Sure, here's a simple Sudoku puzzle generator in Python:

```python
import random

def generate_sudoku():
    # Initialize an empty 9x9 Sudoku grid
    grid = [[0 for _ in range(9)] for _ in range(9)]

    # Generate a valid Sudoku grid
    fill_grid(grid)

    # Remove numbers to create the puzzle
    remove_numbers(grid)

    return grid

def fill_grid(grid):
    for i in range(9):
        for j in range(9):
            # Try random numbers until a valid number is found
            while True:
                num = random.randint(1, 9)
                if is_valid(grid, i, j, num):
                    grid[i][j] = num
                    break

def is_valid(grid, row, col, num):
    # Check if the number is already in the same row or column
    for i in range(9):
        if grid[row][i] == num or grid[i][col] == num:
            return False

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

    return True

def remove_numbers(grid):
    # Remove numbers from the filled grid to create the puzzle
    # The number of removed numbers can vary based on difficulty level
    # For simplicity, let's remove a fixed number of numbers
    num_to_remove = 45  # Adjust this number to change the difficulty level

    for _ in range(num_to_remove):
        # Choose a random cell that is not already empty
        while True:
            row = random.randint(0, 8)
            col = random.randint(0, 8)
            if grid[row][col] != 0:
                break

        # Temporarily store the cell value and set it to 0
        temp = grid[row][col]
        grid[row][col] = 0

        # Check if the puzzle still has a unique solution
        if not has_unique_solution(grid):
            # If not, revert the cell value and try again
            grid[row][col] = temp

def has_unique_solution(grid):
    # Check if the puzzle has a unique solution using backtracking
    # This function assumes that the current grid is solvable

    # Find the first empty cell in the grid
    for i in range(9):
        for j in range(9):
            if grid[i][j] == 0:
                # Try all numbers from 1 to 9
                for num in range(1, 10):
                    if is_valid(grid, i, j, num):
                        # Temporarily fill the cell with the number and check if the puzzle has a unique solution
                        grid[i][j] = num
                        if not has_unique_solution(grid):
                            # If multiple solutions are found, revert the cell value and return False
                            grid[i][j] = 0
                            return False
                        # If a unique solution is found, revert the cell value and continue searching
                        grid[i][j] = 0
                # If no valid number is found for the empty cell, the puzzle has multiple solutions
                return False
    # If no empty cells are found, the puzzle has a unique solution
    return True

def print_grid(grid):
    for row in grid:
        print(" ".join(map(str, row)))

# Example usage:
sudoku_grid = generate_sudoku()
print("Generated Sudoku puzzle:")
print_grid(sudoku_grid)
```

This code generates a Sudoku puzzle with a given difficulty level by removing a fixed number of numbers from a fully filled grid. You can adjust the difficulty level by changing the `num_to_remove` variable. 
by

Python Online Compiler

Write, Run & Share Python code online using OneCompiler's Python online compiler for free. It's one of the robust, feature-rich online compilers for python language, supporting both the versions which are Python 3 and Python 2.7. Getting started with the OneCompiler's Python editor is easy and fast. The editor shows sample boilerplate code when you choose language as Python or Python2 and start coding.

Taking inputs (stdin)

OneCompiler's python online editor supports stdin and users can give inputs to programs using the STDIN textbox under the I/O tab. Following is a sample python program which takes name as input and print your name with hello.

import sys
name = sys.stdin.readline()
print("Hello "+ name)

About Python

Python is a very popular general-purpose programming language which was created by Guido van Rossum, and released in 1991. It is very popular for web development and you can build almost anything like mobile apps, web apps, tools, data analytics, machine learning etc. It is designed to be simple and easy like english language. It's is highly productive and efficient making it a very popular language.

Tutorial & Syntax help

Loops

1. If-Else:

When ever you want to perform a set of operations based on a condition IF-ELSE is used.

if conditional-expression
    #code
elif conditional-expression
    #code
else:
    #code

Note:

Indentation is very important in Python, make sure the indentation is followed correctly

2. For:

For loop is used to iterate over arrays(list, tuple, set, dictionary) or strings.

Example:

mylist=("Iphone","Pixel","Samsung")
for i in mylist:
    print(i)

3. While:

While is also used to iterate a set of statements based on a condition. Usually while is preferred when number of iterations are not known in advance.

while condition  
    #code 

Collections

There are four types of collections in Python.

1. List:

List is a collection which is ordered and can be changed. Lists are specified in square brackets.

Example:

mylist=["iPhone","Pixel","Samsung"]
print(mylist)

2. Tuple:

Tuple is a collection which is ordered and can not be changed. Tuples are specified in round brackets.

Example:

myTuple=("iPhone","Pixel","Samsung")
print(myTuple)

Below throws an error if you assign another value to tuple again.

myTuple=("iPhone","Pixel","Samsung")
print(myTuple)
myTuple[1]="onePlus"
print(myTuple)

3. Set:

Set is a collection which is unordered and unindexed. Sets are specified in curly brackets.

Example:

myset = {"iPhone","Pixel","Samsung"}
print(myset)

4. Dictionary:

Dictionary is a collection of key value pairs which is unordered, can be changed, and indexed. They are written in curly brackets with key - value pairs.

Example:

mydict = {
    "brand" :"iPhone",
    "model": "iPhone 11"
}
print(mydict)

Supported Libraries

Following are the libraries supported by OneCompiler's Python compiler

NameDescription
NumPyNumPy python library helps users to work on arrays with ease
SciPySciPy is a scientific computation library which depends on NumPy for convenient and fast N-dimensional array manipulation
SKLearn/Scikit-learnScikit-learn or Scikit-learn is the most useful library for machine learning in Python
PandasPandas is the most efficient Python library for data manipulation and analysis
DOcplexDOcplex is IBM Decision Optimization CPLEX Modeling for Python, is a library composed of Mathematical Programming Modeling and Constraint Programming Modeling