How can you remove all items from a Python set?
- set.clear()
- set.delete_all()
- set.discard_all()
- set.remove_all()
To remove all items from a Python set, you can use the clear() method. This method clears all elements from the set, leaving it empty. The other options do not exist as methods for removing all items from a set.
How can you run a specific test method from a test case in unittest?
- Specify the method name as an argument to unittest.main()
- Use the python -m unittest command
- Use the run method of the test case
- Use the run_test function
To run a specific test method from a test case in unittest, you can use the run method of the test case class and specify the method name as an argument to it. The other options are not the standard way to run specific test methods in unittest.
How can you secure a RESTful API developed using Python?
- Allowing unrestricted access to the API
- Including sensitive data in API responses
- Storing API keys in public repositories
- Using HTTPS for data encryption
To secure a RESTful API, you should use HTTPS to encrypt data in transit, protecting it from eavesdropping and man-in-the-middle attacks. The other options are insecure practices that should be avoided.
How can you secure sensitive information, like API keys, in a Flask or Django application?
- Include them directly in the HTML templates.
- Store them in cookies.
- Store them in plaintext within the source code.
- Use environment variables to store them and access via os module.
Sensitive information like API keys should never be stored in plaintext within the source code because it can be easily exposed. Using environment variables to store such information and accessing them via the os module is a secure practice.
How can you set up a code breakpoint in Python to start the debugger?
- Add the line breakpoint() at the location where you want to break execution.
- Python does not support breakpoints.
- Set a breakpoint using the debugger statement in your code.
- Use the pdb.set_trace() function at the line where you want to set the breakpoint.
You can set up a code breakpoint in Python by using the pdb.set_trace() function at the line where you want to start debugging. This function will pause execution and start the Python debugger at that point.
How can you use the unittest framework to confirm that a specific exception is raised by a piece of code?
- Use assertException() method
- Use assertRaises() method
- Use checkException() method
- Use expectException() method
In unittest, you can use the assertRaises() method to confirm that a specific exception is raised by a piece of code. This method takes the exception class and the callable as arguments and asserts that the callable raises the specified exception.
How can you view the list of variables and their values in the current scope while debugging with Pdb?
- list()
- locals()
- scope()
- vars()
To view the list of variables and their values in the current scope while debugging with Pdb, you can use the locals() function. It returns a dictionary of all local variables in the current scope.
How can you visualize the distribution of a single variable using Seaborn?
- Box plot
- Histogram
- Line plot
- Scatter plot
To visualize the distribution of a single variable in Seaborn, you can use a histogram. A histogram displays the frequency distribution of the data, showing how values are distributed across different bins or intervals.
How do you convert a list of lists into a single flat list in Python?
- [item for sublist in nested_list for item in sublist]
- list(nested_list)
- nested_list.flat()
- nested_list.flatten()
To flatten a list of lists in Python, you can use a list comprehension with nested loops. This method creates a new list containing all elements from the inner lists concatenated together.
How can you optimize the speed of a Python program that performs extensive numerical computations?
- Add more comments and documentation to your code.
- Use the print() function extensively to debug your code.
- Utilize specialized libraries like NumPy and optimize your algorithms.
- Write your own mathematical functions from scratch.
To optimize a Python program for numerical computations, you should use specialized libraries like NumPy and focus on optimizing your algorithms. Debugging with print() and adding comments won't directly improve speed.