Code quality and design are key factors in building a successful software application. It is known that a good internal structure assures a good external quality. To improve code quality, several guidelines and best practices are defined. Along with these, a key contribution is brought by unit testing. Just like the source code, unit test code is subject to bad programming practices, known as defects or smells, that have a negative impact on the quality of the software system. As a consequence, the system becomes harder to understand, maintain, and more prone to issues and bugs. In this respect, methods and tools that automate the detection of the aforementioned unit test smells are of the utmost importance. While there are several tools that aim to address the automatic detection of unit test smells, the majority of them are focused on Java software systems. Moreover, the only known such framework designed for applications written in Python performs the detection only on Unittest Python testing library. In addition to this, it relies on an IDE to run, which heavily restricts its usage. The tool proposed within this paper aims to close this gap, introducing a new framework which focuses on detecting Python test smells built with Pytest testing framework. As far as we know, a similar tool to automate the process of test smell detection for unit tests written in Pytest has not been developed yet. The proposed solution also addresses the portability issue, being a cross-platform, easy to install and use Python library. An analysis of the test smell detection results, obtained by running our proposed tool on 3 popular Python open source applications, was also performed.