[python] pdf to png, 해상도 높게 저장하기 

import fitz  # PyMuPDF

def pdf_to_png(pdf_file, output_folder, dpi=300):
    # Open the PDF file
    pdf_document = fitz.open(pdf_file)
    
    for page_number in range(pdf_document.page_count):
        # Get the page
        page = pdf_document[page_number]
        
        # Set the resolution (DPI)
        zoom = dpi / 72.0
        mat = fitz.Matrix(zoom, zoom)
        image = page.get_pixmap(matrix=mat)
        
        # Save the image as a PNG file
        image.save(f"{output_folder}/page_{page_number + 1}.png", "png")

    # Close the PDF file
    pdf_document.close()

if __name__ == "__main__":
    input_pdf = "input.pdf"  # Replace with your PDF file path
    output_folder = "output_images"  # Replace with your output folder
    dpi = 600  # Adjust DPI as needed
    
    pdf_to_png(input_pdf, output_folder, dpi)

https://pypi.org/project/matrix/

matrix 3.0.0

Generic matrix generator.

Installation

pip install matrix

You can also install the in-development version with:

pip install https://github.com/ionelmc/python-matrix/archive/main.zip

Documentation

https://python-matrix.readthedocs.io/

Development

To run all the tests run:

tox

알고리즘 탐색(Search)

탐색이란, 원하는 값을 찾는 것입니다.

선형 탐색(Linear Search)

순서대로 하나씩 찾는 방법 입니다.

이분(이진) 탐색(Binary Search)

반씩 제외하면서 찾는 방법 입니다.

해시 탐색(Hash Search)

선형탐색이나 이진탐색은, 어떤 값이 어떤 index에 들어있는지에 대한 정보가 없는 상태에서 탐색할 때 사용하는 방식이 었습니다.반면에 해시 탐색은 값과 index를 미리 연결해 둠으로써 짧은 시간에 탐색할 수 있는 알고리즘입니다.

완전 탐색

브루트 포스(Brute Force)

brute: 무식한, force: 힘 무식한 힘으로 해석할 수 있다. 완전탐색 알고리즘. 즉, 가능한 모든 경우의 수를 모두 탐색하면서 요구조건에 충족되는 결과만을 가져옵니다. 이 알고리즘의 강력한 점은 예외 없이 100%의 확률로 정답만을 출력한다는 점입니다.

백트래킹

해를 찾는 도중 해가 아니어서 막히면, 되돌아가서 다시 해를 찾아가는 기법을 말합니다. 최적화 문제와 결정 문제를 푸는 방법이 됩니다.

재귀함수

함수는 자기 자신을 내부에서 호출할 수 있다. 이러한 함수를 재귀 함수라고 한다. 재귀 알고리즘(recursive algorithm)이란 재귀 함수를 이용하여 문제를 해결하는 알고리즘을 말합니다.

# 정렬/탐색 알고리즘 : https://modulabs.co.kr/blog/algorithm-python/
# Search 탐색 

def linear_search(list, target):
    for i in range(0, len(list)):
        if list[i] == target:
            return i
    return None

def binary_search(list, target):
    first = 0
    last = len(list) - 1

    while first <= last:
        midpoint = (first + last) // 2
        if list[midpoint] == target:
            return midpoint
        elif list[midpoint] < target:
            first = midpoint + 1
        else:
            last = midpoint - 1
    return None

def hash_search(list, target):
    hash_table = {}
    for i in range(0, len(list)):
        hash_table[list[i]] = i
    if target in hash_table:
        return hash_table[target]
    return None

def brute_force_search(list, target):
    for i in range(0, len(list)):
        for j in range(i + 1, len(list)):
            if list[i] + list[j] == target:
                return [i, j]
    return None

def recursive_binary_search(list, target):
    if len(list) == 0:
        return False
    else:
        midpoint = len(list) // 2
        if list[midpoint] == target:
            return True 
        else:
            if list[midpoint] < target:
                return recursive_binary_search(list[midpoint + 1:], target)
            else:
                return recursive_binary_search(list[:midpoint], target)







print(linear_search([1,2,3,4,5], 5)) 

print(binary_search([1,2,3,4,5], 5))

print(hash_search([1,2,3,4,5], 5))

print(brute_force_search([1,2,3,4,5], 5))

print(recursive_binary_search([1,2,3,4,5], 5))

BFS(너비 우선 탐색) & DFS(깊이 우선 탐색)

# 정렬/탐색 알고리즘 : https://modulabs.co.kr/blog/algorithm-python/
# Search 탐색 2 : BFS(너비 우선 탐색) & DFS(깊이 우선 탐색)

from collections import deque

graph_list = { 1: set([2, 3]),
                2: set([1, 3, 4]),
                3: set([1, 5]),
                4: set([1]),
                5: set([2,6]),
                6: set([3,4])}

root_node = 1

def bfs(graph, root):
    visited = []
    queue = deque([root])
    while queue:
        node = queue.popleft()
        if node not in visited:
            visited.append(node)
            queue += graph[node] - set(visited)
    return visited

print(bfs(graph_list, root_node))

def dfs(graph, root):
    visited = []
    stack = [root]
    while stack:
        node = stack.pop()
        if node not in visited:
            visited.append(node)
            stack += graph[node] - set(visited)
    return visited

print(dfs(graph_list, root_node))

[python] sudoku 만들기 - 랜덤 문제 

#sudoku puzzle create using python chatGPT
import random

def generate_solved_sudoku():
    base  = 3
    side  = base*base
    # pattern for a baseline valid solution
    def pattern(r,c): return (base*(r%base)+r//base+c)%side

    # randomize rows, columns and numbers (of valid base pattern)
    def shuffle(s): return random.sample(s,len(s)) 
    rBase = range(base) 
    rows  = [ g*base + r for g in shuffle(rBase) for r in shuffle(rBase) ] 
    cols  = [ g*base + c for g in shuffle(rBase) for c in shuffle(rBase) ]
    nums  = shuffle(range(1,base*base+1))

    # produce board using randomized baseline pattern
    board = [ [nums[pattern(r,c)] for c in cols] for r in rows ]
    
    return board

def print_sudoku(board):
    for i in range(9):
        if i % 3 == 0 and i != 0:
            print("- - - - - - - - - - - -")
        for j in range(9):
            if j % 3 == 0 and j != 0:
                print("|", end=" ")
            print(board[i][j], end=" ")
        print()

def remove_numbers(board, difficulty_level):
    """
    Remove numbers from the solved Sudoku grid based on the difficulty level.
    """
    if difficulty_level == 'easy':
        num_to_remove = 30  # Easy: 30 numbers removed
    elif difficulty_level == 'medium':
        num_to_remove = 40  # Medium: 40 numbers removed
    else:
        num_to_remove = 50  # Hard: 50 numbers removed
    
    for _ in range(num_to_remove):
        row = random.randint(0, 8)
        col = random.randint(0, 8)
        if board[row][col] != 0:
            board[row][col] = 0

# Generate a solved Sudoku puzzle
solved_sudoku = generate_solved_sudoku()

# Print the solved Sudoku puzzle
print("Solved Sudoku Puzzle:")
print_sudoku(solved_sudoku)

# Create a copy of the solved puzzle
unsolved_sudoku = [row[:] for row in solved_sudoku]

# Remove numbers to create a puzzle
difficulty_level = 'medium'  # Change difficulty level as needed ('easy', 'medium', 'hard')
remove_numbers(unsolved_sudoku, difficulty_level)

# Print the unsolved Sudoku puzzle (the generated puzzle)
print("\nUnsolved Sudoku Puzzle:")
print_sudoku(unsolved_sudoku)

# sudoku using python

def is_valid_move(board, row, col, num):
    """
    Check if placing 'num' at position (row, col) is a valid move.
    """
    # Check the row
    if num in board[row]:
        return False

    # Check the column
    if num in [board[i][col] for i in range(9)]:
        return False

    # Check the 3x3 subgrid
    start_row, start_col = 3 * (row // 3), 3 * (col // 3)
    for i in range(start_row, start_row + 3):
        for j in range(start_col, start_col + 3):
            if board[i][j] == num:
                return False

    return True

def solve_sudoku(board):
    """
    Solve the Sudoku puzzle using backtracking.
    """
    empty_cell = find_empty_cell(board)

    if not empty_cell:
        # Puzzle is solved
        return True

    row, col = empty_cell

    for num in range(1, 10):
        if is_valid_move(board, row, col, num):
            board[row][col] = num

            if solve_sudoku(board):
                return True

            # If the current placement doesn't lead to a solution, backtrack
            board[row][col] = 0

    # No valid move found, need to backtrack
    return False

def find_empty_cell(board):
    """
    Find an empty cell in the Sudoku grid.
    """
    for i in range(9):
        for j in range(9):
            if board[i][j] == 0:
                return (i, j)
    return None

def print_board(board):
    """
    Print the Sudoku grid.
    """
    for i in range(9):
        if i % 3 == 0 and i != 0:
            print("- - - - - - - - - - - -")
        for j in range(9):
            if j % 3 == 0 and j != 0:
                print("|", end=" ")
            print(board[i][j], end=" ")
        print()

# Example Sudoku puzzle (0 represents empty cells)
sudoku_board = [
    [5, 3, 0, 0, 7, 0, 0, 0, 0],
    [6, 0, 0, 1, 9, 5, 0, 0, 0],
    [0, 9, 8, 0, 0, 0, 0, 6, 0],
    [8, 0, 0, 0, 6, 0, 0, 0, 3],
    [4, 0, 0, 8, 0, 3, 0, 0, 1],
    [7, 0, 0, 0, 2, 0, 0, 0, 6],
    [0, 6, 0, 0, 0, 0, 2, 8, 0],
    [0, 0, 0, 4, 1, 9, 0, 0, 5],
    [0, 0, 0, 0, 8, 0, 0, 7, 9]
]

print("Sudoku Puzzle:")
print_board(sudoku_board)
print("\nSolving...\n")

if solve_sudoku(sudoku_board):
    print("Sudoku Solution:")
    print_board(sudoku_board)
else:
    print("No solution exists.")

How to send text messages with Python for Free

https://medium.com/testingonprod/how-to-send-text-messages-with-python-for-free-a7c92816e1a4

What you’ll need

For this post, I’ll be using the following:

• Python (I used version 3.9.1)
• smtplib (https://docs.python.org/3/library/smtplib.html)
• Email (I use gmail)

It should be noted that if you’re using gmail, like me, you’ll need to setup and use an application password with your account. You can read more information and security warnings on that here: https://support.google.com/accounts/answer/185833?p=InvalidSecondFactor&visit_id=637700239874464736-1954441174&rd=1

import smtplib
import sys
 
CARRIERS = {
    "att": "@mms.att.net",
    "tmobile": "@tmomail.net",
    "verizon": "@vtext.com",
    "sprint": "@messaging.sprintpcs.com"
}
 
EMAIL = "EMAIL"
PASSWORD = "PASSWORD"
 
def send_message(phone_number, carrier, message):
    recipient = phone_number + CARRIERS[carrier]
    auth = (EMAIL, PASSWORD)
 
    server = smtplib.SMTP("smtp.gmail.com", 587)
    server.starttls()
    server.login(auth[0], auth[1])
 
    server.sendmail(auth[0], recipient, message)
 
 
if __name__ == "__main__":
    if len(sys.argv) < 4:
        print(f"Usage: python3 {sys.argv[0]} <PHONE_NUMBER> <CARRIER> <MESSAGE>")
        sys.exit(0)
 
    phone_number = sys.argv[1]
    carrier = sys.argv[2]
    message = sys.argv[3]
 
    send_message(phone_number, carrier, message)