Model and Object-Oriented Programming
Object Oriented Programming is a part of learning Python. The objective of this blog is to introduce OOP with the intention of PBL task to create a database. The foundations for a database is defining a Class and understanding instance data and methods. A database is often a focus of backend coding as it will store persistent data, that can be recalled after the immediate session is closed.
Class and Object Terms
The foundations of Object-Oriented Programming is defining a Class
- In Object-Oriented Programming (OOP), a class is a blueprint for creating an Object. (a data structure). An Object is used like many other Python variables.
- A Class has ...
- a collection of data, these are called Attributes and in Python are pre-fixed using the keyword self
- a collection of Functions/Procedures. These are called *Methods when they exist inside a Class definition.
- An Object is created from the Class/Template. Characteristics of objects ...
- an Object is an Instance of the Class/Template
- there can be many Objects created from the same Class
- each Object contains its own Instance Data
- the data is setup by the Constructor, this is the "init" method in a Python class
- all methods in the Class/Template become part of the Object, methods are accessed using dot notation (object.method())
- A Python Class allow for the definition of @ decorators, these allow access to instance data without the use of functions ...
- @property decorator (aka getter). This enables developers to reference/get instance data in a shorthand fashion (object.name versus object.get_name())
- @name.setter decorator (aka setter). This enables developers to update/set instance data in a shorthand fashion (object.name = "John" versus object.set_name("John"))
- observe all instance data (self._name, self.email ...) are prefixed with "", this convention allows setters and getters to work with more natural variable name (name, email ...)
# A gateway in necessary as a web server cannot communicate directly with Python.
# In this case, imports are focused on generating hash code to protect passwords.
from werkzeug.security import generate_password_hash, check_password_hash
import json
# Define a User Class/Template
# -- A User represents the data we want to manage
class User:
# constructor of a User object, initializes the instance variables within object (self)
def __init__(self, name, uid, password, dob):
self._name = name # variables with self prefix become part of the object,
self._uid = uid
self.set_password(password)
self._dob = dob
# a name getter method, extracts name from object
@property
def name(self):
return self._name
# a setter function, allows name to be updated after initial object creation
@name.setter
def name(self, name):
self._name = name
# a getter method, extracts email from object
@property
def uid(self):
return self._uid
# a setter function, allows name to be updated after initial object creation
@uid.setter
def uid(self, uid):
self._uid = uid
# check if uid parameter matches user id in object, return boolean
def is_uid(self, uid):
return self._uid == uid
#---
# a name getter method, extracts name from object
@property
def dob(self):
return self._name
# a setter function, allows name to be updated after initial object creation
@dob.setter
def dob(self, dob):
self._dob = dob
#---
@property
def password(self):
return self._password[0:10] + "..." # because of security only show 1st characters
# update password, this is conventional setter
def set_password(self, password):
"""Create a hashed password."""
self._password = generate_password_hash(password, method='sha256')
# check password parameter versus stored/encrypted password
def is_password(self, password):
"""Check against hashed password."""
result = check_password_hash(self._password, password)
return result
# output content using str(object) in human readable form, uses getter
def __str__(self):
return f'name: "{self.name}", id: "{self.uid}", psw: "{self.password}"'
# output command to recreate the object, uses attribute directly
def __repr__(self):
return f'Person(name={self._name}, uid={self._uid}, password={self._password})'
# tester method to print users
def tester(users, uid, psw, dob):
result = None
for user in users:
# test for match in database
if user.uid == uid and user.is_password(psw): # check for match
print("* ", end="")
result = user
# print using __str__ method
print(str(user))
return result
# place tester code inside of special if! This allows include without tester running
if __name__ == "__main__":
# define user objects
u1 = User(name='Thomas Edison', uid='toby', password='123toby', dob='11/02/1847')
u2 = User(name='Nicholas Tesla', uid='nick', password='123nick', dob='10/07/1856')
u3 = User(name='Alexander Graham Bell', uid='lex', password='123lex', dob='11/02/1847')
u4 = User(name='Eli Whitney', uid='eli', password='123eli', dob='11/02/1847')
u5 = User(name='Hedy Lemarr', uid='hedy', password='123hedy', dob='11/02/1847')
# put user objects in list for convenience
users = [u1, u2, u3, u4, u5]
# Find user
print("Test 1, find user 3")
u = tester(users, u3.uid, "123lex", u3.dob)
# Change user
print("Test 2, change user 3")
u.name = "John Mortensen"
u.uid = "jm1021"
u.set_password("123qwerty")
u = tester(users, u.uid, "123qwerty", u.dob)
# Make dictionary
'''
The __dict__ in Python represents a dictionary or any mapping object that is used to store the attributes of the object.
Every object in Python has an attribute that is denoted by __dict__.
Use the json.dumps() method to convert the list of Users to a JSON string.
'''
print("Test 3, make a dictionary")
json_string = json.dumps([user.__dict__ for user in users])
print(json_string)
print("Test 4, make a dictionary")
json_string = json.dumps([vars(user) for user in users])
print(json_string)
Hacks
Add new attributes/variables to the Class. Make class specific to your CPT work.
- Add classOf attribute to define year of graduation
- Add setter and getter for classOf
- Add dob attribute to define date of birth
- This will require investigation into Python datetime objects as shown in example code below
- Add setter and getter for dob
- Add instance variable for age, make sure if dob changes age changes
- Add getter for age, but don't add/allow setter for age
- Update and format tester function to work with changes
Start a class design for each of your own Full Stack CPT sections of your project
- Use new
code cellin this notebook- Define init and self attributes
- Define setters and getters
- Make a tester
import json
class ingredient:
def __init__(self,name,den):
self._name = name
self._den = den
@property
def name(self):
return self._name
@name.setter
def name(self,name):
self._name = name
@property
def den(self):
return self._den
@den.setter
def den(self,den):
self._den = den
# tester method to print users
def tester(users, den):
result = None
for user in users:
# test for match in database
if user.den == den: # check for match
print("* ", end="")
result = user
# print using __str__ method
print(str(user))
return result
if __name__ == "__main__":
# define user objects
u1 = ingredient(name='Thomas Edison', den='4')
u2 = ingredient(name='Cinnamon', den='47')
u3 = ingredient(name='Sugar', den='13')
u4 = ingredient(name='Oil', den='9')
u5 = ingredient(name='Baking Soda', den='8')
# put user objects in list for convenience
users = [u1, u2, u3, u4, u5]
# Find user
print("Test 1, find user 3")
u = tester(users, u3.den)
# Change user
print("Test 2, change user 3")
u.name = "Flour"
u.den = "7"
u = tester(users, u.den)
# Make dictionary
'''
The __dict__ in Python represents a dictionary or any mapping object that is used to store the attributes of the object.
Every object in Python has an attribute that is denoted by __dict__.
Use the json.dumps() method to convert the list of Users to a JSON string.
'''
print("Test 3, make a dictionary")
json_string = json.dumps([user.__dict__ for user in users])
print(json_string)
print("Test 4, make a dictionary")
json_string = json.dumps([vars(user) for user in users])
print(json_string)