Python Real-World Projects: Crafting your Python Portfolio with Deployable Applications
Develop Python applications using an enterprise approach with unit and acceptance tests, following agile methodologies to create a minimally viable product and iteratively adding features.
- Build two dozen projects to demonstrate mastery of Python and related technologies
- Build a personal project portfolio that can be an important adjunct to a resume or CV
- Learn about data acquisition, preparation, and analysis applications
In today’s job market, a project portfolio often outshines a traditional resume for developers. This guide empowers you to grasp crucial Python concepts while building complete modules and applications that resonate in real-world scenarios. With two dozen meticulously designed projects, showcase your Python mastery and refine your skills further.
Tailored for those with a foundational understanding of class definitions, module creation, and Python’s inherent data structures, this book is your gateway to programming excellence. Harness both the standard library and key external projects like Jupyter Lab, pydantic, pytest, and requests. Embrace an enterprise-oriented methodology, including unit and acceptance testing, and an agile development approach. Dive into the software development lifecycle, starting with a minimum viable product and seamlessly expanding it to add innovative features.
Whether you’re a developer with a working knowledge of Python programming, looking for projects to demonstrate their skills or a developer who want more background in building complete applications that include comprehensive test cases and documentation. his book’s practical approach empowers you to craft deployable projects that exhibit your Python proficiency, paving the way for a successful career.
What you will learn
- Core deliverables for an application including documentation and test cases
- Some approaches to data acquisition including file processing, RESTful APIs, and SQL queries
- Creating a data inspection notebook to establish properties of source data
- Writing applications to validate, clean, convert, and normalize source data
- Use some foundational graphical analysis techniques to visualize data
- Build basic univariate and multivariate statistical analysis tools
- Create reports from raw data using Jupyter Lab publication tools
Who This Book Is For
Beginner to Intermediate level Python Programmers. It is an outright projects book and it assumes the reader to understand basic programming concepts which they have studied during the college times and basic Python understanding like Syntax and writing simple programs. Rest of the book can be interactive project. People knowing programing and seeking jobs can be an ideal readers of the book.