python – Stefan Jaspers

Python

Python – Object Oriented Programming – Design Inheritance & Properties

Posted on June 18, 2020June 19, 2020by Stefan

Best Practices Designing for Inheritance and Polymorphism Polymorphism Interface

# Withdraw amount from each account in list_of_accounts
def batch_withdraw(list_of_accounts, amount):
  for acct in list_of_accounts:
    acct.withdraw(amount)
b, c, s = BankAccount(1000), CheckingAccount(2000), SavingsAccount(3000)
batch_withdraw([b,c,s])   # uses bankaccount.withdraw, checking, Savings

# Withdraw amount from each account in list_of_accounts

def batch_withdraw(list_of_accounts, amount):

for acct in list_of_accounts:

acct.withdraw(amount)

b, c, s = BankAccount(1000), CheckingAccount(2000), SavingsAccount(3000)

batch_withdraw([b,c,s]) # uses bankaccount.withdraw, checking, Savings

batch_withdraw() doesn’t need to check the object to know which withdraw() to call Liskov substitution principle Base class should be interchangeable with any of its subclasses without altering any properties of the program Wherever BankAccout woorks –> CheckingAccount should work as well Syntactically function […]

Python

Python – Object Oriented Programming – Exceptions

Posted on June 18, 2020June 19, 2020by Stefan

Integration with Python Operator overloading : comparison Object equality

class Customer:
  def __init__(self, name, balance):
    self.name, self.balance = name, balance
cust1 = Customer("John Fisher", 2100)
cust2 = Customer("John Fisher", 2100)

cust1 == cust2
> False

class Customer:

def __init__(self, name, balance):

self.name, self.balance = name, balance

cust1 = Customer("John Fisher", 2100)

cust2 = Customer("John Fisher", 2100)

cust1 == cust2

> False

Variables are references

class Customer: 
  def __init__(self, name, balance, id): 
    self.name, self.balance = name, balance 
    self.id = id

cust1 = Customer("John Fisher", 2100, 123) 
cust2 = Customer("John Fisher", 2100, 123) 
cust1 == cust2 
> False

print(cust1)
<__main__.Customer at 0x16549e8e78>
print(cust2)
<__main__.Customer at 0x16549e7e51>

class Customer:

def __init__(self, name, balance, id):

self.name, self.balance = name, balance

self.id = id

cust1 = Customer("John Fisher", 2100, 123)

cust2 = Customer("John Fisher", 2100, 123)

cust1 == cust2

> False

print(cust1)

<__main__.Customer at 0x16549e8e78>

print(cust2)

<__main__.Customer at 0x16549e7e51>

Due to the fact how the objects and variables representing them are stored printing the value of the (customer) object –> prints the memory allocation chunk the value = reference to the memory chunk ))> so when comparing we are […]

Python

Python – Object Oriented Programming – Class Inheritance

Posted on June 17, 2020June 19, 2020by Stefan

Inheritance and Polymorphism Instance and Class Data Core Principles of OOP Inheritance Extending functionality of existing code Polymorphism Creating an unified interface Encapsulation Bundling of data and Methods Instance-level data

class Employee:
  def __init__(self, name, salary):
    self.name = name
    self.salary = salary

emp1 = Employee("Theo Mill", 50000)
emp2 = Employee("Martina Kosova", 65000)

class Employee:

def __init__(self, name, salary):

self.name = name

self.salary = salary

emp1 = Employee("Theo Mill", 50000)

emp2 = Employee("Martina Kosova", 65000)

name , salary are instance attributes self binds to an instance Class-level data

class MyClass:
  # Define a class attribute
  CLASS_ATTR_NAME = attr_value

class MyClass:

# Define a class attribute

CLASS_ATTR_NAME = attr_value

data shared among all instances of a class define class […]

Python

Python Basics – Boolean Operations

Posted on June 10, 2020June 10, 2020by Stefan

Boolean Operations Boolean logic consists of operations done between True and False values : and ( logical conjunction) or ( logical disjunction) not ( logical negation ) Object Evaluation Evaluates as False Constants : False and None Numeric zero : 0 and 0.0 Lengths of zero : “” and [] Evaluates as True everything else […]

Python

Python Basics – Dictionary

Posted on June 10, 2020June 10, 2020by Stefan

Dictionaries Lists

my_list = ['a','b','c','d']
# index     0   1   2   3

my_list[0]
> 'a'
my_list.index['c']
> 2

my_list = ['a','b','c','d']

# index 0 1 2 3

my_list[0]

> 'a'

my_list.index['c']

> 2

Intro

Keys          Values
----          ------ 
Firm Code     FRD
Process Date  10/14/2019
CUSIP         13246879

Keys Values

---- ------

Firm Code FRD

Process Date 10/14/2019

CUSIP 13246879

Representation of a dictionary = { ‘key-1’ : ‘value-1’ , ‘key-2’ : ‘value-2’ , ‘key-3’ : ‘value-3’ , ‘key-4’ : ‘value-4’ } Creation

# Create an empty dict
my_dict = {}
my_dict
> {}

# native
tickersymbols = {'AAPL':'Apple', 'F':'Ford', 'XON':'Exxon'}
> {'AAPL': 'Apple', 'F': 'Ford', 'XON': 'Exxon'}
# OR by lists
tickersymbols = dict([['AAPL','Apple'],['F','Ford'],['XON','Exxon']])
> {'AAPL': 'Apple', 'F': 'Ford', 'XON': 'Exxon'}

# Create an empty dict

my_dict = {}

my_dict

> {}

# native

tickersymbols = {'AAPL':'Apple', 'F':'Ford', 'XON':'Exxon'}

> {'AAPL': 'Apple', 'F': 'Ford', 'XON': 'Exxon'}

# OR by lists

tickersymbols = dict([['AAPL','Apple'],['F','Ford'],['XON','Exxon']])

> {'AAPL': 'Apple', 'F': 'Ford', 'XON': 'Exxon'}

Handling a dictionary

# Adding
tickersymbols['TSLA'] = 'Tesla'
tickersymbols
> {'AAPL': 'Apple', 'F': 'Ford', 'XON': 'Exxon', 'TSLA': 'Tesla'}

# Update
tickersymbols['TSLA'] = 'Tesla_Inc'
tickersymbols
> {'AAPL': 'Apple', 'F': 'Ford', 'XON': 'Exxon', 'TSLA': 'Tesla_Inc'}

# Deleting an entry
del(tickersymbols['F'])
tickersymbols
> {'AAPL': 'Apple', 'XON': 'Exxon', 'TSLA': 'Tesla_Inc'}

# Adding

tickersymbols['TSLA'] = 'Tesla'

tickersymbols

> {'AAPL': 'Apple', 'F': 'Ford', 'XON': 'Exxon', 'TSLA': 'Tesla'}

# Update

tickersymbols['TSLA'] = 'Tesla_Inc'

tickersymbols

> {'AAPL': 'Apple', 'F': 'Ford', 'XON': 'Exxon', 'TSLA': 'Tesla_Inc'}

# Deleting an entry

del(tickersymbols['F'])

tickersymbols

> {'AAPL': 'Apple', 'XON': 'Exxon', 'TSLA': 'Tesla_Inc'}

Accessing

# Entry in dict
tickersymbols['XON']
> 'Exxon'

# No entry in dict
tickersymbols['IBM']
> KeyError: 'IBM'

# Second method
tickersymbols.get('XON')
> 'Exxon'
tickersymbols.get('IBM')
> (nothing)
tickersymbols.get('IBM','Missing ticker')
> 'Missing ticker'

# Entry in dict

tickersymbols['XON']

> 'Exxon'

# No entry in dict

tickersymbols['IBM']

> KeyError: 'IBM'

# Second method

tickersymbols.get('XON')

> 'Exxon'

tickersymbols.get('IBM')

> (nothing)

tickersymbols.get('IBM','Missing ticker')

> 'Missing ticker'

Examples

from datetime import datetime, timedelta
alphabet_hist = {datetime.datetime(2019, 7, 30, 0, 0): 1228, datetime.datetime(2019, 7, 31, 0, 0): 1218.2, datetime.datetime(2019, 8, 1, 0, 0): 1211.78, datetime.datetime(2019, 8, 2, 0, 0): 1196.32}
closing_price_date = datetime.datetime(2019, 8, 2, 0, 0)

# Closing price for day before
day_before_closing_price_date = closing_price_date - timedelta(days=1)
# Safely print closing price day before or None if it's missing
print(alphabet_hist.get(day_before_closing_price_date))
> 1211.78

# Get day eight weeks in future
future_closing_price_date = closing_price_date + timedelta(weeks=8)
# Safely get value for the future date or the string 'Missing'
print(alphabet_hist.get(future_closing_price_date, 'Missing'))
> Missing

# Print with key
print(alphabet_hist)
> {datetime.datetime(2019, 8, 2, 0, 0): 1196.32, datetime.datetime(2019, 8, 1, 0, 0): 1211.78, datetime.datetime(2019, 7, 31, 0, 0): 1218.2, datetime.datetime(2019, 7, 30, 0, 0): 1228}
# Remove entry
del(alphabet_hist[closing_price_date])
# Print with key deleted
print(alphabet_hist)
> {datetime.datetime(2019, 8, 1, 0, 0): 1211.78, datetime.datetime(2019, 7, 31, 0, 0): 1218.2, datetime.datetime(2019, 7, 30, 0, 0): 1228}

from datetime import datetime, timedelta

alphabet_hist = {datetime.datetime(2019, 7, 30, 0, 0): 1228, datetime.datetime(2019, 7, 31, 0, 0): 1218.2, datetime.datetime(2019, 8, 1, 0, 0): 1211.78, datetime.datetime(2019, 8, 2, 0, 0): 1196.32}

closing_price_date = datetime.datetime(2019, 8, 2, 0, 0)

# Closing price for day before

day_before_closing_price_date = closing_price_date - timedelta(days=1)

# Safely print closing price day before or None if it's missing

print(alphabet_hist.get(day_before_closing_price_date))

> 1211.78

# Get day eight weeks in future

future_closing_price_date = closing_price_date + timedelta(weeks=8)

# Safely get value for the future date or the string 'Missing'

print(alphabet_hist.get(future_closing_price_date, 'Missing'))

> Missing

# Print with key

print(alphabet_hist)

> {datetime.datetime(2019, 8, 2, 0, 0): 1196.32, datetime.datetime(2019, 8, 1, 0, 0): 1211.78, datetime.datetime(2019, 7, 31, 0, 0): 1218.2, datetime.datetime(2019, 7, 30, 0, 0): 1228}

# Remove entry

del(alphabet_hist[closing_price_date])

# Print with key deleted

print(alphabet_hist)

> {datetime.datetime(2019, 8, 1, 0, 0): 1211.78, datetime.datetime(2019, 7, 31, 0, 0): 1218.2, datetime.datetime(2019, 7, 30, 0, 0): 1228}