Instructions

After a recent security review you have been asked to clean up the organization's archived log files.

1. Identify garbled log lines

You need some idea of how many log lines in your archive do not comply with current standards. You believe that a simple test reveals whether a log line is valid. To be considered valid a line should begin with one of the following strings:

• [DEBUG]
• [INFO]
• [WARNING]
• [ERROR]

Implement the is_valid_line function to return True if the log line is valid.

2. Split the log line

Shortly after starting the log parsing project, you realize that one application's logs aren't split into lines like the others. In this project, what should have been separate lines, is instead on a single line, connected by fancy arrows such as <---> or <*~*~>.

In fact, any string that has a first character of <, a last character of >, and zero or more of the following characters ~, *, =, and - in between can be used as a separator in this project's logs.

Implement the split_line function that takes a line and returns a list of strings.

3. Tag lines with user names

You have noticed that some of the log lines include sentences that refer to users. These sentences always contain the string "User", followed by one or more whitespace characters, and then a user name. You decide to tag such lines.

Implement a function tag_with_user_name that processes log lines:

• Lines that do not contain the string "User" remain unchanged.
• For lines that contain the string "User", prefix the line with [USER] followed by the user name.

You can assume that:

• Each occurrence of the string "User" is followed by one or more whitespace character and the user name.
• There is at most one occurrence of the string "User" on each line.
• User names are non-empty strings that do not contain whitespace.