Clean the text

Read first Task 21

Models and keyword matchers both do better on clean text: lower case, no stray spaces, no punctuation. Normalise first, compare second.

Definition and example

Clean the text is the focus of this lesson. Models and keyword matchers both do better on clean text: lower case, no stray spaces, no punctuation. Normalise first, compare second. The task asks you to apply that idea in a small example: Why lower-case the question first. Before you run the code, predict what should happen. Then Inspect the printed output and the values your program uses and compare it with your prediction. If the result differs, change one relevant line and run it again. Testing one change at a time makes the cause of a result easier to understand.

Python 1 automatic check Build the assistant

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# TASK clean-the-text-01: Why lower-case the question first?
# STEPS: Read the explanation. Change one relevant line at a time, then run the code and compare the result with the check on the right.
raw = '   What is the PYTHON fee??  '

def clean(text):
    text = text.strip().lower()
    for mark in '?!.,':
        text = text.replace(mark, '')
    return ' '.join(text.split())

# TODO: produce the required output for this task.

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Checks on this task:

The program output must match “what is the python fee”.

The task and step-by-step instructions are written as comments at the top of the editor. Change one relevant line, run it, and compare the result with these checks.

Incorrect attempts before answer: 0 / 3

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