How can you optimize the memory usage of a Python program that handles large data sets?

  • Add more comments to the code
  • Increase variable names length
  • Use generators and iterators
  • Use global variables
To optimize memory usage in Python for programs handling large data sets, you should use generators and iterators. These allow you to work with data one piece at a time, reducing the overall memory footprint by not loading everything into memory at once.

How can you merge two dictionaries in Python?

  • dict1.add(dict2)
  • dict1.concat(dict2)
  • dict1.extend(dict2)
  • dict1.update(dict2)
To merge two dictionaries in Python, you can use the update method. This method updates the first dictionary with the key-value pairs from the second dictionary. It is the recommended way to merge dictionaries in Python. The other options are not valid methods for merging dictionaries.

How can you merge two DataFrames in Pandas based on a common column, ensuring that only the matching rows are included in the result?

  • Using the concat() function
  • Using the join() function with the on parameter
  • Using the merge() function with the how='inner' parameter
  • Using the merge() function with the how='outer' parameter
To merge two DataFrames based on a common column and include only the matching rows, you should use the merge() function with the how='inner' parameter. This performs an inner join and includes only rows with matching keys in both DataFrames.

How can you make a deep copy of a list in Python?

  • copy.deepcopy(original_list)
  • list.copy(original_list)
  • original_list.clone()
  • original_list.deep_copy()
To create a deep copy of a list in Python, you should use the copy.deepcopy() function from the copy module. This function recursively copies all elements and sub-elements of the list, ensuring a truly independent copy.

How can you include JavaScript functionality in a web page developed using a Python web framework?

  • By directly importing JavaScript files in the HTML
  • By embedding JavaScript code within HTML script tags
  • By including JavaScript code in the CSS
  • By using the Python import statement
You can include JavaScript functionality in a web page developed using a Python web framework by embedding JavaScript code within HTML script tags. This allows you to write JavaScript code directly in your HTML files to add interactivity and dynamic behavior to your web pages. Importing JavaScript files or using Python's import statement is not the typical way to include JavaScript in a web page. CSS is used for styling, not for adding functionality.

How can you implement WebSocket in a Flask application to enable real-time functionality?

  • Add WebSocket support directly in Flask's core library.
  • Use Django instead of Flask to implement WebSocket functionality.
  • Use regular HTTP routes in Flask and JavaScript's setInterval for polling.
  • Use the Flask-SocketIO extension to add WebSocket support. Create WebSocket routes using the @socketio.on decorator. Implement server-side logic for real-time interactions.
To enable real-time functionality in a Flask application, Flask-SocketIO is a popular extension. It allows you to implement WebSocket routes and server-side logic for real-time interactions. Polling (Option 2) is not an efficient real-time solution.

How can you implement setup code that needs to run before any tests or test cases in a pytest module?

  • Use a function named setup in the pytest module
  • Use the @pytest.before decorator
  • Use the @pytest.setup decorator
  • Use the conftest.py file with fixtures
To implement setup code that runs before any tests or test cases in a pytest module, you should use the conftest.py file and define fixtures that provide the necessary setup. These fixtures can be used by multiple test modules.

How can you apply a custom function to each element of a Pandas Series or DataFrame?

  • Using the apply() function
  • Using the filter() function
  • Using the for loop in Python
  • Using the transform() function
You can apply a custom function to each element of a Pandas Series or DataFrame using the apply() function. It allows you to apply a given function along the axis of the Series or DataFrame.

How can metaclasses be used to enforce coding standards or patterns within a Python program?

  • Metaclasses can define custom methods like __init__ and __new__ to enforce coding standards or patterns.
  • Metaclasses can directly modify the code of classes they create to enforce standards.
  • Metaclasses can enforce standards by adding comments to class attributes.
  • Metaclasses cannot enforce coding standards; they are only used for class creation.
Metaclasses can define custom methods like __init__ and __new__ to enforce coding standards or patterns by intercepting class creation and customization.

For serializing complex data types, like querysets and model instances, in Django Rest Framework, ____ is used.

  • Converter
  • JSON
  • Serialize
  • Serializer
In Django Rest Framework, you use a Serializer to serialize complex data types like querysets and model instances into JSON or other content types. Serializers provide a convenient way to convert complex data structures into a format that can be easily rendered into JSON, XML, or other content types for API responses.

Django's ____ system is used to maintain user sessions and manage user authentication.

  • auth
  • login
  • security
  • session
Django's auth system is used for user authentication and managing user sessions. It provides features like user registration, login, and user management out of the box.

Can you use a metaclass to modify the behavior of methods within its associated class? How?

  • No, metaclasses can only affect class-level attributes, not methods.
  • Yes, by redefining methods in the metaclass directly.
  • Yes, by using the @modify_method decorator in conjunction with a metaclass.
  • Yes, metaclasses can modify method behavior by intercepting method creation using __new__. You can then modify the method or wrap it with additional functionality.
Metaclasses can indeed modify method behavior by intercepting method creation through __new__. This allows for the customization and enhancement of methods within the associated class.