from proj.inventory import MobileInventory, InsufficientException
import pytest
# Define a pytest test class **'TestingInventoryCreation'**
class TestingInventoryCreation:

    # Define a pytest test method **'test_creating_empty_inventory'**, which creates an empty inventory and checks if its 'balance_inventory' is an empty dict using assert.
    def test_creating_empty_inventory(self):
        c1 = MobileInventory()
        assert c1.balance_inventory == {}

    # Define a pytest test method **'test_creating_specified_inventory'**, which checks if inventory instance with input {'iPhone Model X':100, 'Xiaomi Model Y': 1000, 'Nokia Model Z':25}.
    def test_creating_specified_inventory(self):
        c2 = MobileInventory({'iPhone Model X':100, 'Xiaomi Model Y': 1000, 'Nokia Model Z':25})
        assert c2.balance_inventory == {'iPhone Model X':100, 'Xiaomi Model Y':1000, 'Nokia Model Z':25}

    # Define a pytest test method  **'test_creating_inventory_with_list'**, which checks if the  method raises a TypeError with the message "Input inventory must be a dictionary" when a list "['iPhone Model X', 'Xiaomi Model Y', 'Nokia Model Z']" is passed as input using assert.
    def test_creating_inventory_with_list(self):
        with pytest.raises(TypeError) :
            c3 = MobileInventory(['iPhone Model X', 'Xiaomi Model Y', 'Nokia Model Z'])

    # Define a pytest test method **'test_creating_inventory_with_numeric_keys'**, which checks if the  method raises a ValueError with the message "Mobile model name must be a string" using assert, when the dict {1:'iPhone Model X', 2:'Xiaomi Model Y', 3:'Nokia Model Z'} is passed as input.
    def test_creating_inventory_with_numeric_keys(self):
        with pytest.raises(ValueError):
            c4 = MobileInventory({1:'iPhone Model X', 2:'Xiaomi Model Y', 3:'Nokia Model Z'})

    # Define a pytest test method **'test_creating_inventory_with_nonnumeric_values'**, which checks if the  method raises a ValueError with the message "No. of mobiles must be a positive integer" using assert, when the dict {'iPhone Model X':'100', 'Xiaomi Model Y': '1000', 'Nokia Model Z':'25'} is passed as input.
    def test_creating_inventory_with_nonnumeric_values(self):
        with pytest.raises(ValueError):
            c5 = MobileInventory({'iPhone Model X':'100', 'Xiaomi Model Y':'1000', 'Nokia Model Z':'25'})

    # Define a pytest test method **'test_creating_inventory_with_negative_value'**, which checks if the  method raises a ValueError with the message "No. of mobiles must be a positive integer" using assert, when the dict {'iPhone Model X':-45, 'Xiaomi Model Y': 200, 'Nokia Model Z':25} is passed as input.
    def test_creating_inventory_with_negative_value(self):
        with pytest.raises(ValueError) :
            c6 = MobileInventory({'iPhone Model X':-45, 'Xiaomi Model Y': 200, 'Nokia Model Z':25})

# Define another pytest test class **'TestInventoryAddStock'**, which tests the behavior of the **'add_stock'** method, with the following tests
class TestInventoryAddStock:
    inventory = None
    @classmethod
    # Define a pytest class fixture 'setup_class', which creates an **'MobileInventory'** instance with input {'iPhone Model X':100, 'Xiaomi Model Y': 1000, 'Nokia Model Z':25} and assign it to class attribute **'inventory'**.
    def setup_class(cls):
        cls.inventory = MobileInventory({'iPhone Model X': 100, 'Xiaomi Model Y': 1000, 'Nokia Model Z': 25})

    # Define a pytest test method **'test_add_new_stock_as_dict'**, which adds the new stock {'iPhone Model X':50, 'Xiaomi Model Y': 2000, 'Nokia Model A':10} to the existing inventory, and update the **balance_inventory** attribute. Also, check if the updated **balance_inventory** equals {'iPhone Model X':150, 'Xiaomi Model Y': 3000, 'Nokia Model Z':25, 'Nokia Model A':10} using assert.
    def test_add_new_stock_as_dict(self):
        self.inventory.add_stock({'iPhone Model X': 50, 'Xiaomi Model Y': 2000, 'Nokia Model A': 10})

    # Define a pytest test method **'test_add_new_stock_as_list'**, which adds the new stock ['iPhone Model X', 'Xiaomi Model Y', 'Nokia Model Z'] to the existing inventory, and which checks if the method raises a TypeError with the message "Input stock must be a dictionary" using assert.
    def test_add_new_stock_as_list(self):
        with pytest.raises(TypeError):
          MobileInventory.add_stock(self, ['iPhone Model X', 'Xiaomi Model Y', 'Nokia Model Z'])

    # Define a pytest test method **'test_add_new_stock_with_numeric_keys'**, which adds the new stock {1:'iPhone Model A', 2:'Xiaomi Model B', 3:'Nokia Model C'} to the existing inventory, and which checks if the method raises a ValueError with the message "Mobile model name must be a string" using assert.
    def test_add_new_stock_with_numeric_keys(self):
        with pytest.raises(ValueError):
            MobileInventory.add_stock(self, {1: 'iPhone Model A', 2: 'Xiaomi Model B', 3: 'Nokia Model C'})


    # Define a pytest test method **'test_add_new_stock_with_nonnumeric_values'**, which adds the new stock {'iPhone Model A':'50', 'Xiaomi Model B':'2000', 'Nokia Model C':'25'} to the existing inventory, and which checks if the method raises a ValueError with the message "No. of mobiles must be a positive integer" using assert.
    def test_add_new_stock_with_nonnumeric_values(self):
        with pytest.raises(ValueError):
            MobileInventory.add_stock(self, {'iPhone Model A': '50', 'Xiaomi Model B': '2000', 'Nokia ModelC': '25'})

    # Define a pytest test method **'test_add_new_stock_with_float_values'**, which adds the new stock {'iPhone Model A':50.5, 'Xiaomi Model B':2000.3, 'Nokia Model C':25} to the existing inventory, and which checks if the method raises a ValueError with the message "No. of mobiles must be a positive integer" using assert.
    def test_add_new_stock_with_float_values(self):
        with pytest.raises(ValueError):
            MobileInventory.add_stock(self, {'iPhone Model A': 50.5, 'Xiaomi Model B': 2000.3, 'Nokia Model C': 25})

# Define another pytest test class **'TestInventorySellStock'**, which tests the behavior of the **'sell_stock'** method, with the following tests
class TestInventorySellStock:
    inventory = None
    @classmethod
    # Define a pytest class fixture 'setup_class', which creates an **'MobileInventory'** instance with the input {'iPhone Model A':50, 'Xiaomi Model B': 2000, 'Nokia Model C':10, 'Sony Model D':1}, and assign it to the class attribute **'inventory'**.
    def setup_class(cls):
        cls.inventory = MobileInventory({'iPhone Model A': 50, 'Xiaomi Model B': 2000, 'Nokia Model C': 10, 'Sony Model D': 1,})

    # Define a pytest test method **'test_sell_stock_as_dict'**, which sells the requested stock {'iPhone Model A':2, 'Xiaomi Model B':20, 'Sony Model D':1} from the existing inventory, and update the **balance_inventory** attribute. Also check if the updated **balance_inventory** equals {'iPhone Model A':48, 'Xiaomi Model B': 1980, 'Nokia Model C':10, 'Sony Model D':0} using assert.
    def test_sell_stock_as_dict(self):
        self.inventory.sell_stock({'iPhone Model A': 2, 'Xiaomi Model B': 20, 'Sony Model D': 1})

    # Define a pytest test method **'test_sell_stock_as_list'**, which tries selling the requested stock ['iPhone Model A', 'Xiaomi Model B', 'Nokia Model C'] from the existing inventory, and which checks if the method raises a TypeError with the message "Requested stock must be a dictionary" using assert.
    def test_sell_stock_as_list(self):
        with pytest.raises(TypeError):
            MobileInventory.sell_stock(self, ['iPhone Model A', 'Xiaomi Model B', 'Nokia Model C'])

    # Define a pytest test method **'test_sell_stock_with_numeric_keys'**, which tries selling the requested stock {1:'iPhone Model A', 2:'Xiaomi Model B', 3:'Nokia Model C'} from the existing inventory, and which checks if the method raises ValueError with the message "Mobile model name must be a string" using assert.
    def test_sell_stock_with_numeric_keys(self):
       with pytest.raises(ValueError):
          MobileInventory.sell_stock(self, {1: 'iPhone Model A', 2: 'Xiaomi Model B', 3: 'Nokia Model C'})

    # Define a pytest test method **'test_sell_stock_with_nonnumeric_values'**, which tries selling the requested stock {'iPhone Model A':'2', 'Xiaomi Model B':'3', 'Nokia Model C':'4'} from the existing inventory, and which checks if the method raises a ValueError with the message "No. of mobiles must be a positive integer" using assert.
    def test_sell_stock_with_nonnumeric_values(self):
        with pytest.raises(ValueError):
            MobileInventory.sell_stock(self, {'iPhone Model A': '5', 'Xiaomi Model B': '3', 'Nokia Model C': '4'})

    # Define a pytest test method **'test_sell_stock_with_float_values'**, which tries selling the requested stock {'iPhone Model A':2.5, 'Xiaomi Model B':3.1, 'Nokia Model C':4} from the existing inventory, and which checks if the method raises a ValueError with the message "No. of mobiles must be a positive integer" using assert.
    def test_sell_stock_with_float_values(self):
        with pytest.raises(ValueError):
            MobileInventory.sell_stock(self, {'iPhone Model A': 2.5, 'Xiaomi Model B': 3.1, 'Nokia Model C': 4})

    # Define a pytest test method **'test_sell_stock_of_nonexisting_model'**, which tries selling the requested stock {'iPhone Model B':2, 'Xiaomi Model B':5} from the existing inventory, and which checks if the method raises an InsufficientException with the message "No Stock. New Model Request" using assert.
    def test_sell_stock_of_nonexisting_model(self):
        with pytest.raises(ValueError):
            MobileInventory.sell_stock(self, {'iPhone Model B': 2, 'Xiaomi Model B': 5})

    # Define a pytest test method **'test_sell_stock_of_insufficient_stock'**, which tries selling the requested stock {'iPhone Model A':2, 'Xiaomi Model B':5, 'Nokia Model C': 15} from the existing inventory, and which checks if the method raises an InsufficientException with the message "Insufficient Stock" using assert.
    def test_sell_stock_of_insufficient_stock(self):
        with pytest.raises(ValueError):
            MobileInventory.sell_stock(self, {'iPhone Model A': 2, 'Xiaomi Model B': 5, 'Nokia Model C': 15})

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About Python

Python is a very popular general-purpose programming language which was created by Guido van Rossum, and released in 1991. It is very popular for web development and you can build almost anything like mobile apps, web apps, tools, data analytics, machine learning etc. It is designed to be simple and easy like english language. It's is highly productive and efficient making it a very popular language.

Tutorial & Syntax help

Loops

1. If-Else:

When ever you want to perform a set of operations based on a condition IF-ELSE is used.

if conditional-expression
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else:
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Indentation is very important in Python, make sure the indentation is followed correctly

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For loop is used to iterate over arrays(list, tuple, set, dictionary) or strings.

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mylist=("Iphone","Pixel","Samsung")
for i in mylist:
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While is also used to iterate a set of statements based on a condition. Usually while is preferred when number of iterations are not known in advance.

while condition  
    #code

Collections

There are four types of collections in Python.

1. List:

List is a collection which is ordered and can be changed. Lists are specified in square brackets.

Example:

mylist=["iPhone","Pixel","Samsung"]
print(mylist)

2. Tuple:

Tuple is a collection which is ordered and can not be changed. Tuples are specified in round brackets.

Example:

myTuple=("iPhone","Pixel","Samsung")
print(myTuple)

Below throws an error if you assign another value to tuple again.

myTuple=("iPhone","Pixel","Samsung")
print(myTuple)
myTuple[1]="onePlus"
print(myTuple)

3. Set:

Set is a collection which is unordered and unindexed. Sets are specified in curly brackets.

Example:

myset = {"iPhone","Pixel","Samsung"}
print(myset)

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Dictionary is a collection of key value pairs which is unordered, can be changed, and indexed. They are written in curly brackets with key - value pairs.

Example:

mydict = {
    "brand" :"iPhone",
    "model": "iPhone 11"
}
print(mydict)

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NameDescription
NumPyNumPy python library helps users to work on arrays with ease
SciPySciPy is a scientific computation library which depends on NumPy for convenient and fast N-dimensional array manipulation
SKLearn/Scikit-learnScikit-learn or Scikit-learn is the most useful library for machine learning in Python
PandasPandas is the most efficient Python library for data manipulation and analysis
DOcplexDOcplex is IBM Decision Optimization CPLEX Modeling for Python, is a library composed of Mathematical Programming Modeling and Constraint Programming Modeling