Sell Functionality to reduce quantity in inventory

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Python Anonymous Functions/Lambda Functions

• In Python, anonymous function is a function that is defined without a name.
• Generally normal functions are defined using def keyword, where as anonymous functions are defined using the lambda keyword
• Syntax:

lambda arguments: expression

• Basic example
• Use of Lambda functions in python:
• Example use with filter()
• Example use with map()
• Lambda can be implement to choose the product

selected_product: models.Product = list(filter(lambda product: product.id == id),products)[0]

Using List Comprehensions

• Consider the employees and try to find all the employees having salary greater than or equal to 1 lakh as top earners
• To find the top earners the code is

employees = {
    'Alice': 100000,
    'Bob': 98000,
    'Cena': 127000,
    'Dwayne': 158000,
    'Frank': 88000
}

# find the top earner (every one with salary greater than or equal to 1 lakh)

top_earners = []
for name,salary in employees.items():
    if salary >= 100000:
        top_earners.append((name,salary))

print(top_earners)

• One liner

## One-liner

top_earners = [(n,s) for n,s in employees.items() if s >= 100000 ]
print(top_earners)

Reading a File

• Traditional approach:

file_name = 'data/info.txt'

file_object = open(file_name)
lines = []
for line in file_object:
    lines.append(line.strip())
print(lines)
file_object.close()

• one_liner

print([line.strip() for line in open('data/info.txt')])

Combinining List Comprehensions and Slicing

• Assume we have a large dataset which has stock market prices of some stock during a week
• To create a data sample for some alogrithm, we decided to take every alternate stock price in a day

price = [
    [ 9.9, 9.8, 9.7, 9.5, 9.4 ],
    [ 9.5, 9.6, 9.4, 9.4, 9.2 ],
    [ 8.4, 7.9, 7.9, 8.2, 8.1 ],
    [ 7.1, 5.9, 4.1, 4.8, 5.2 ]
]

sample = [ line[::2] for line in price ]
print(sample)

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