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Imagine a log file that abridges chats. An example chat might be:
10:00 <john> hi!
10:01 <maria> hello!
10:07 <john> can you link the design?
where john said 6 total words and maria said 1.
Your goal is to present the top N most talkative users in descending order.
You need to write a function that takes an integer N and a filepath.
You are provided a helper function, parse_log, which returns a list of usernames and word counts for each message parsed from the provided file
[(‘john’, 1), (‘maria’, 1), (‘john’, 5)] in the example above.
Output: [“john”, “maria”]
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In this Google interview problem, you are given a chat log where each line has a timestamp, a username, and a message. A helper function parse_log has already broken the log into tuples of (username, word_count) for each message. Your task is to aggregate the counts per user, rank users by how many words they spoke in total, and return the top N usernames in descending order of word count, resolving ties by order implied in the data if needed.
