Before using lazy import, I would import the function at the top and use it later in the function.

import at.favre.lib.crypto.bcrypt.BCrypt;



// Using it somewhere in the program
String password = “Test@123”
String storedHashString = "$2RandomHashString”
isValid = BCrypt.verifyer().verify(password.toCharArray(), storedHashString.toCharArray()).verified

Above, you can see example code where I am using the Bcrypt library's functions to verify a password. However, I wanted to import Bcrypt lazily. Here is what I did:

// Directly wrote this where I wanted to use this function.
Class<?> bCryptClass = Class.forName("at.favre.lib.crypto.bcrypt.BCrypt"); // Get the instance of the class
Method verifyerMethod = bCryptClass.getMethod("verifyer"); //Get the method  from class.
Object verifyer = verifyerMethod.invoke(null); // Invoke verifyer method and store instance in the variable.
Method verifyMethod = verifyer.getClass().getMethod("verify", char[].class, char[].class);
Object result = verifyMethod.invoke(verifyer, password.toCharArray(), storedHashString.toCharArray()); // Final invoke the verify method.
Boolean ans = (Boolean) result.getClass().getField("verified").get(result); // get the verified field.

Few things to notice here:

• I didn’t import the Bcrypt library at the top.

• It will be imported at runtime. If the jar file is not present, it will throw a ClassNotFoundException. So, add a try-catch block if needed.

• My goal was to achieve this because, in my case, the library might or might not exist in the environment.

Let me know if you have a better way to do this. I hope you find it helpful.
P.S. I'm a noob at Java, so don't quote me on this :P

Great codebases don't need comments.

What is BEM?

BEM stands for Block Element Modifier. It is a Methodology that every web developer should follow. This makes development easy and enforces re-usability. Enough of the theory Let's understand this by an example 😉

Here We can say,

• Form = Block(An Independent meaningful entity)
• Input, Link, Button = Element(Part of Black, Which has no standalone meaning)
• Button types (primary/secondary) = Modifier(Represent state of Block or Element.)

BEM Methodology

Let's continue with the above example. This is how you will name your CCS classes.

For Block:

.form {
   // Your CSS
}

For Element:

.form__input {
   // Your CSS
}
.form__button {
   // Your CSS
}
.form__link {
   // Your CSS
}

For Modifier:

.form__button--primary {
   background: "blue";
}
.form__button--secondary {
   background: "green";
}

NOTE: When using modifiers you will put all the common styles in form__button so that you don't repeat them again And here is how your HTML will look like:

<form class="form">
   <input type="email" class="form__input" placeholder="Email">
   <input type="email" class="form__input" placeholder="Email">
   <button class="form__button form__button--primary">Login</button>
   <button class="form__button form__button--secondary">Signup</button>
</form>

That's it! I know it looks like an overhead but trusts me it will help you a lot in many different ways.

Cheatsheets are good when you want to revise some of the concepts, but not an idle way to start learning
I would recommend you to learn in depth from this course: Udemy Course
If you can self learn then this Repository: Github

Index

• Python Cheatsheet
  • Index
  • Theory
  • VSCODE extension:
  • Making a virtual env:
    • Why Virtual env?
  • Comments in python
  • Data Types:
  • Naming conventions:
  • Printing in Python:
  • Numbers in Python:
  • Using with variables:
    • Variables makes it easy to understands the code.
  • Strings in Python:
    • Using directly with print:
    • Taking Input
    • Use , instead of + This will auto seprate them by spaces.
    • Escape characters in python:
    • Check the length of string:
    • String indexing
    • String Slicing
    • String methods:
    • Formatting strings:
    • String Print alignment
  • Lists in Python:
    • Basic Usage
    • Concat
    • Append the list
    • Poping objs
    • Sorting
    • Reverse
    • Nested list
  • Dictionaries in Python
    • Basic Usage
  • Tuples in Python
    • Basic Usage
  • Sets in Python
    • Convert list to set
  • File IO with Python
    • init file obj
    • read contents
    • move the cursor/pointer
    • read line by line
    • close the file
    • Using context manager
    • different modes for file
  • Chaining comparison operators:
  • Python Statements:
    • if, elif, else
    • for loops
    • while loops
    • Statement in python
  • Some useful operators
    • range()
    • enumerate()
    • zip()
    • in operator:
    • min and max:
  • List Comprehensions
  • help function in python
  • Functions in python
    • Basic function with argument and default value
    • args and *kwargs
    • lamda, filter and map
  • Classes in python
    • Basic implementation
    • Inheritance
    • Polymorphism
    • Using Special methods
  • Exception Handling
    • try, except, finally, and else.
  • Decorators
  • Generators
  • Useful Python modules you should look.
  • Working with CSVs in python
  • Working with pdfs in python
  • Sending Emails with python

Theory

• Python is a scripting language.
• Scripting vs Compiled ? - Language like c++/java's code needs to compiled by its compiler, after compilation it is just machine level code. Where as in a scripting language its interpreter will be run the code one the spot one line at a time.

VSCODE extension:

• Python
• Python for vscode
• Magic Python
• Arepl

Making a virtual env:

Why Virtual env?

Because managing python dependencies is a mess, this will install dependencies for that project only instead of globally.

• python -m venv venv this will create a venv folder in your directory.
• source ./venv/bin/activate this will activate this virtual env.

Comments in python

• single line use #

  # single line comments
  

• multiline use '''. often called as docstring, as it is just to document function/classes.

  '''
  This is a example of 
  Multiline comment.
  '''
  

Data Types:

• int # Whole Numbers
• float # Number with decimals.
• str # String
• list # ordered sequence of object
• dict # unordered key-value pairs.
• tup # ordered immutable seq. of objects.
• set # Unordered collection of unique objs.
• bool # Logical value True / False.
• None # no value

Naming conventions:

• Use underscore for variables.
• variables cannot Start with a number.
• Avoid special meaning keywords.
• Use snake case for functions.
• Use CamelCase for Classes names.

Printing in Python:

print("")

Numbers in Python:

print(1+2) # Addition
print(3-2) # Subtraction
print(3*2) # Multiplication
print(3/2) # Division
print(3%2) # Mod.
print(3**2) # Power
print((3 + 10) * 15) # Using Braces.

Using with variables:

a = 10
print(a)
# TO check the type:
print(type(a))

Variables makes it easy to understands the code.

my_income = 100
tax_rate = 0.1
my_taxes = my_income*tax_rate
print("My income tax is",my_taxes)

Strings in Python:

String is nothing but ordered seq. of characters. Note: Strings are immutable

Using directly with print:

print("Simple String")
print('Add quotes inside the  "string" by using single quote.')
print("concat string "+"like this")

Taking Input

greeting = "Hello"
name = input("Enter your name: ")
print(greeting + ' ' + name)

Use , instead of + This will auto seprate them by spaces.

print(greeting,name)

Escape characters in python:

print("Hello\nWorld")
# or
print("""
 ---
Hello
world\
Yeahh!!
"Quotes"
'Single quote'
 ---
""")

Check the length of string:

print(len("Hey"))

String indexing

a = "Hello"
a[0] Will return H

String Slicing

a[start:end:step]
a[0:2] # Start from 0th index till 2(excluding)
a[::2] # Step will be 2.
# We can use this to print a string backwards
s[::-1]

String methods:

# Multiply Strings
a = 'H' * 10

# Upper Case a string
s.upper()

# Lower case
s.lower()

# Splitting
s.split('W')
s.split() # split via whitespace.

Formatting strings:

• .format()
• f"" F-string

  print('The {2} {1} {0}'.format('fox','brown','quick'))
  print('First Object: {a}, Second Object: {b}, Third Object: {c}'.format(a=1,b='Two',c=12.3))
  num = 23.45
  print("My 10 character, four decimal number is:{0:10.4f}".format(num))
  print(f"My 10 character, four decimal number is:{num:10.4f}")
  

  String Print alignment

  left_alignment = "Left Text"
  center_alignment = "Centered Text"
  right_alignment = "Right Text"
  print(f"{left_alignment : <20}|{center_alignment : ^15}|{right_alignment : >20}")
  More about this: https://pyformat.info/
  

Lists in Python:

Basic Usage

# Supports dynamic types, as it is python :)
my_list = [100,2.5,"Mohit"]
# len(my_list) for length
# Change objs:
my_list[0]=1000

Slicing is same as String slicing

Concat

a = [1,2,3]
b = [4,5]
c = a + b

Append the list

my_list.append(10.8)

Poping objs

my_list.pop(index) # default index is -1, returns popped element.

Sorting

a = [1,2,3]
a.sort() # in-place sort, it will modify the list, returns None
# Tip: use sorted(a) it will return the value instead of in-place

Reverse

a = [1,2,3]
a.reverse() # also in-place

Nested list

a = [1, 2, 3, [4,5,]]
print(a[3][1]) # Returns 5.

Dictionaries in Python

Unordered key-value mappings, basically you can have custom keys
Think it like, you can use this to make dynamic variables, where key will be the variable name.
Like list value can be any data type.

Basic Usage

prices = {"apple":10, "orange":20.5}
print(prices)
print(prices["apple"])
print(prices.keys()) # get keys
print(prices.values()) # get values
print(prices.items()) # get items, return tuples with keys and values
print(prices.pop("apple")) # Pop the object
print(prices)
print(prices.clear()) # Clear All
print(prices)
print(prices.get("banana")) # it will check if it is present, return None if not.
print(prices.__contains__("apple")) # Returns true/false

Tuples in Python

Same as list, but immutable.

Basic Usage

a = (1,2,2,4)
print(a)
# Interesting Fact: tuple supports only two methods:
a.count(2) # This can be use with list as well.
a.index(3) # This can be use with list as well.

Sets in Python

Sets are an unordered collection of unique elements.

a = set()
a.add(1)
a.add(1)
a.add(1)
print(a) # {1}

Convert list to set

a = [1,1,2,2,2,3,3,3]
a = set(a)

File IO with Python

init file obj

file = open("file.txt")

read contents

contents = file.read()
print(contents)

move the cursor/pointer

file.seek(0)

read line by line

contents = file.readlines() # returns list of lines.

close the file

file.close()

Using context manager

with open("file.txt") as file:
    print(file.read())

different modes for file

• r: Read
• r+: Read and Write
• w: Write (will override the file)
• w+: Write + Read (will override the file)
• a: Append the file

Chaining comparison operators:

To chain ==, != <, >, >=, <= and is these operators, we have these logical operators

• and
• or
• not

  if 2 > 3 and 2 > 5:
    print("I am inevitable")
  if "hello" is "world" or "india" is "country":
    print("Yeah!!")
  if not 10 == 10:
    print("Tough luck!" )
  

Python Statements:

Indentation is important in the python.

if, elif, else

loc = 'Bank'

if loc == 'Auto Shop':
    print('Welcome to the Auto Shop!')
elif loc == 'Bank':
    print('Welcome to the bank!')
else:
    print('Where are you?')

for loops

# iterate list/string/tuple
l = [1,2,3]
for item in l:
    print(item)
# extraction made easy
list2 = [(2,4),(6,8),(10,12)]
for t1,t2 in list2: # Same as dict. t1 will be key, t2 will be value.
    print(t1) # will print 2,6,10
# Protip about dict: use .value() and .keys() for looping Values/keys.

while loops

in python we can use python with else statement.

x = 1
while x < 3:
    print(f"x is {x}")
    x = x + 1
else:
    print("Uhhoo! x > 3")

Statement in python

• break: Breaks out of the current closest enclosing loop.
• continue: Goes to the top of the closest enclosing loop.
• pass: Does nothing at all, Programmers use this for placeholder.

  def future_method():
    # Todo: implement it later.
    pass
  while True:
    break
  for i in range(10):
    if i == 5:
        #omit
        continue 
    print(i)
  

  Some useful operators

  range()

  range is a generator.
  Syntax: range(start,end,step)
  Use directly with loops for iteration.

a = list(range(0,11,2)) # returns 0,2,4,..10

enumerate()

with help of this we can keep track of index and value.

a = [20,100,5,3,6]
for index,value in enumerate(a):
    print(f"{index}\t{value}")

zip()

zip multiple lists.
a = [1,2,3]
b = [4,5,6]
for item in zip(a,b):
    print(item)

in operator:

a = [1,2,3]
print(3 in a) # True

min and max:

a = [1,2,3]
print(min(a)) # 1
print(max(a)) # 3

List Comprehensions

Quicker and unique way to create lists.

# Grab every letter in string
lst = [x for x in 'word']

# Square numbers in range and turn into list
lst = [x**2 for x in range(0,11)]

# Check for even numbers in a range
lst = [x for x in range(11) if x % 2 == 0]

help function in python

if you are lazy like me, want to learn documentation about specific inbuilt method via terminal, you can use help()

a = [1,2,3]
help(a.insert) # will print info about this method

Functions in python

Basic function with argument and default value

# def keyword to define functions.
def say_hello(name="world"):
    print(f"Hello {name}!")
    # or return f"Hello {name}!" if you want to return it.

args and *kwargs

• *args: N number of arguments, returns tuple.
• **kwargs: N number of keyword arguments, returns dict.

  def total_income(*args, **kwargs):
    print(f"Income for month, {kwargs['month']} is : {sum(args)}")
  total_income(10,20,300,month="July")
  

  lamda, filter and map

  ```python #map def square(num): return num**2 my_nums = [1,2,3,4,5] map(square,my_nums) # 1, 4, 9, 16, 25

filter

def check_even(num): return num % 2 == 0 nums = [0,1,2,3,4,5,6,7,8,9,10] filter(check_even, nums) # 0, 2, 4, 6, 8, 10

lets convert each of the above function to lambda.

map(lambda num:num**2,my_nums) filter(lambda num:num%2==0, nums)

## Classes in python
### Basic implementation
```python
class Circle:
    pi = 3.14

    # Circle gets instantiated with a radius (default is 1)
    def __init__(self, radius=1):
        self.radius = radius 
        self.area = radius * radius * Circle.pi

    # Method for resetting Radius
    def setRadius(self, new_radius):
        self.radius = new_radius
        self.area = new_radius * new_radius * self.pi

    # Method for getting Circumference
    def getCircumference(self):
        return self.radius * self.pi * 2


c = Circle()

print('Radius is: ',c.radius)
print('Area is: ',c.area)
print('Circumference is: ',c.getCircumference())

Inheritance

class Animal:
    def __init__(self):
        print("Animal created")

    def whoAmI(self):
        print("Animal")

    def eat(self):
        print("Eating")


class Dog(Animal):
    def __init__(self):
        Animal.__init__(self)
        print("Dog created")

    def whoAmI(self):
        print("Dog")

    def bark(self):
        print("Woof!")

Polymorphism

class Animal:
    def __init__(self, name):    # Constructor of the class
        self.name = name

    def speak(self):              # Abstract method, defined by convention only
        raise NotImplementedError("Subclass must implement abstract method")


class Dog(Animal):

    def speak(self):
        return self.name+' says Woof!'

class Cat(Animal):

    def speak(self):
        return self.name+' says Meow!'

fido = Dog('Fido')
isis = Cat('Isis')

print(fido.speak())
print(isis.speak())

Using Special methods

Just like __init__ we have more special methods.

class Book:
    def __init__(self, title, author, pages):
        print("A book is created")
        self.title = title
        self.author = author
        self.pages = pages

    def __str__(self):
        return "Title: %s, author: %s, pages: %s" %(self.title, self.author, self.pages)

    def __len__(self):
        return self.pages

    def __del__(self):
        print("A book is destroyed")


book = Book("Python Rocks!", "Jose Portilla", 159)

#Special Methods
print(book)
print(len(book))
del book

Exception Handling

try, except, finally, and else.

def askint():
    while True:
        try:
            val = int(input("Please enter an integer: "))
        except:
            # You can also expect specific error like TypeError or generic type Exception
            print("Looks like you did not enter an integer!")
            continue
        else:
            print("Yep that's an integer!")
            break
        finally:
            print("Finally, I executed!")
        print(val)

Decorators

def new_decorator(func):

    def wrap_func():
        print("Code would be here, before executing the func")

        func()

        print("Code here will execute after the func()")

    return wrap_func

@new_decorator
def func_needs_decorator():
    print("This function is in need of a Decorator")

func_needs_decorator()
# Code would be here, before executing the func
# This function is in need of a Decorator
# Code here will execute after the func()

Generators

# Without generator
def get_me_cubes(n):
    output_list = []
    for i in range(n):
        output_list.append(i**3)
    return output_list

print(get_me_cubes(10))
# With generator
def generate_cubes(n):
    for i in range(n):
        yield i**3

print(generate_cubes(10))

Useful Python modules you should look.

• collections
• os
• shutil
• datetime
• math
• random
• pdb
• re
• timeit
• zipfile

Working with CSVs in python

# don't forget to install csv
import csv
data = open('example.csv',encoding="utf-8")
# passing encoding is important otherwise you will get the Unicode error.
csv_data = csv.reader(data)
# reading
data_lines = list(csv_data)
# writing 
file_to_output = open('to_save_file.csv','w',newline='')
# use 'a' for append
csv_writer = csv.writer(file_to_output,delimiter=',')
csv_writer.writerow(['a','b','c'])
file_to_output.close()

Working with pdfs in python

# don't forget to use PyPDF2
import PyPDF2
f = open('Working_Business_Proposal.pdf','rb')
# we need to pass rb for binary files.
pdf_text = []

pdf_reader = PyPDF2.PdfFileReader(f)

for p in range(pdf_reader.numPages):
    page = pdf_reader.getPage(p)
    pdf_text.append(page.extractText())

Sending Emails with python

import smtplib
smtp_object = smtplib.SMTP('smtp.gmail.com',587)
email = "youremail@email.com"
password = "yourpassword"
# Tip: search about how you generate app passwords.
smtp_object.login(email,password)
from_address = "fromemail@email.com"
to_address = "toemail@email.com"
subject = "Subject"
message = "Message"
msg = "Subject: " + subject + '\n' + message
smtp_object.sendmail(from_address,to_address,msg)
smtp_object.quit()