You are assigned to develop a Django app with a complex user permission system. How would you manage and assign permissions to different user roles?
- Assign all permissions to a single user role for simplicity
- Create a separate database table for permissions
- Hard-code permissions in the views
- Use Django's built-in user permission groups
In Django, you can effectively manage and assign permissions to different user roles by using Django's built-in user permission groups. This keeps the code maintainable and allows for easy management of permissions.
Which Python tool would you use to visualize an application’s call stack and identify performance bottlenecks?
- cProfile
- Gunicorn
- Pyflame
- Pygraphviz
Pyflame is a tool for profiling Python applications. It helps visualize the call stack and identify performance bottlenecks. cProfile (Option 1) is a built-in profiler, but it doesn't offer visualization. Gunicorn (Option 3) is a web server. Pygraphviz (Option 4) is for graph visualization, not profiling.
Which Python web framework uses the “Don’t repeat yourself” principle?
- Django
- Flask
- Pyramid
- Tornado
Django is a Python web framework that follows the "Don't repeat yourself" (DRY) principle. DRY encourages developers to avoid duplicating code by providing reusable components and an organized structure.
Which Seaborn function would you use to visualize a bivariate distribution of two variables?
- sns.barplot()
- sns.distplot()
- sns.jointplot()
- sns.plot()
To visualize a bivariate distribution of two variables in Seaborn, you should use the sns.jointplot() function. It creates a scatter plot with marginal histograms and can also display a regression line or a kernel density estimate.
Which sorting algorithm is best suited for large datasets?
- Bubble Sort
- Insertion Sort
- Quick Sort
- Selection Sort
Quick Sort is typically the best choice for sorting large datasets due to its average-case time complexity of O(n log n). Bubble Sort, Insertion Sort, and Selection Sort have worse time complexities and are less efficient for large datasets.
Which status code indicates that a request was successful in HTTP?
- 200 OK
- 401 Unauthorized
- 404 Not Found
- 500 Internal Server Error
The HTTP status code 200 OK indicates that a request was successful. It is used to signal that the request has been successfully received, understood, and accepted by the server. Other codes (404, 500, 401) indicate various error conditions.
Which type of tree would you use to implement an ordered map?
- AVL Tree
- Binary Search Tree (BST)
- Heap
- Red-Black Tree
To implement an ordered map, you would typically use a Binary Search Tree (BST). A BST ensures that elements are stored in sorted order, making it efficient for operations like search, insert, and delete in O(log n) time.
You are asked to create a new column in a DataFrame that is the sum of two other columns. How would you create this new column in Pandas?
- df.create_column('new_column', df.column1 + df.column2)
- df.new_column = df.column1 + df.column2
- df['new_column'] = df['column1'] + df['column2']
- df['new_column'] = df['column1'].add(df['column2'])
To create a new column in a Pandas DataFrame that is the sum of two existing columns, you would use the syntax df['new_column'] = df['column1'] + df['column2']. This operation will perform element-wise addition and create the new column.
You are asked to create a plot comparing the distribution of a variable across different categories, highlighting the median and interquartile range. Which Seaborn plot would you choose?
- Box Plot
- Line Plot
- Swarm Plot
- Violin Plot
To compare the distribution of a variable across categories while highlighting the median and interquartile range, a Violin Plot in Seaborn is a suitable choice. It combines a box plot with a kernel density estimation to provide a richer visualization of the data distribution.
Which Python library is specifically designed for creating static, interactive, and real-time graphs and plots?
- Matplotlib
- NumPy
- Pandas
- Seaborn
Matplotlib is specifically designed for creating static, interactive, and real-time graphs and plots in Python. It is a widely-used plotting library for data visualization.