Here we got into the specific features in PyCharm that streamline various tasks and processes in Python programming. From creating and managing virtual environments to version control, testing, and debugging, PyCharm handles all the low-level, backend tasks, leaving its users on a high level so that they can focus on the development side of things.

During these discussions, we saw that PyCharm can work well with external software and tools such as Conda and Git/GitHub that are common elements of a Python project. On another note, the testing and debugging options even extend to other non-traditional Python scripts, such as PyCharm code cells and Jupyter notebooks. This feature allows PyCharm users to combine the unique advantages of working with different tools in one environment.

The point about PyCharm handling low-level repetitive tasks is also illustrated by the wide range of different project types that PyCharm offers (simply Python projects, web development such as Django or Flask, scientific computing, Angular, or even React projects), as illustrated here:

Each type of project is created with various boilerplate files and folders automatically generated so that the programmer can immediately start working.

One of the best supports that PyCharm offers must be its intelligent coding support engine. Having the ability to adjust its scope, the code-completion engine in PyCharm allows users to find the most relevant suggestions with respect to other files in the same project. The quality of this coding support engine ensures that the code written in PyCharm is compatible with all conventions and standards of the Python community.

Having learned about the various features and functionalities PyCharm offers to improve our productivity, we thus move onto to the specific usage of PyCharm in web development projects.