{"blocks": [{"key": "f6adc9f8", "text": "Scenario", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "5ccec4b5", "text": "Technical phone screen in Python; assess ability to implement similarity metric.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "6dc9d318", "text": "Question", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "0af88be9", "text": "Implement a Python function that computes the cosine similarity between two strings (treat each string as a bag-of-words vector).", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "819adb73", "text": "Hints", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "2d25f9c8", "text": "Tokenize, count word frequencies, form vectors, dot product divided by magnitudes; handle empty inputs.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}], "entityMap": {}}