Lab
A Cloud Guru

Overriding Comparison Operators in Python

When modeling systems in any programming language, we occasionally need our custom objects to be comparable. This is useful for when the class encapsulates a calculation based on some attributes and we want to sort them, or if we want to make direct comparisons to know if two instances are equivalent. In Python, we implement this sort of behavior by defining a suite of double underscore ("dunder") methods on our classes. These allow our custom class instances to be compared using the same operators that we would use if we wanted to know if one integer was greater than or equal to the next. In this hands-on lab, you'll be building a class to model a `Lead` for your sales team so that they can compare and rank leads in the system.

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Path Info

Level

Advanced

Duration

45m

Published

Mar 26, 2021

Challenge

Create the Lead Model and Calculate Lead Score
Before you can start working on the sorting of leads, you need to have a model. Your coworker has requested that you create the Lead class within the lead.py file next to test_lead.py. Be sure to create the initializer for the class and have it take the proper arguments:
- name
- staff_size
- estimated_revenue
- effort_factor
With these implemented, you'll also want to add a method (or calculated property) to return the calculated lead score. Here's the formula to use:
```
1 / (staff_size / estimated_revenue * (10 ** (digits_in_revenue - digits_in_staff_size)) * effort_factor)
```
The automated tests assume that lead_score is a method, but you can adjust the test file if you'd rather it be calculated property instead.

You can run the unit tests with the following command:
```
python -m unittest
```
Challenge

Implement the Equivalence Comparison Operators
The first set of operators that you need to implement are the == and != operators. These should compare the lead score of the two Lead instances being compared. You can implement these using the __eq__ and __ne__ methods, and these methods should compare the lead scores of the instances. Implementing these methods should make a few more automated tests pass.

You can run the unit tests with the following command:
```
python -m unittest
```
Challenge

Implement the Ordering Operators
With the equivalence operators implemented, you're ready to move onto implementing the ordering operators: <, >, <=, and >=. These operators can be implemented by defining the __lt__, __gt__, __le__, and __ge__ methods, and these methods should compare the lead scores of the instances. Implementing these methods should get the remaining automated tests to pass.

You can run the unit tests with the following command:
```
python -m unittest
```

Author

A Cloud Guru

The Cloud Content team comprises subject matter experts hyper focused on services offered by the leading cloud vendors (AWS, GCP, and Azure), as well as cloud-related technologies such as Linux and DevOps. The team is thrilled to share their knowledge to help you build modern tech solutions from the ground up, secure and optimize your environments, and so much more!

What's a lab?

Hands-on Labs are real environments created by industry experts to help you learn. These environments help you gain knowledge and experience, practice without compromising your system, test without risk, destroy without fear, and let you learn from your mistakes. Hands-on Labs: practice your skills before delivering in the real world.