#Python #OpenCV #Automation #ML #AI #DEEPLEARNING #MACHINELEARNING #ComputerVision

fruits = ['apple', 'banana', 'cherry']
for index, fruit in enumerate(fruits):
    print(f"{index}: {fruit}")

# Output:
# 0: apple
# 1: banana
# 2: cherry

# With start offset:
for index, fruit in enumerate(fruits, start=1):
    print(f"{index}: {fruit}")
# 1: apple
# 2: banana
# 3: cherry

  lst = [1, 2]
  lst.append(3)
  print(lst)  # Output: [1, 2, 3]
  

  lst = [1, 2]
  lst.extend([3, 4])
  print(lst)  # Output: [1, 2, 3, 4]
  

  lst = [1, 3]
  lst.insert(1, 2)
  print(lst)  # Output: [1, 2, 3]
  

  lst = [1, 2, 2]
  lst.remove(2)
  print(lst)  # Output: [1, 2]
  

  lst = [1, 2, 3]
  item = lst.pop(1)
  print(item, lst)  # Output: 2 [1, 3]
  

  lst = [1, 2, 3]
  lst.clear()
  print(lst)  # Output: []
  

  lst = [1, 2, 2, 3]
  print(lst.count(2))  # Output: 2
  

  lst = [1, 2, 3, 2]
  print(lst.index(2))  # Output: 1
  

  lst = [3, 1, 2]
  lst.sort()
  print(lst)  # Output: [1, 2, 3]
  

  lst = [1, 2, 3]
  lst.reverse()
  print(lst)  # Output: [3, 2, 1]
  

  lst = [1, 2]
  new_lst = lst.copy()
  print(new_lst)  # Output: [1, 2]
  

  lst = [1, 2, 3]
  print(len(lst))  # Output: 3
  

  lst = [3, 1, 2]
  print(min(lst))  # Output: 1
  

  lst = [3, 1, 2]
  print(max(lst))  # Output: 3
  

  lst = [1, 2, 3]
  print(sum(lst))  # Output: 6
  

  lst = [3, 1, 2]
  print(sorted(lst))  # Output: [1, 2, 3]
  

# For loop: Use for fixed iterations over iterables (e.g., processing lists)
fruits = ["apple", "banana", "cherry"]
for fruit in fruits:  # Iterates each element
    print(fruit)      # Output: apple \n banana \n cherry

for i in range(3):    # Numeric sequence (start=0, stop=3)
    print(i)          # Output: 0 \n 1 \n 2

# While loop: Use when iterations depend on a dynamic condition (e.g., user input, convergence)
count = 0
while count < 3:      # Runs as long as condition is True
    print(count)
    count += 1       # Increment to avoid infinite loop! Output: 0 \n 1 \n 2

# Nested loops: Use for 2D data (e.g., matrices, grids); outer for rows, inner for columns
matrix = [[1, 2], [3, 4]]
for row in matrix:    # Outer: each sublist
    for num in row:   # Inner: elements in row
        print(num)    # Output: 1 \n 2 \n 3 \n 4

# Control statements: break (exit loop), continue (skip iteration)
for i in range(5):
    if i == 2:
        continue    # Skip 2
    if i == 4:
        break       # Exit at 4
    print(i)        # Output: 0 \n 1 \n 3

# List comprehension: Concise for loop alternative (use for simple transformations/filtering)
squares = [x**2 for x in range(5) if x % 2 == 0]  # Even squares
print(squares)  # Output: [0, 4, 16]

import re

# Basic search: Find if pattern exists (returns Match object or None)
txt = "The rain in Spain"
match = re.search(r"Spain", txt)  # r"" for raw string (avoids escaping issues)
if match:
    print(match.group())  # Output: Spain (full match)
    print(match.start(), match.end())  # Output: 12 17 (positions)

# findall: Extract all matches as list (non-overlapping)
txt = "The rain in Spain stays mainly in the plain"
emails = re.findall(r"\w+@\w+\.com", "Contact: user1@example.com or user2@test.com")
print(emails)  # Output: ['user1@example.com', 'user2@test.com']

# split: Divide string at matches (like str.split but with patterns)
words = re.split(r"\s+", "Hello   world\twith spaces")  # \s+ matches whitespace
print(words)  # Output: ['Hello', 'world', 'with', 'spaces']

# sub: Replace matches (count limits replacements; use \1 for groups)
cleaned = re.sub(r"\d+", "***", "Phone: 123-456-7890 or 098-765-4321", count=1)
print(cleaned)  # Output: Phone: *** or 098-765-4321 (first number replaced)

# Metacharacters basics:. (any char except \n), ^ (start), $ (end), * (0+), + (1+),? (0-1)
match = re.search(r"^The.*Spain$", txt)  # ^ start, $ end,. any, * 0+ of previous
print(match.group() if match else "No match")  # Output: The rain in Spain

# Character classes: \d (digit), \w (word char), [a-z] (range), [^0-9] (not digit)
nums = re.findall(r"\d+", "abc123def456")  # \d+ one or more digits
print(nums)  # Output: ['123', '456']

words_only = re.findall(r"\w+", "Hello123! World?")  # \w+ word chars (alphanum + _)
print(words_only)  # Output: ['Hello123', 'World']

# Groups: () capture parts; use for extraction or alternation
date = re.search(r"(\d{4})-(\d{2})-(\d{2})", "Event on 2023-10-27")
if date:
    print(date.groups())  # Output: ('2023', '10', '27') (tuples of captures)
    print(date.group(1))  # Output: 2023 (first group)

# Alternation: | for OR (e.g., cat|dog)
animals = re.findall(r"cat|dog", "I have a cat and a dog")
print(animals)  # Output: ['cat', 'dog']

# Flags: re.IGNORECASE (case-insensitive), re.MULTILINE (^/$ per line)
text = "Spain\nin\nSpain"
matches = re.findall(r"^Spain", text, re.MULTILINE)  # ^ matches start of each line
print(matches)  # Output: ['Spain', 'Spain']

# Advanced: Greedy vs non-greedy (*? or +?) to match minimal
html = "<div><p>Text</p></div>"
content = re.search(r"<div>.*?</div>", html)  #.*? non-greedy (stops at first </div>)
print(content.group())  # Output: <div><p>Text</p></div>

# Edge cases: Empty string, no match
print(re.search(r"a", ""))  # Output: None
print(re.findall(r"\d", "no numbers"))  # Output: []

# Compile for reuse (faster for multiple uses)
pattern = re.compile(r"\w+@\w+\.com")
email = pattern.search("email@example.com")
print(email.group() if email else "No email")  # Output: email@example.com