An Informal Introduction to Python

6 minute read

Published:

This lesson covers An Informal Introduction to Python 3.10.5, https://docs.python.org/3/tutorial/introduction.html

conda update anaconda

conda create -n “py310” python=3.10.5 ipython –channel conda-forge

# this is the first comment
spam = 1  # and this is the second comment
          # ... and now a third!
text = "# This is not a comment because it's inside quotes."

Introduction

Using Python as a Calculator

Numbers

x = 2 + 2
print(x) #4

x = 50 - 5*6
print(x) #20

x = (50 - 5*6) / 4 
print(x) #5.0

x = 8 / 5 # division always returns a floating point number
print(x) #1.6 

x = 17 // 3 # floor division discards the fractional part 
print(x) #5 

x = 17 % 3  # remainder of the division
print(x) #2

x = 5 ** 2  # 5 squared
print(x) #25

x = 2 ** 7  # 2 to the power of 7
print(x) #128
tax = 12.5 / 100
price = 100.50
price += price * tax
price # 113.0625
round(_, 2) # 113.06 # new cell #last printed expression assigned to variable _ as read-only

Strings

x = 'no quote'  # single quotes
print(x)

x = "no quote"  # double quotes
print(x)

x = 'doesn\'t'  # use \' to escape the single quote...
print(x) # "doesn't"

x = "doesn't"  # ...or use double quotes instead
print(x) # "doesn't"

x = '"Yes," they said.'
print(x) # '"Yes," they said.'

x = "\"Yes,\" they said."
print(x) # '"Yes," they said.'

x = '"Isn\'t," they said.'
print(x) # '"Isn\'t," they said.'

x = 'First line.\nSecond line.'  # \n means newline
print(x)  # with print(), \n produces a new line else \n gets added

x = 'c:\some\name' # \n means newline even in path
print(x)  

x = r'c:\some\name' # r (raw string)
print(r'C:\some\name')  #C:\some\name # note the r (raw string) before the quote

x = """\
Usage: thingy [OPTIONS]
     -h                        Display this usage message
     -H hostname               Hostname to connect to
""" # / to not include newline which is default included
print(x)

x = 2 * "Hello " + "Python" # concatenation
print(x) # Hello Hello Python

x = 2 * "Hello " "Python " # auto concatenation
print(x) # Hello Python Hello Python

text = ('Put several strings within parentheses '
        'to have them joined together.'
       )
print(text) # 'Put several strings within parentheses to have them joined together.'

prefix = 'Py'
# text = prefix 'thon'  # can't concatenate a variable and a string literal without +
# print(text) 

prefix = 'Py'
text = prefix + 'thon'  # concatenate a variable and a string literal with +
# print(text)

word = 'Python' # Sting can be indexing/subscripted
print(word[0])
print(word[-1])
print(word[0:2])

# print(word[42])  # error since the word only has 6 characters
print(word[4:42]) # on # slices handled gracefully
print(word[42:]) # ""

# word[0] = "J" # Immutable
word = "J" + word[1:]
print(word) # Jython

print(len(word)) # 6 #length

Lists

print(squares[0])  # 1 # indexing
print(squares[-1]) # 25 # indexing

# slicing returns a new list
print(squares[-3:]) # [9, 16, 25] 

# references objects that contain other objects
print(squares[:]) # shallow copy 


# Assignment statements in Python do not copy objects
# they create bindings between a target and an object

# shallow or deep relevant for compound objects
s1 = [[1], [4], [9]]
s2 = s1[:]
s1[0][0] = 11 # Mutable
print(s2) # [[11], [4], [9]]

s1 = [[1], [4], [9]]
s2 = s1[:]
s2[0][0] = 11 # Mutable
print(s1) # [[11], [4], [9]]

s1 = [1, 4, 9] 
s2 = s1[:]
s1[0] = [11] # Mutable
print(s2) # [1, 4, 9] # not a compound object

import copy
s1 = [[1], [4], [9]]
s2 = copy.copy(s1) # shallow copy
s1[0][0] = 11
print(s2) # [[11], [4], [9]]


import copy
s1 = [[1], [4], [9]]
s2 = copy.deepcopy(s1) # deep copy
s1[0][0] = 11
print(s2) # [[1], [4], [9]]


cubes = [1, 8, 27, 65, 125]
cubes[3] = 4 ** 3 # Mutable
print(cubes)

cubes.append(6 ** 3)
print(cubes) 

# Assignment to slices
letters = ['a', 'b', 'c', 'd', 'e', 'f', 'g']
letters[3:] = []
print(letters) # ['a', 'b', 'c']

letters = ['a', 'b', 'c', 'd', 'e', 'f', 'g']
letters[3:] = ['D', 'E', 'F', 'G']
print(letters) # ['a', 'b', 'c', 'D', 'E', 'F', 'G']

letters[:] = [] # Clear
print(letters) # []

letters = ['a', 'b', 'c', 'd', 'e', 'f', 'g']
print(len(letters)) # 7

# Nested Lists
letters = [['a', 'b', 'c'], ['d', 'e', 'f', 'g']]
print(len(letters)) # 2

First Steps Towards Programming

# Fibonacci series:

# the sum of two elements defines the next
a, b = 0, 1 # Multiple Assignment

while a < 10: # Loop
    print(a)  # Indention
    a, b = b, a+b
# Fibonacci series:

# the sum of two elements defines the next
a, b = 0, 1 # Multiple Assignment

while a < 10: # Loop
    print(a, end=",")  # Indention
    a, b = b, a+b

Mutable and Immutable

  • Mutable: the internal state of the object can be changed/mutated
    • Lists; Sets; Dictionaries; User-Defined Classes (depends on definition)
  • Immutable: the internal state of the object cannot be mutated
    • Numbers (Integer, Rational, Float, Decimal, Complex & Booleans); Strings; Tuples; Frozen Sets; User-Defined Classes (depends on definition)
  • Objects: everything in Python is an object with three attributes
    • Identity: address that the object refers to in memory
    • Type: kind e.g. integer, list, string etc.
    • Value: value stored by the object e.g. list_nums = [1,2,3]
# id - keeps changing at run - assigned when created
# hexa - memory address in hexadecimal

alphabets = ["A", "B", "C"] # List Mutable
print(alphabets, id(alphabets), hex(id(alphabets)))

alphabets.append("D")
# same object updated - Mutable
print(alphabets, id(alphabets), hex(id(alphabets))) 

print()
alphabets = ("A", "B", "C") # Tuple Immutable
print(alphabets, id(alphabets), hex(id(alphabets)))

alphabets += tuple("D")
# new object created - Immutable
print(alphabets, id(alphabets), hex(id(alphabets)))