
I most like its code assistance and completion feature as a data engineer, PyCharm provides an intelligent code completion feature that helps me to write code faster and with fewer errors. This is especially useful for me when I'm working with large codebases or complex data engineering projects.
I also like its integration with version control systems like Git. This is beneficial for me while I'm working in teams, as it facilitates collaboration and ensures that changes to the codebases are tracked and managed effectively.
It also provides integration with data science libraries and frameworks like NumPy, pandas, and TensorFlow. This makes it easy of use for me to work with multiple tools and libraries seamlessly within the IDE.
I mostly use PyCharm for my data-related operations and changes in the projects as an integrated debugger which allows me to step through my code, inspect variables, identify errors, and fix issues more efficiently. It provides ease of implementation changes in the projects.
It support for jupyter Notebooks and this allows me to develop, run and debug Jupyter Notebooks directly in the IDE.
I also like its customization and extensibility, allowing me to tailor the IDE to my preferences and workflow.
Customer suppprt feature was good and conviniant and if i say about my frequency of use, I use it daily on my working day. Review collected by and hosted on G2.com.
One thing that I say I don't like about Pycharm is, Its limited support for other languages like PyCharm is excellent for python development, but sometimes when I have to work with multiple programming languages then I have to face problems.
Also it is not suitable for small and simple data engineering projects because It take some time to start up, which can be a minor inconvenience if I need to quickly edit a file or perform a simple task. Review collected by and hosted on G2.com.