Book Image

Hands-On Application Development with PyCharm

By : Quan Nguyen
Book Image

Hands-On Application Development with PyCharm

By: Quan Nguyen

Overview of this book

JetBrain’s PyCharm is the most popular Integrated Development Environment (IDE) used by the Python community thanks to its numerous features that facilitate faster, more accurate, and more productive programming practices. However, the abundance of options and customizations can make PyCharm seem quite intimidating. Hands-on Application Development with PyCharm starts with PyCharm’s installation and configuration process, and systematically takes you through a number of its powerful features that can greatly improve your productivity. You’ll explore code automation, version control, graphical debugging/testing, management of virtual environments, and much more. Finally, you’ll delve into specific PyCharm features that support web development and data science, two of the fastest growing applications in Python programming. These include the integration of the Django framework as well as the extensive support for IPython and Jupyter Notebook. By the end of this PyCharm book, you will have gained extensive knowledge of the tool and be able to implement its features and make the most of its support for your projects.
Table of Contents (23 chapters)
Free Chapter
1
Section 1: The Basics of PyCharm
4
Section 2: Improving Your Productivity
9
Section 3: Web Development in PyCharm
14
Section 4: Data Science with PyCharm
18
Section 5: Plugins and Conclusion

Data viewing made easy with PyCharm's SciView

We already encountered the SciView panel in PyCharm briefly in the previous chapter. In this section, we will fully explore the support for data-related tasks offered by this feature. By the end of this section, I hope you will be able to appreciate the SciView panel, which I personally consider to be PyCharm's best feature when it comes to scientific computing and data science projects.

The code example we will be working with in this section is included in the Chapter12/SciViewPanel folder of our code repository and looks as follows. In essence, this program is the same as the one we were working with in the previous chapter.

However, instead of simply plotting the histogram to indicate the distribution of the x and y variables once, here, we will randomly generate x and y five times using the range function and draw the...