Protecting Constant Variables

Why protect certain variables?

When reading data from a file (like a CSV), it's common to want to keep an intact copy of the original data, even after processing it.

If we accidentally modify a variable containing important data, we risk losing information and making the program difficult to fix.

Convention: write in uppercase

In Python, it's customary to write the names of variables we want to consider as constants entirely in uppercase.

Example:

ORIGINAL_DATA = ["Name", "Firstname", "Age"]

This indicates to code readers (and ourselves!) that this variable should not be modified.

Use a tuple instead of a list

A tuple is an immutable structure in Python: we cannot modify its content after creation.

Thus, to protect a set of fixed values, it's preferable to use a tuple:

EXPECTED_COLUMNS = ("Name", "Firstname", "Age")

Clearly name transformation steps

When processing data (cleaning, sorting, typing...), it's useful to create new variables at each step, with precise names.

For example:

csv_data = load_csv("file.csv")
cleaned_data = clean(csv_data)
typed_data = type(cleaned_data)

This allows:

• keeping previous versions if needed,
• better understanding the sequence of transformations,
• limiting errors by directly modifying the right data.

Summary