python-warmup

Get Familiar with Python

• Get Familiar with Python
  • Functions
  • Classes
  • Modules & Packages
  • Generators
  • Inheritance and Polymorphism
  • Decorators
  • Python Virtual Environments
  • What to do next?

Functions

A user-defined function object is created by a function definition (def).

It should be called with an argument list containing the same number of items as the function’s formal parameter list.

# function​
def get_weather_info():​
    pass​

​# functino with input argument
def kill_process(pid):​
    pass​

​# functino with args and kwargs
def update_model(model, *args, **kwargs):​
    pass​

​# one line function
lambda x, y, z: round((x / y) ** z, 2)

Classes

Classes provide a means of bundling data and functionality together.

• Creating a new class creates a new type of object, allowing new instances of that type to be made.
• Each class instance can have attributes attached to it for maintaining its state.
• Class instances can also have methods (defined by its class) for modifying its state.

# class​
class NLPException(Exception):​
    pass​

​# class with functions
class Processing:​

    def clean_stop_words(self):​
        pass​

    def clean_rare_words(self, rare_words_list):​
        pass​

Modules & Packages

Import function and use in another file.

from module1 import greeting

greeting('Metin')
# Hello, Metin!

Generators

A function or method which uses the yield statement is called a generator function. Such a function, when called, always returns an iterator object which can be used to execute the body of the function.

Generators are a simple and powerful tool for creating iterators. Below example shows that they can be easy to create.

def get_fruit1():
    items = ['apple', 'peach', 'pineapple']

    for item in items:
        return item
        
def get_fruit2():
    items = ['apple', 'peach', 'pineapple']

    for item in items:
        print('Current item: ', item, 'Items list: ', items)
        yield item
        print('Going next...')

Inheritance and Polymorphism

A class with some functions.

class Person:​
    def __init__(self, fname, lname):​
        self.firstname = fname​
        self.lastname = lname​
​
    def printname(self):​
        print(self.firstname, self.lastname)

Another class inherits Person class.

class Student(Person):​
    pass​

Inheriting class (Student) now also has printname function, even tough it is defined in inherited class (Person).

x = Student("Mike", "Olsen")​
x.printname()​

Decorators

Decorators wrap a function, modifying its behavior.

Simple example for decorators.

import time 
import math 

def calculate_time(func): 
    def inner1(*args, **kwargs): 
        begin = time.time() 
        func(*args, **kwargs) 
        end = time.time() 
        print("Total time taken in : ", func.__name__, end - begin) 

    return inner1 


@calculate_time
def factorial1(num): 
	time.sleep(2) 
	print('factoria1: ', math.factorial(num)) 


def factorial2(num): 
	time.sleep(2) 
	print('factoria2: ', math.factorial(num)) 


print('Method 1: Sugar syntax')
# sugar syntax!
factorial1(10)

print('Method 2: Sugar syntax')
# long way
calculate_time(factorial2(10))

Decorators can really be useful. For example, below case, where a data class needs to be defined.

from dataclasses import dataclass

class Student:
    name: str
    lastname: str 
    age: int = None
    gpa: float = None
    
    def __init__(self, name='Mike', lastname='Olsen'):
       self.name = name
       self.lastname = lastname


@dataclass
class Student:
    name: str 
    lastname: str 
    age: int = None
    gpa: float = None

Python Virtual Environments

Environment is a container for your application to run isolated with safely and without interrupting any other existing applications in the same machine.

There are many virtual environment tools, but I will be listing some of the well known ones.

• Venv, the standard virtual environments package
• Virtualenv, where venv is mostly developed from.
• Pipenv, both package manager and environment maintainer using virtualenv.
• Conda, anaconda package manager
• Poetry, package manager

What to do next?

• Search GitHub for python tutorials
• W3School
• More on decorators
• Virtual env vs VirtualEnvWrapper