Bug Fix: Integer overflow on windows in Project Euler 072

[ManpreetXSingh]

Describe your change:

• Bug Fix in Sol1.py

  • I've identified a bug in sol1.py that appears to be related to integer overflow. This issue specifically arises on Windows platforms because, by default, numpy on Windows 64-bit uses 32-bit integers, whereas on Linux, it employs 64-bit integers, so it also went unnoticed in automated checking.

• Sol2.py

  • Separated prime number generator from solution.

• Checked all Euler Problems

  • I've checked all other project euler solutions using the following command on both windows and linux.
    • pytest scripts\validate_solutions.py
• Both solutions have a runtime of less than or equal to 1 sec. So, I've not tried to optimize anything yet. Let me know if required.

• Add an algorithm?
• Fix a bug or typo in an existing algorithm?
• Documentation change?

Checklist:

• I have read CONTRIBUTING.md.
• [ x This pull request is all my own work -- I have not plagiarized.
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• This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
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[algorithms-keeper]

Multiple Pull Request Detected

@manpreetsingh2004, we are extremely excited that you want to submit multiple algorithms in this repository but we have a limit on how many pull request a user can keep open at a time. This is to make sure all maintainers and users focus on a limited number of pull requests at a time to maintain the quality of the code.

This pull request is being closed as the user already has an open pull request. Please focus on your previous pull request before opening another one. Thank you for your cooperation.

User opened pull requests (including this one): #10672, #10615, #10580, #10558

[quant12345]

@manpreetsingh2004 what numbers are different, show an example?

[ManpreetXSingh]

@quant12345
On windows it produces a negative number -979125625 without specifying dtype=np.int64. With dtype=np.int64, it produces the correct output 303963552391.
It is a known issue with numpy.
References:

• Inconsistent handling of integer overflow between Windows and Linux
• numpy array dtype is coming as int32 by default in a windows 10 64 bit machine
• Numpy returns different results on windows and unix [duplicate]