Answer:
d. integrity
Explanation:
Data integrity is defined as the condition in which all of the data in the database are consistent with the real-world events and conditions.
Data integrity can be used to describe a state, a process or a function – and is often used as a proxy for “data quality”. Data with “integrity” is said to have a complete or whole structure. Data integrity is imposed within a database when it is designed and is authenticated through the ongoing use of error checking and validation routines. As a simple example, to maintain data integrity numeric columns/cells should not accept alphabetic data.
The two access modes that are used when opening a file for input and output when pickling are rb and wb.
<h3>What is pickling?</h3>
Pickle is generally used in Python to serialize and deserialize a Python object structure. In other words, it is the act of transforming a Python object into a byte stream in order to save it to a file/database, maintain program state across sessions, or transport data over a network. By unpickling the pickled byte stream, the original object hierarchy can be recreated. This entire procedure is comparable to object serialization in Java or .Net.
When a byte stream is unpickled, the pickle module first makes an instance of the original object before populating it with the right data. To accomplish this, the byte stream only carries data relevant to the original object instance.
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On windows, it is the type command.
On linux, the cat command outputs the file.
All bytes that represent printable characters will be displayed as ASCII or even Unicode.
