PyCharm for Big Data Analyticshttps://www.trustradius.com/static-code-analysisPyCharmUnspecified8.9671012018-06-12T22:24:31.149Z
June 12, 2018
PyCharm for Big Data Analytics
Score 9 out of 101
Overall Satisfaction with PyCharm
PyCharm is being used by the Business Intelligence department because Python is their language used for big data analytics. We needed a comprehensive IDE for Python in order to utilize good debugging tools and plugin managers, and we needed a one-stop-shop to take care of all of the Python dependencies including Anaconda.
- Debugging tools are great, and coming from experience with other IDEs, this was a breeze and was absolutely needed.
- Switching Python versions easily from 2.x-2.x whenever we needed.
- The package manager was great, and I'm very visual and appreciate good UIs that let me see what I have installed and manage them.
- The easily added scratch pads are great, especially if I don't want to make another project to try a simple snippet.
- You can't fire it up on a big project and expect to get right into the game. PyCharm has to scan everything every time it runs, which can take time and is very annoying.
- If you have many versions of Python, it can take some fiddling to get PyCharm to recognize them all in the proper order.
- Great project turnaround times when we were able to use the debugging tools and other features offered by an IDE.
- We have a small BI developer group, and the licensing was reasonable and easily managed by the machines.
There isn't a ton of great competition for PyCharm, aside from text editors. Atom came closest to functionality but required a lot of plugins to be added, and it's not stable when interacting with massive data frames. A full Python IDE with commercial support was what we needed, and most of the tools out there couldn't offer a good experience, good support, or a well-made tool.