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The Quick and Easy Way to Analyze Numpy Arrays

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The quickest and easiest way to analyze NumPy arrays is by using the numpy.array() method. This method allows you to quickly and easily analyze the values contained in a numpy array. This method can also be used to find the sum, mean, standard deviation, max, min, and other useful analysis of the value contained within a numpy array. Sum You can find the sum of Numpy arrays using the np.sum() function.  For example:  import numpy as np  a = np.array([1,2,3,4,5])  b = np.array([6,7,8,9,10])  result = np.sum([a,b])  print(result)  # Output will be 55 Mean You can find the mean of a Numpy array using the np.mean() function. This function takes in an array as an argument and returns the mean of all the values in the array.  For example, the mean of a Numpy array of [1,2,3,4,5] would be  result = np.mean([1,2,3,4,5])  print(result)  #Output: 3.0 Standard Deviation To find the standard deviation of a Numpy array, you can use the NumPy std() function. This function takes in an array as a par

Best Testing Practices You need for DevOps Projects

Testing is the critical phase in DevOps. The process of DevOps is to speed up the deployment process. That means there are no shortcuts in testing. Covering most relevant test cases is the main thing the tester has to focus.

DevOps Testing

Requirements 

  1. Good maintainable code
  2. Exhaustive coverage of cases
  3. Training documents to Operations team
  4. Fewer bugs in the bug tracker
  5. Less complex and no redundant code

Testing Activities  

    • The team to use Tools to check the quality of code
    • Style checker helps to correct code style
    • Good design avoids bugs in production
    • Code performance depends on the code-quality
    • Bugs in production say poor testing 

    Tester Roles 

    1. Good quality means zero bugs in production.
    2. Design requirements a base to validate testing results.
    3. Automated test scripts give quick feedback on the quality of code.
    4. Right test cases cover all the functional changes.

    The Bottom Line

    • The DevOps approach is seamless integration between Development and Operations without compromising the Quality.
    • Use test cases in a way to test all possible scenarios.
    • Automate the tasks wherever possible to get the quick reply on quality of source code.

    References

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