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

Chapter 12

  1. The SciView panel contains the Plots tab, which displays all the visualizations that have been generated by a Python program, and the Data tab, which can be used to inspect the values of data-related variables.
  2. All of the visualizations that are generated by a Python program are included in the Plot viewer of the SciView panel, where a user can navigate through them with a straightforward graphical interface. Since all of the visualizations are temporarily saved to the panel, the whole program can run in one go. This also allows us to avoid clicking through the Matplotlib plots in order to proceed with the execution, which is the case when executing a Python program from, say, the Terminal.
  3. The data viewer of the SciView panel supports pandas DataFrames and NumPy arrays.
  4. Iterative development is done when a given program is split into different sections so that the...