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My review on PyChram
Updated August 27, 2022

My review on PyChram

Anonymous | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User

Overall Satisfaction with PyCharm

We use PyCharm for doing machine learning experiments and quickly writing task-specific scripts in python, it is very useful when we want to perform multiple experiments with minor changes as it is very fast to do code changes and run experiments in PyCharm because it gives us useful suggestions whenever we need them.
  • Good code completion suggestions.
  • Better git support.
  • Easy to create virtual environments.
  • It will be better if Jupyter Notebook can be integrated with it.
  • Some ready-made frequently used python code can be provided for quickly doing machine learning experiments.
  • Git support can be improved.
  • Support different python versions.
  • We can connect to gpu servers in PyCharm's terminal itself
  • We can run code in PyCharm's terminal.
  • We can quickly show results to managers as we can perform experiments faster as it's easy to clone the code and start experimenting.
  • PR's can be easily created so we can deploy code faster for our customers.
  • Debugging is very efficient so less pain for developers in understanding the code.
When it comes to development and debugging PyCharm is better than Spyder as it provides good debugging support and top-quality code completion suggestions. Compared to Jupiter notebook it's easy to install required packages in PyCharm, also PyChram is a good option when we want to write production-grade code because it provides required suggestions.

Do you think PyCharm delivers good value for the price?

Yes

Are you happy with PyCharm's feature set?

Yes

Did PyCharm live up to sales and marketing promises?

Yes

Did implementation of PyCharm go as expected?

Yes

Would you buy PyCharm again?

Yes

It's easy to create virtual environments and install packages for different projects as we may need project-specific packages for doing our experiments, also it's easy to see what changes we have made and create pull requests faster. But sometimes we want some light python editor like Jupiter notebook as PyCharm is relatively heavier, also Jupiter notebooks are a good option when we need to run remote code on local machines.