Python Fundamentals

Notes

install - https://www.python.org
use https://replit.com or visual studio code and install python extension
learn python - https://www.learnpython.org/, https://www.w3schools.com/python/python_intro.asp, Python YT playlist, python overview, FCC - Python Playbook
how to run python progs - python
Projects - Bite-Size Python (afflitate), Big Book of Python projects (afflitate), YouTube - Python playlist
mutable = flexible / lists, dicts, sets
immutable delete and recreate / ints, floats, str, bools, tuples, frozenset
type() - returns data type type(1) = int

Comments

# comment here
name = "Marj" # another comment here
multi-line

"""
multi line
comment
"""

Vars

name = 'Marj', vars stores data, no special characs or start with a #, snake case = 'var_name' or camel case = varName, vars are case sensitive
track vars - %who (list vars) or %whos (lists vars, type, data/info)
concatenate:

x = 'hi'
y = 'world'
z = x + " " + y
print(z) # prints hi world

Casting - specify a type on to a variable

str(3) = '3'
int(3) = 3
float(3) = 3.0

Conversion "enables you to change the int variable from int to str so that you can combine the two variables together. Calling str() on either a float or an int will change the value to a str. However, keep in mind that this change applies only to the output and does not change the type of the original variable."

city = 'NYC'
state = 'NY'
zip_code = 10003

location = city + ', ' + state + ' ' + str(zip_code)
print(location)

Data types

integer (int) - 23 or -22
float - 26.3 or -75.5
complex - 3 + 2j
string (str) - "Marj" or 'Marj'
boolean (bool) - true, false
list - x = ["red", "purple", "blue"]
tuple - x = ("red", "purple", "blue")
dict - x = {"name" : "Marj", "age" : 21}
set x = {"red", "purple", "blue"}

Output and printing

print(4.5)
print("Hey world")
x = "hi", print(x + " world")
print(variable.find('string')) - print(month.find('u')) prints index of charac
print(variable[index]) - print(car[2]) prints specific index / print(car[−2]) prints 2nd to last charac

Input

input('Name: ')
view users input, assign to var

name = input('Name: ')
print(name)

Operators

'=' assigns a value to operator - age = 21 assignment ops - x += 3 same as x = x + 3 and x *= 3 same as x = x * 3, also - -=, /=, %=, *= arithmetic operators - +, -, *, /, %, * (exponents: x ** y), // = floor division
comparisons - ==, !=, <, >, >=, <= - logical - not, and, or / if 1st expression chained by 'and' is false or 'or is True, rest of cluase not evaluated, put simples clauses 1st bitwise - & = AND, | = OR, ~ = NOT

use () to control order of evaluation
Membership tests - in, not in - 'rain' in message = True

Escape characs

\ = escape, \n = new line, \r = return, \t = tab, \b = backspace

User Input

Python 3.6 uses the input() method. Can ask user for input.

username = input("Enter username:")
print("Username is: " + username)

name = input("What's your name?: ")
age = input("How old are you?: ")

print("Hello " + name + "! You are " + age + " years old.")

F Strings

name = "Marj G"
print(f"Your name is {name}.") # 'Your name is Marj G'

user = {name: "Marj G", email: "youremail@gmail.com"}
print(f{"Hello, {user['name']}. Your email address is: {user['email']}.")

String methods

print(hello.upper()) - uppercase entire string
print(hello.lower()) - lowercase
print(hello.capatalize()) - capatalize first letter
print(hello.count('a')) - # of times a value is in a string
print('hello world'.count('o')) - chaining / message[6::].lower().split() - removes 6 characs, lowercase for remaining, split into list
format() - formats values in string
index() - searches the string for a value, returns where the value is found / items.index(200.14) / index(list) <2: (can use start/stop)
swapcase() - lower becomes upper, vice versa
title() - first char of each word is uppercase print(book.title())
strip() - strips away certain characs, or leading and trailing spaces print(mood.strip('!'))
replace() - replace with 2nd argument print(opinion.replace('hard', 'fun'))
len() - # of characs in a string print(len(state)), len(list_name) = # of elements in list
.find(string) - case sensitive, .split(), .join()

List methods

myList = ["red", "orange", "yellow", "green", "blue"] or myList = list(("red", "orange", "yellow", "green", "blue"))

collection which is ordered and changeable/mutable, allows duplicate values
access list - print(myList[:4]) - prints all but blue (1st item has index 0), print(myList[2:]) - prints ygb
.append() - myList.append("indigo") - adds this to the end of list
.insert() - myList.insert(2, "indigo") - adds this after orange
.extend() - myList.extend(secondList) - joins myList and secondList
.remove() - myList.remove("yellow") / use for larger lists - new_items.remove('coat') / if 'C001' in customer_list: customer_list.remove('C005')
.pop() - removes last item, .pop(2) - removes 3rd item
del myList[2] - removes 3rd item / del new_items[1:3]
.clear() - empties list, no content listed, prints []
.sort() - in place, sorts alphabetically or numerically permanently, myList.sort(reverse = True) - descending
.sorted() - not in place, sorts list, original unchanged
.copy() - make a copy, copies over main list to new list, original list the same
.deepcopy() - need to import library, creates independent copy of nested list
.reverse() - in place/permanent, use negative slice for reverse not tin place

Slice Operators

can use on lists, sets, tuples

sliced = [start:stop] or sliced = [start:stop:step]
start - default = 0 : stop - includes all previous at start (not inclusive) : step size - increment default = 1 (returns every element)
[-1] - prints second to last item
[1:4] - start at 1 and stop at 4
[:4] - stop at index 4 but don't include
[2:] - start at 2 and stop at end
[::2] - start at beg, stop at end, every second one
[::-1] - reverse a list
[-2:] - last two characs or elements

Tuples

less memory than lists, executes quicker, reduces user erros myTuple = ("red", "orange", "yellow", "green", "blue") or myTuple = tuple(("red", "orange", "yellow", "green", "blue"))
stores multiple items in a single variable, collection which is ordered and unchangeable or immutable, and allow duplicate values
convert the tuple into a list to be able to change or add values - y = list(myTuple) then y.append("gray"), myTuple = tuple(y)
defined as objs with data type 'tuple' print(type(myTuple)) prints <class 'tuple'>
print(len(myTuple)) - # of items in tuple
create a tuple with only one item - myTuple = ("red",)
print(myTuple[1]) - prints 2nd item - orange
packing - assign values to a tuple.
tuple() - unpacking = extract values

fruits = ("apple", "banana", "cherry")

(green, yellow, red) = fruits

print(green)
print(yellow)
print(red)

Set

collection of unique values, unordered - no indexing or keys, mutable values, set values = unique and immutable, no repeats/duplicates are removed
use cases - more efficient than lists whe performing membership tests ('item' in list), gather unique values w/o looping list(set(shipments_today)), find date shared or not shared btwn items w/o looping set(shipment_today).difference(set(shipment_yesterday))

mySet = {"red", "orange", "yellow", "green", "blue"} ormySet = set(("red", "orange", "yellow", "green", "blue"))

built-in methods - add(), discard(), copy, clear, difference, update, remove, pop
union() - unique values in both sets weekend_set = set(sat_cust).union(sun_cust)
intersection() - all values in both sets - weekend_set.intersection(set(fri_cust))
difference() - returns values in set1 not set2 / set1 - set2, order matters
symmetric_difference() - values not shared, opposite of intersection / set1.symmetric_difference(set2)

Dictionary

collection which is ordered (version 3.7+) and changeable, no duplicate values (overwrites 1st dupe), used to store data values in key:value pairs / keys = unique and immutable, values = not unique, use any data type

myFamily = {
  "child1": {
  "name": "Marj",
  "age": 22,
  "city": "Atlanta"
  },
  "child2": {
  "name": "Vee",
  "age": 27,
  "city": "Orlando"
  }
}

methods to use - copy(), fromkeys(), get() - value for given key get(k, value if key not found), update('k':v) - appends, items() - pairs tuples, keys() - returns keys, values() - returns values
call - item['skis']
add or reassign - item['skis'] = 14.99
delete - del item['coffee']
item_details.values()
item_details.get("item", "we don't carry that item") - used to avoid errors in case item not found
item_details.update({'item': [29.99, 0, 'sold out']})

zip builds dicts, 2 iterables only

list_one = [[..], [..]] # v
list_two = ['..', '..'] # k

item_dict = dict(zip(list_two, list_one))

# output {'..': [..], '..': [..]}


# mulitple iterables
dict(zip(item_ids, zip(names, prices, category, sizes)))

# 1st zip for key, 2nd zip for values

Nested dictionaries outerdict(keys:{innerdict(values): [..], [..]}) item_list = { 2019:{'skis':[249.99,10,'instock'], 'snowboards': [99.99,0,'sold out']}, 2020:{'skis':[259.99,10,'instock'], 'snowboards': [109.99,0,'sold out']}, 2021:{'skis':[269.99,10,'instock'], 'snowboards': [129.99,0,'sold out']} }

call - item_list[2020]['price']

Comprehension

List comprehension - when you want to create a new list based on the values of an existing list. For dict, lists, sets. For tuples x = tuple(condition)

Syntax newlist = [expression for item in iterable if condition == True]

fruits = ["apple", "banana", "cherry", "kiwi", "mango"]

newlist = [x for x in fruits if "a" in x]

print(newlist) # prints ['apple', 'banana', 'mango']

nested lists

list = [
  ['a', 'b', 'c'], 
  ['d', 'e', 'f'],
  ['g', 'h', 'i']
  ]

list[1] = ['d', 'e', 'f']
list[1][1] = 'e'
list[1].append('k') = defk

If statements

examples from W3schools indentation is muy importante!

a = 33
b = 200

if b > a:
  print("b is greater than a")

elif

a = 33
b = 33  

if b > a:
print("b is greater than a")
elif a == b:
print("a and b are equal")

else

a = 200
b = 33

if b > a:
  print("b is greater than a")
elif a == b:
  print("a and b are equal")
else:
  print("a is greater than b")

shorthand if if a > b: print("a is greater than b")

shorthand if else

a = 2
b = 330

print("A") if a > b else print("B")

and

a = 200
b = 33
c = 500

if a > b and c > a:
  print("Both conditions are True")

or

a = 200
b = 33
c = 500

if a > b or a > c:
  print("At least one of the conditions is True")

Nested if condition: if : else : elif : else :

While loops

can execute a set of statements as long as a condition is true (while condition == True:)

Print i as long as i is less than 6:

i = 1

while i < 6:
  print(i)
  i += 1

The break statement we can stop the loop even if the while condition is true.

Exit the loop when i is 3:

i = 1

while i < 6:
  print(i)
  if i == 3:
    break
  i += 1

The continue statement we can stop the current iteration, and continue with the next

Continue to the next iteration if i is 3:

i = 0

while i < 6:
  i += 1
  if i == 3:
    continue
  print(i)

For loops

used for iterating over a sequence (that is either a list, a tuple, a dictionary, a set, or a string). can execute a set of statements, once for each item in a list, tuple, set.

for item in iterable: do this

Print each fruit in a fruit list:

fruits = ["apple", "banana", "cherry"]
for x in fruits:
  print(x)

Prints each letter in a list

for x in "banana":
  print(x)

range function - sequence of ints, generated by start, stop, step or 2 args - start, stop, works well with loops

for i in range(10, -1, -1): 
  print(i)

range(0,100,10)[5] = 50 list(range(0,100,10)) = 0,10,20,30,40,50

loop controls

break statement stops the loop before completion, avoid infinite loops

Exit the loop when x is "banana":

fruits = ["apple", "banana", "cherry"]
for x in fruits:
  print(x)
  if x == "banana":
    break

The continue statement skips to next iteration in loop, repeats prev code

Do not print banana:

fruits = ["apple", "banana", "cherry"]
for x in fruits:
  if x == "banana":
    continue
  print(x)

pass serves as a placeholder for future code, avoiding run errors with incomplete logic

if 'ski' in item
  pass # comment for later

try, except help with error and exception handling, for resolving errors in a loop without stopping execution midway

for rating in ratings:
  try:
    print(int(rating[0]))
  except ValueError: # TypeError, ValueError, ZeroDivisionError
    print('incorrect data')

The try block lets you test a block of code for errors. The try block will generate an exception, because x is not defined:

try:
  print(x)
except:
  print("An exception occurred")

The except block lets you handle the error. In this example, the try block does not generate any error:

try:
  print("Hello")
except:
  print("Something went wrong")
else:
  print("Nothing went wrong")

The finally block lets you execute code, regardless of the result of the try- and except blocks.

try:
  print(x)
except:
  print("Something went wrong")
finally:
  print("The 'try except' is finished")

Print all numbers from 0 to 5, and print a message when the loop has ended:

for x in range(6):
  print(x)
else:
  print("Finally finished!")

for loops cannot be empty, but if you for some reason have a for loop with no content, put in the pass statement to avoid getting an error

for x in [0, 1, 2]:
  pass

enumerate function - returns index and item for each item in an iterable as it loops thru

for index, element in enumerate(list_name):
  print(index, element)
# output (index, element) - 0 5.27 1 8.79 2 17.59 3 21.99

multiple lists

for index, element in enumerate(list_name):
  print(list[index].element)
# output snowboard 5.27 boots 8.79 helmet 17.59

# for -singular- in -plural-
taxes = []
total = []

for subtotal in subtotals:
  tax = round(subtotal * .08, 2)
  total = round(subtotal + tax, 2)
  taxes.append(tax)
  totals.append(total)

print(taxes)
print(totals)

for i, subtotal in enumerate(subtotals):
  if location[i] == 'Sun Valley':
    tax = round(subtotal * .08, 2)
  elif location[i] == 'Stowe':
    tax = round(subtotal * .06, 2)
  else:
    tax = round(subtotal * .0775, 2)

  total = round(subtotal + tax, 2)  
  taxes.append(tax)
  totals.append(total)

print(taxes)
print(totals)

Nested loops

for item in item_list:
  for size in size_list:
    print(f"{item} is available in {size}")

Functions

reusable blocks of code that perform tasks when it is called. You can pass data, known as parameters, into a function. A function can return data as a result. ex. min(), max(), len()
use cases - when repeating code or copying and pasting code - DRY, when you'll use in the future, when you need to share with others, make complex program made readable
tip - package pieces of data cleaning or analysis workflow into funcs to save time
input = args
function - what the input does, call a func, stored elsewhere
output = values to return
side effects - changes or actions made by func

def func(args): do this return output

function is defined using the def keyword:

def function_name(args):
  print("Run")
  
func() # call a function

parameters - is the variable listed inside the parentheses in the function definition
arguments (args) - var names separated by commas, info can be passed into functions, value that is sent to the function when it is called. (below: fname and lname are args)

if your function expects 2 arguments, you have to call the function with 2 arguments

def my_function(fname, lname):
  print(fname + " " + lname)

my_function("Marj", "Gee")

Arbitrary Arguments, *args tuples, pass 1+ args If the number of arguments is unknown, add a * before the parameter name:

def my_function(*kids):
  print("The youngest child is " + kids[2])

my_function("Emil", "Tobias", "Linus")

unpack operator *

def func(x, y):
  print(x, y)

pairs = [(1,2), (3,4)]

for pair in pairs:
  func(*pair) # prints 1 2 \n 3 4

for dict - func(**{'x': 2, 'y': 5})

**kwargs - keyword args = dicts, any # or args, use to unpack dicts and pass it as kwargs (machine learning)

Return Values - to let a function return a value, use the return statement:

def my_function(x):
  return 5 * x

print(my_function(3))
print(my_function(5))
print(my_function(9))

pass statement - func def cant be empty -

  pass

docstrings

def concatenator(string1, string2):
  """ what this func  does
  args
    string1(str): ..
    string2(str): ..
  returns

  """
return string1 + " " + string2

# use ? to retrieve docstring 'concatenator?'

arg types - docstrings = positional args - passed in order defined, keyword any order

Math Functions

min() and max() functions can be used to find the lowest or highest value in an iterable
round() - 'round(#, # of digits)' / round(transactions * .08, 2)
abs() - absolute(-3) = 3
sum() - sum(1,2,3), sum(transactions)
find average - sum(list_name) / len()

x = min(5, 10, 25)
y = max(5, 10, 25)

print(x) # prints 5
print(y) # prints 25

built-in module called math, which extends the list of mathematical functions. To use - import math can use the math.sqrt() method

math.pi (prints 3.141592653589793), math.ceil(), math.floor()

import math

x = math.ceil(1.4)
y = math.floor(1.4)

print(x) # returns 2
print(y) # returns 1

Lambda Functions

A lambda function is a small anonymous function. A lambda function can take any number of arguments, but can only have one expression. Use lambda functions when an anonymous function is required for a short period of time.

Syntax lambda arguments : expression

Add 10 to argument a, and return the result:

x = lambda a : a + 10
print(x(5))

map and filter

x = [1,5,7,10,23,50]

mp = map(lambda i: i + 2, x)

print(list(mp)) # adds 2 to the values and prints new list in brackets

filter mp = filter(lambda i: i % 2 == 0, x) - only return values that are even

Classes and objects

Python is an OOP. most things in Python are objects, with its props and methods. Class = blueprint for creating objects.

Create a class named MyClass, with a property named x, create an object named p1, print value of x:

class MyClass: 
  x = 5 

p1 = MyClass() 

print(p1.x) # prints 5

All classes have a function called __init__(), which is always executed when the class is being initiated.

Use the __init__() function to assign values to object properties, or other operations that are necessary to do when the object is being created:

class Person:
  def __init__(self, name, age):
    self.name = name
    self.age = age

p1 = Person("John", 36)

print(p1.name) # prints John
print(p1.age) # prints 36

The __init__() function is called automatically every time the class is being used to create a new object.

Object Methods - objects can also contain methods. Methods in objects are functions that belong to the object. The self parameter is a reference to the current instance of the class, and is used to access variables that belong to the class. (Doesn't have to be called 'self')

class Person:
  def __init__(self, name, age):
    self.name = name
    self.age = age

  def myfunc(self):
    print("Hello my name is " + self.name)

p1 = Person("John", 36)
p1.myfunc() 

# prints Hello my name is John

del - del p1.age = dels age prop from the p1 obj, del p1 = dels p1 obj

Iterators

an object that contains a countable number of values. w3schools

Modules

Consider a module to be the same as a code library. A file containing a set of functions you want to include in your application.

To create a module just save the code you want in a file with the file extension .py. Save this code in a file named mymodule.py:

def greeting(name):
  print("Hello, " + name)

When using a function from a module, use the syntax: module_name.function_name:

import mymodule
mymodule.greeting("Marj")

import mymodule as mx - can rename module
dir(module) - built-in function to list all the function names (or variable names) in a module
from mymodule import person1, print (person1["age"]) - can choose to import only parts from a module, by using the from keyword (imports only the person1 dictionary from the module)

JSON in Python

import json
If you have a JSON string, you can parse it by using the json.loads() method.
If you have a Python object, you can convert it into a JSON string by using the json.dumps() method.

import json

# a Python object (dict):
x = {
  "name": "John",
  "age": 30,
  "city": "New York"
}

# convert into JSON:
y = json.dumps(x)

# the result is a JSON string:
print(y)

# prints  {"name": "John", "age": 30, "city": "New York"}

When you convert from Python to JSON, Python objects are converted into the JSON (JavaScript) equivalent:

Python	JSON
dict	Object
list	Array
tuple	Array
str	String
int	Number
float	Number
True	true
False	false
None	null

Regular Expression, RegEx

a sequence of characters that forms a search pattern. RegEx can be used to check if a string contains the specified search pattern. w3schools
built-in package called re, which can be used to work with Regular Expressions. import re

Function	Description
findall()	Returns a list containing all matches
search()	Returns a Match object if there is a match anywhere in the string
split()	Returns a list where the string has been split at each match
sub()	Replaces one or many matches with a string

PIP

Package manager for Python packages, or modules if you like. For Python version 3.4 or later, PIP is included by default.

What's a package? A package contains all the files you need for a module. Modules are Python code libraries you can include in your project.

Install pip. to download a pkg - pip install camelcase
Find pkgs - https://pypi.org
Remove pkgs - pip uninstall camelcase
List pkgs - pip list

Name		Name	Last commit message	Last commit date
Latest commit History 28 Commits
project		project
.replit		.replit
README.md		README.md
main.py		main.py

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Python Fundamentals

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Comprehension

If statements

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