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Spam filter - step 1

We are going to create a function, which can read the information from files !truth.txt or !prediction.txt into the dictionary data structure.

Preparation

Task:

In a module called utils.py, create a function read_classification_from_file() that will read the mail classes from a text file.

Why do we need it:

We will need this function if we want to create a learning filter, and during the evaluation of the filter quality.

Function read_classification_from_file() (in module utils.py) has to conform to the following specifications:

Input	The path to the text file (most likely either `!truth.txt` or `!prediction.txt`)
Output	A dictionary containing either `SPAM` or `OK` label for each filename in email corpus.

The function loads a text file contaning a pair of strings per line, separated by single space, like this:

email01 OK
email02 OK
email03 SPAM
email1234 OK
...

and creates a dictionary (the order of individual “rows” in the following listing is not important):

{'email1234': 'OK', 'email03': 'SPAM', 'email02': 'OK', 'email01': 'OK'}

If the file is empty, it returns an empty dictionary.