Python Sets and Dictionaries | 6/100 Days of Python Algo trading

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Day 6: Python Sets and Dictionaries

1. What is the primary advantage of using a set to store unique trade identifiers in algorithmic trading?

A) Sets allow duplicate values.

B) Sets ensure there are no duplicate trade identifiers.

C) Sets maintain the order of insertion.

D) Sets support indexing.

2. Which operation is used to find common elements between two sets of stock symbols traded on different days?

A) The union

B) The difference

C) The intersection

D) The symmetric difference

3. How do you efficiently check if a stock symbol is part of the trading set?

A) symbol in trading_set

B) trading_set.get(symbol)

C) trading_set.index(symbol)

D) trading_set.contains(symbol)

4. Which set method is used to add multiple items from a list of stock symbols?

A) add()

B) extend()

C) insert()

D) update()

5. In a scenario where you need to remove symbols no longer in play without causing an error if they aren't present, which method would you use?

A) remove()

B) discard()

C) pop()

D) delete()

6. What is the best way to store and access large datasets of stock prices where the keys are dates and values are prices?

A) Using a list of tuples.

B) Using a dictionary with dates as keys and prices as values.

C) Using a set of prices.

D) Using a tuple of dates and prices.

7. How can dictionaries enhance performance when managing real-time data feeds in algo trading?

A) By maintaining data in ordered sequence.

B) By allowing fast lookup, insert, and delete operations.

C) By preventing any data duplication.

D) By automatically sorting the data.

8. When using a dictionary to track the highest trading volume for each stock symbol, which method updates the volume only if the new volume is higher than the existing one?

A) volumes[symbol] = max(volume, volumes.get(symbol, 0))

B) volumes.update({symbol: volume})

C) volumes.setdefault(symbol, volume)

D) volumes[symbol] = volume if volume > volumes[symbol] else volumes[symbol]

9. Which of the following is a valid way to iterate over keys and values in a dictionary storing stock prices, printing each stock and its price?

A) for stock, price in prices: print(stock, price)

B) for stock in prices.keys(): print(stock, prices[stock])

C) for stock, price in prices.items(): print(stock, price)

D) for price in prices.values(): print(stock, price)

10. In Python dictionaries, what does the popitem() method do, and how can it be used in algo trading?

A) It removes a random item, useful in scenarios requiring random stock removal.

B) It removes and returns the last added item, useful for undoing the last trade action.

C) It deletes all items, quickly clearing out trades at the end of the day.

D) It sorts and removes the lowest value item, used in low-priority trades removal.

11. How would you use a Python dictionary to ensure no duplicate processing of trade identifiers seen in a trading session?

A) Store trade identifiers as keys and boolean as values; check and update during processing.

B) Store trade identifiers as values and timestamps as keys.

C) Use the dictionary's keys to store timestamps and values for identifiers.

D) Implement a list within a dictionary to accumulate identifiers.

12. For a dictionary trade_volumes with stock symbols as keys and volumes as values, what does trade_volumes.setdefault('AAPL', 0) achieve?

A) It returns the volume for 'AAPL', but sets it to 0 if 'AAPL' was not already a key.

B) It deletes the 'AAPL' entry if its value is not 0.

C) It multiplies the existing volume by 0.

D) It reduces the volume of 'AAPL' to 0.

13. What is the purpose of using the update() method in a dictionary when processing real-time trade data?

A) To add new trades without checking for duplicates.

B) To replace the content of the dictionary with new data.

C) To merge another dictionary or iterable of key/value pairs into the dictionary.

D) To reset the dictionary at the end of each trading day.

14. Which Python data structure should be used to implement a FIFO (First In, First Out) queue mechanism for trade orders using only standard libraries?

A) list using append() and pop(0)

B) collections.deque using append() and popleft()

C) dict using update() and popitem()

D) set using add() and pop()

15. When might you use a nested dictionary in algorithmic trading?

A) To store multiple attributes (like price, volume) for each stock symbol on different dates.

B) To enhance the speed of calculations by separating data into smaller chunks.

C) To avoid using classes for simplicity.

D) To implement stack functionality.

16. How do sets differ from dictionaries in Python?

A) Sets store unordered collections of unique elements; dictionaries store key-value pairs.

B) Sets allow duplicate elements; dictionaries do not.

C) Sets support indexing; dictionaries do not.

D) Sets are faster than dictionaries in all aspects.

17. What happens when you attempt to access a non-existing key in a dictionary without using get()?

A) It returns None.

B) It automatically adds the key with a default value of None.

C) It raises a KeyError.

D) It returns a default value that can be predefined.

18. Which dictionary method is most suitable for removing a key and getting its value simultaneously during trade error handling?

A) pop()

B) remove()

C) discard()

D) delete()

19. In the context of algo trading, why might a trader use a set instead of a list to store the days on which trades are allowed?

A) To ensure each day only appears once and check quickly if trading is allowed on a given day.

B) To order the days sequentially by default.

C) To use less memory regardless of the number of days.

D) To automatically update the days at the end of each year.

20. What would be the result of the following dictionary operation {'AAPL': 200, 'GOOG': 800}.get('MSFT', 500)?

A) 500

B) {'MSFT': 500}

C) None

D) Error

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