Book Image

Hands-On Application Development with PyCharm - Second Edition

By : Bruce M. Van Horn II, Quan Nguyen
5 (1)
Book Image

Hands-On Application Development with PyCharm - Second Edition

5 (1)
By: Bruce M. Van Horn II, Quan Nguyen

Overview of this book

In the quest to develop robust, professional-grade software with Python and meet tight deadlines, it’s crucial to have the best tools at your disposal. In this second edition of Hands-on Application Development with PyCharm, you’ll learn tips and tricks to work at a speed and proficiency previously reserved only for elite developers. To achieve that, you’ll be introduced to PyCharm, the premiere professional integrated development environment for Python programmers among the myriad of IDEs available. Regardless of how Python is utilized, whether for general automation scripting, utility creation, web applications, data analytics, machine learning, or business applications, PyCharm offers tooling that simplifies complex tasks and streamlines common ones. In this book, you'll find everything you need to harness PyCharm's full potential and make the most of Pycharm's productivity shortcuts. The book comprehensively covers topics ranging from installation and customization to web development, database management, and data analysis pipeline development helping you become proficient in Python application development in diverse domains. By the end of this book, you’ll have discovered the remarkable capabilities of PyCharm and how you can achieve a new level of capability and productivity.
Table of Contents (24 chapters)
1
Part 1: The Basics of PyCharm
4
Part 2: Improving Your Productivity
9
Part 3: Web Development in PyCharm
15
Part 4: Data Science with PyCharm
19
Part 5: Plugins and Conclusion

Leveraging Jupyter notebooks

Jupyter notebooks are arguably the most-used tool in Python scientific computing and data science projects. In this section, we will briefly discuss the basics of Jupyter notebooks as well as the reasons why they are a great tool for data analysis purposes. Then, we will consider the way PyCharm supports the usage of these notebooks.

We will be working with the jupyter_notebooks project in the chapter source. Don’t forget you’ll need to install the requirements within the requirements.txt file in a virtual environment in order to use the sample project. If you need a refresher on how to do this, refer back to Chapter 3.

Even though we will be writing code in Jupyter notebooks, it is beneficial to first consider a bare-bones program in a traditional Python script so that we can fully appreciate the advantages of using a notebook later on. Let’s look at the main.py file and see how we can work with it. We can see that this file...