# Topic covered
* Exception Handling
* Syntax Errors
* Runtime Errors
* Custom Exception
* List Of General Use Exceptions
* Python’s Exception Hierarchy

# Topic covered
* Regular expression
* Raw string
* String operation
* RegEx function
* Metacharacters
* Advance RegEx

# Topic covered
* File Handling
* Various properties of File Object
* Allowed Modes
* Open and close file
* The with statement
* seek() and tell() methods
* Writing data into files
* Reading Data from files
* Buffer Read and Write file
* Zipping and Unzipping Files

# Topic covered
* Python OS Module
* Common OS functions
* OS Path
* Additional OS Fxn

Scopes and Name Resolution

Local scope - inside a function

Enclosing scope - from outer function if nested

Global - Top leve script

def serve_chai():
    chai_type = "Masala" # local scope
    print(f"Inside function {chai_type}")
chai_type = "Lemon"
serve_chai()
print(f"Outside function: {chai_type}")


def chai_counter():
    chai_order = "lemon" # Enclosing scope
    def print_order():
        chai_order = "Ginger"
        print("Inner:", chai_order)
    print_order()
    print("Outer: ", chai_order)
chai_order = "Tulsi" # Global
chai_counter()
print("Global :", chai_order)

NonLocal - The nonlocal keyword is used to modify a variable in an enclosing but non-global scope, which is specifically relevant for nested functions.

# Topic covered
* Generators
* Iterable and Iterator in Python
    * Create an Iterator Class

11.1 Generators

Generator is a function which is responsible to generate a sequence of values.

We can write generator functions just like ordinary functions, but it uses yield keyword to return values.

def simpleGeneratorFun(): 
  yield 1         
  yield 2         
  yield 3         

for value in simpleGeneratorFun(): 
  print(value, end=' ')
# 1 2 3

x = simpleGeneratorFun() 
print(list(x))
# [1, 2, 3]

Advantages of Generator Functions

1. When compared with class level iterators, generators are very easy to use
2. Improves memory utilization and performance.
3. Generators are the best suitable for reading data from large number of large files
4. Generators work great for web scraping and crawling.

* Saves memory
* Don't want the result immediately
* Lazy evaluation

[…] → list comprehension (eager, stores everything in memory).

We will get MemoryError in this case because all these values are required to store in the memory.

# Topic covered
* Built-in Functions
    * Anonymous/lambda Functions
    * map() function
    * reduce() function
    * filter() function
    * eval() function

10.1 Anonymous/lambda Functions

Sometimes we can declare a function without any name, such type of nameless functions are called anonymous/lambda functions

The main purpose of anonymous function is just for instant use(i.e. for one time usage)

AKA lambda functions or shorthand function

# Syntax
lambda argument_list : expression

print((lambda x: x + 1)(2)) # 3

s = lambda n:n*n
print(s(4)) # 64

s = lambda a,b:a+b
print(s(2, 3)) # 5

s = lambda a,b:a if a>b else b
print(s(10,20)) # 20
print(s(100,200)) # 200

print((lambda x, y, z=3: x + y + z)(1, 2))

Note

Lambda Function internally returns expression value and we are not required to write return statement explicitly

# Topic covered
* Dictionary Data Structure
* Dictionary declaration
* Keys of Dictionary
* Update Dictionary
* Display/access Dictionary
* Dictionary in-built function
* Dictionary Comprehension
* Iterate Through a Dictionary
* Usage

# Topic covered
* Functions
* User Defined Functions
* Return Statement
* Parameters & Arguments
    * Positional arguments
    * Keyword arguments
    * Default arguments
    * Variable length arguments

# Topic covered
* Tuple Data Structure
  * Tuple Packing and Unpacking
  * Mathematical operators for tuple
  * Tuple in-built function
  * Tuple Comprehension
* Set Data Structure
  * Mathematical operations on the Set
  * Set in-built function
  * Set Comprehension