated': dt.datetime(2022, 1, 1, hour=12, minute=0, second=2)})
    return d
                                                                                                                                                                                                    
                                                                                                                                                                                                    
def latest_snapshot() -> dict[str, Any]:
    """Return a snapshot of latest equipment."""
    return {
        "T456": { "position": { 'x': 91., 'y': 74, 'z': 0.389 }, 'last_updated': dt.datetime(2022, 1, 1, hour=12, minute=0, second=3)},
        "T123": { 'position': { "x": 44, "y": 26, "z": 0.43 }, 'last_updated': dt.datetime(2022, 1, 1, hour=12, minute=0, second=2)},
        "T789": { "position": { 'x': 19., 'y': 79, 'z': 0.991 }, 'last_updated': dt.datetime(2022, 1, 1, hour=12, minute=0, second=7)},
    }


def counts() -> dict[str, int]:
    """Return counts per equipment."""
    return {
        "T123": 3,
        "T456": 2,
        "T789": 2
    }
    

def average_speed_ms() -> dict[str, float]:
    return {
        "T123": 1.414231239822,
        "T456": 26.87421316678,
        "T789": 5.721496885627, 
    }


def find_furthest_west(d: DataDictType) -> str:
    """
    Find the name of the truck that is furthest west. That is,
    the truck with the smallest easting position component.
    """
    raise NotImplementedError


def get_latest_snapshot(d: DataDictType) -> dict[str, Any]:
    """
    Return a snapshot of the latest positional updates for the
    equipment.
    """
    raise NotImplementedError


def get_counts(d: DataDictType) -> dict[str, int]:
    """Return a dict of trucks and the times they have provided updates."""
    raise NotImplementedError


def get_average_speed_ms(d: DataDictType) -> dict[str, float]:
    """Return a dict of trucks and their average speed in meters per second over all the provided updates."""
    raise NotImplementedError

import codewars_test as test
import solution


# test.assert_equals(actual, expected, [optional] message)
@test.describe("Example")
def test_group():
    @test.it('test find_furthest_west')
    def test_cases():
        d = data_dict()
        test.assert_equals(find_furthest_west(d), 'T789')
        
    @test.it('test get_latest_snapshot')
    def test_get_latest_snapshot():
        d = data_dict()
        snapshot = latest_snapshot()
        test.assert_equals(get_latest_snapshot(d), snapshot)
        
    @test.it('test get_counts')
    def test_get_counts():
        d = data_dict()
        the_counts = counts()
        test.assert_equals(get_counts(d), the_counts)
        
    @test.it('test get_average_speed_ms')
    def test_get_speeds():
        d = data_dict()
        expected = average_speed_ms()
        actual = get_average_speed_ms(d)
        for truck_id in expected.keys():
            test.assert_approx_equals(expected[truck_id], actual[truck_id])

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