answer:Here's the modified code that allows the user to input the threshold value at runtime: ```python from termcolor import colored def check_low_inventory(products, threshold): for product, qty in products.items(): if qty < threshold: print(colored(fLow inventory alert: {product} has quantity {qty}, 'red')) else: print(f{product} has quantity {qty}) def get_threshold_from_user(): while True: try: threshold = int(input(Enter the threshold value: )) if threshold <= 0: print(Threshold value must be greater than 0.) continue return threshold except ValueError: print(Invalid input. Please enter an integer value.) # Sample data products = { widget1: 109, widget2: 45, widget3: 208, widget4: 15, widget5: 39, widget6: 402, widget7: 208, widget8: 125, widget9: 55, widget10: 23 } threshold = get_threshold_from_user() check_low_inventory(products, threshold) ``` In this modified code: * We define a new function `get_threshold_from_user` that asks the user to input the threshold value. * We use a `while` loop to continuously ask the user for input until a valid integer value is entered. * We use a `try-except` block to catch `ValueError` exceptions that occur when the user enters a non-integer value. * We also check if the input value is less than or equal to 0, and if so, ask the user to enter a value greater than 0. * We call the `get_threshold_from_user` function to get the threshold value and then pass it to the `check_low_inventory` function.

answer:Here's the modified code that allows the user to input multiple threshold values and sets alerts at multiple levels: ```python from termcolor import colored def check_low_inventory(products, thresholds): thresholds.sort(reverse=True) # Sort thresholds in descending order for product, qty in products.items(): for threshold in thresholds: if qty < threshold: if threshold == thresholds[-1]: # If quantity is below the lowest threshold print(colored(fCritical low inventory alert: {product} has quantity {qty}, 'red')) elif threshold == thresholds[0]: # If quantity is below the highest threshold print(colored(fLow inventory warning: {product} has quantity {qty}, 'yellow')) else: # If quantity is below any other threshold print(colored(fLow inventory alert: {product} has quantity {qty}, 'orange')) break # Break out of the inner loop once a threshold is triggered else: # If no threshold is triggered print(f{product} has quantity {qty}) def get_thresholds_from_user(): thresholds = [] while True: try: threshold = input(Enter a threshold value (or 'done' to finish): ) if threshold.lower() == 'done': if not thresholds: print(Please enter at least one threshold value.) continue return thresholds threshold = int(threshold) if threshold <= 0: print(Threshold value must be greater than 0.) continue thresholds.append(threshold) except ValueError: print(Invalid input. Please enter an integer value or 'done' to finish.) # Sample data products = { widget1: 109, widget2: 45, widget3: 208, widget4: 15, widget5: 39, widget6: 402, widget7: 208, widget8: 125, widget9: 55, widget10: 23 } thresholds = get_thresholds_from_user() check_low_inventory(products, thresholds) ``` In this modified code: * We modify the `get_thresholds_from_user` function to allow the user to input multiple threshold values. The user can enter 'done' to finish entering threshold values. * We modify the `check_low_inventory` function to accept a list of threshold values. * We sort the threshold values in descending order so that we can trigger alerts at multiple levels. * We use a nested loop to check each product's quantity against each threshold value. We break out of the inner loop once a threshold is triggered. * We use different colors to indicate different levels of alerts. The highest threshold triggers a yellow warning, the lowest threshold triggers a red critical alert, and any other threshold triggers an orange alert.

answer:To find the coordinates of the four cells that surround the given coordinate, you can first determine the row and column indices of the given coordinate in the 2-dimensional array. If the coordinate is not on the edge of the array, the four surrounding cells can be found by adding or subtracting 1 to the row and column indices. Here is the Python function implementing this logic: ```python def get_surrounding_cells(array, coordinate): row_index, column_index = coordinate surrounding_cells = [] if row_index > 0: surrounding_cells.append(array[row_index - 1][column_index]) if row_index < len(array) - 1: surrounding_cells.append(array[row_index + 1][column_index]) if column_index > 0: surrounding_cells.append(array[row_index][column_index - 1]) if column_index < len(array[0]) - 1: surrounding_cells.append(array[row_index][column_index + 1]) return surrounding_cells ```

answer:Designing a futuristic city is indeed a monumental task that requires a multifaceted approach. Let's start by envisioning a city that seamlessly integrates technology, sustainability, and innovative design to create a thriving, efficient, and environmentally conscious urban ecosystem. Imagine a city built on a series of interconnected, elevated platforms, allowing for a multi-layered infrastructure that maximizes space while minimizing the urban footprint. The city's foundation would be built using locally sourced, sustainable materials, such as reclaimed wood, low-carbon concrete, and recycled metals. The elevated platforms would be supported by slender, aerodynamic pillars that also serve as wind turbines, generating electricity and reducing the city's reliance on non-renewable energy sources. The city's main thoroughfares would be reserved for advanced public transportation systems, such as Hyperloop tubes, self-driving vehicles, and gravitationally elevated monorails, reducing congestion and emissions. Narrow, winding streets would be designed for pedestrians, cyclists, and personal mobility devices, encouraging a more human-scale, walkable urban experience. To manage waste, the city would employ a closed-loop system, where all organic waste is converted into energy, fertilizer, or nutrient-rich compost. Advanced recycling facilities would utilize AI-powered sorting and processing technologies to maximize material recovery and minimize landfill waste. Grey water systems would collect and treat rainwater and wastewater, providing a reliable source of non-potable water for irrigation, toilet flushing, and industrial processes. In terms of renewable energy, the city would incorporate a diverse array of sources, including solar panels integrated into building facades, wind turbines, and kinetic energy harvesting systems that capture the vibrational energy generated by foot traffic and vehicles. Energy storage systems, such as supercapacitors and hydrogen fuel cells, would ensure a stable and reliable power supply. The city's buildings would be designed with adaptability and resilience in mind, featuring modular, prefabricated components that can be easily assembled, disassembled, and repurposed as needed. This would enable buildings to evolve and change over time, reducing waste and supporting a more dynamic, responsive urban environment. To promote sustainable food systems, the city would incorporate vertical farms, community gardens, and rooftop greenhouses, providing fresh produce to residents and reducing reliance on industrial agriculture. Advanced hydroponics and aeroponics would optimize crop yields while minimizing water and nutrient usage. Innovative public spaces would be designed to foster community engagement, creativity, and well-being. Interactive art installations, virtual reality experiences, and immersive educational environments would encourage social interaction, cultural exchange, and lifelong learning. By integrating these cutting-edge technologies and sustainable design principles, the futuristic city would become a beacon of innovation, a model for urban development that prioritizes the well-being of both people and the planet.