 import hashlib

def bsgs_brute_force(hash160: str, start: int = 0, end: int = 2**32):
    """
    Function to perform a brute force search for a Bitcoin private key using the BSGS algorithm.

    Parameters:
    - hash160: str
        The Hash160 value for which we want to find the corresponding private key.
    - start: int (optional)
        The starting point of the search range. Default is 0.
    - end: int (optional)
        The ending point of the search range. Default is 2^32.

    Returns:
    - int or None:
        Returns the private key if found within the search range, otherwise returns None.

    Raises:
    - ValueError:
        Raises an error if the start value is greater than or equal to the end value.
    """

    # Verifying that the start value is less than the end value
    if start >= end:
        raise ValueError("Start value should be less than the end value.")

    # Iterating through the search range
    for private_key in range(start, end):
        # Converting the private key to bytes
        private_key_bytes = private_key.to_bytes(4, 'big')

        # Hashing the private key using SHA256 twice
        hashed_key = hashlib.sha256(hashlib.sha256(private_key_bytes).digest()).digest()

        # Converting the hashed key to hexadecimal format
        hashed_key_hex = hashed_key.hex()

        # Checking if the hashed key matches the given Hash160 value
        if hashed_key_hex == hash160:
            return private_key

    # If no private key is found within the search range, return None
    return None

# Example usage:
hash160_value = "5dedfbf9ea599dd4e3ca6a80b333c472fd0b3f69"
start_value = 0
end_value = 2**32

result = bsgs_brute_force(hash160_value, start_value, end_value)
if result is not None:
    print(f"Private key found: {result}")
else:
    print("Private key not found within the specified range.")

created 1 year ago

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import sys
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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

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