On a purely technical level, Python names must begin with a letter. They can include any number of letters, digits, and the _ character. Python 3 is based on Unicode, so a letter is not limited to the Latin alphabet. While the A-Z Latin alphabet is commonly used, it's not required.

When creating a descriptive variable, we want to create names that are both specific and articulate the relationships among things in our programs. One widely used technique is to create longer names in a style that moves from particular to general.

The steps to choosing a name are as follows:

How do we choose the broad category part of a name? The general category depends on whether we're talking about a thing or a property of a thing. While the world is full of things, we can create some board groupings that are helpful. Some of the examples are Document, Enterprise, Place, Program, Product, Process, Person, Asset, Rule, Condition, Plant, Animal, Mineral, and so on.

We can then narrow these with qualifiers:

    FinalStatusDocument
    ReceivedInventoryItemName

The first example is a class called Document. We've narrowed it slightly by adding a prefix to call it a StatusDocument. We narrowed it even further by calling it a FinalStatusDocument. The second example is a Name that we narrowed by specifying that it's a ReceivedInventoryItemName. This example required a four-level name to clarify the class.

An object often has properties or attributes. These have a decomposition based in the kind of information that's being represented. Some examples of terms that should be part of a complete name are amount, code, identifier, name, text, date, time, datetime, picture, video, sound, graphic, value, rate, percent, measure, and so on.

The idea is to put the narrow, more detailed description first, and the broad kind of information last:

    measured_height_value
    estimated_weight_value
    scheduled_delivery_date
    location_code

In the first example, height narrows a more general representation term value. And measured_height_value further narrows this. Given this name, we can expect to see other variations on height. Similar thinking applies to weight_value, delivery_date and location_code. Each of these has a narrowing prefix or two.

Python doesn't use static variable definitions. A variable is created when a name is assigned to an object. It's important to think of the objects as central to our processing, and variables as little more than sticky notes that identify an object. Here's how we use the fundamental assignment statement:

      >>> circumference_diameter_ratio = 355/113>>> target_color_name = 'FireBrick'>>> target_color_rgb = (178, 34, 34)

We've created some objects and assigned them to variables. The first object is the result of a calculation. The next two objects are simple literals. Generally, objects are created by expressions that involve functions or classes.

This basic statement isn't the only kind of assignment. We can assign a single object to multiple variables using a kind of duplicated assignment like this:

>>> target_color_name = first_color_name = 'FireBrick'

This creates two names for the same string object. We can confirm this by checking the internal ID values that Python uses:

>>> id(target_color_name) == id(first_color_name)True

This comparison shows us that the internal identifiers for these two objects are the same.

When we look at numbers and collections, we'll see that we can combine assignment with an operator. We can do things like this:

>>> total_count = 0>>> total_count += 5>>> total_count += 6>>> total_count11

We've augmented assignment with an operator. total_count += 5 is the same as total_count = total_count + 5. This technique has the advantage of being shorter.