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Community insights

TrustRadius Insights for PyCharm are summaries of user sentiment data from TrustRadius reviews and, when necessary, third party data sources.

Pros

Syntax Highlighting: Users have found Syntax Highlighting in PyCharm to be extremely helpful for understanding code with just a glimpse. They appreciate how it improves their code reading and writing experience by providing visual cues and color-coded formatting. This feature allows them to quickly identify syntax errors, variable references, and function calls, ultimately enhancing their overall productivity.

Version Control: Many users praise Version Control in PyCharm for its ability to provide a comprehensive history of files they are working on. It allows them to easily track changes, compare revisions, and collaborate with other team members effectively. The integration of version control within the IDE streamlines their workflow and ensures efficient project management.

Virtual Environments: Several reviewers highly value the convenience of Virtual Environments within PyCharm. By enabling them to create isolated environments for different projects, it eliminates conflicts between dependencies and makes it easier to manage package installations. Users can seamlessly switch between environments without leaving the IDE, thereby improving their efficiency and focus during development tasks.

Reviews

4 Reviews
Manufacturing

Pycharm review from Pharma.

Rating: 9 out of 10
Incentivized

Use Cases and Deployment Scope

We use PyCharm to code data workflows, generate Python applications, and write in Terraform the necessary infrastructure for the data platform we are building in GCP. It allows us to develop faster due to the ease of adding widgets and extensions, the GitLab collaboration, and the console inside the IDE. The development of Python, bash, debt, and Kubernetes tools are all made in PyCharm.

Pros

  • Console integration.
  • Git Integration.
  • Jupyter notebooks inside the IDE.
  • Multiple projects.

Cons

  • Connection to LLms to help us code.
  • Merge commits.
  • Google integration.

Likelihood to Recommend

PyCharm is well suited to developing and deploying Python applications in the cloud using Kubernetes or serverless pipelines. The integration with GitLab is great; merges and rebates are easily done and help the developer move quickly. The search engine that allows you to search inside your code is also great. It is less appropriate for other languages.
Vetted Review
PyCharm
10 years of experience

Extensive Python IDE

Rating: 9 out of 10
Incentivized

Use Cases and Deployment Scope

It is used by several departments in the organization to develop Web applications, and machine learning algorithms/pipelines. For the case of Web applications, it is used because it is a great IDE for web application with its built-in support for Django. And for the case of machine learning models/pipelines it is used because it conveniently allows to use SQL queries, so convenient that it recommends/fixes the query during the process of writing it.

Pros

  • Software development.
  • Debugging.
  • Code completion.
  • Git visualization.
  • Package management.
  • Python.

Cons

  • Its great and huge feature set comes at the cost of space, complexity and speed.

Likelihood to Recommend

PyCharm is great for software development in Python, whether it's a Web/Django application or a machine learning model development/deployment. It has many awesome extra features such as auto code completion, data type illustration, git visualization, package management (pip), visualization and version management of code history. It's highly flexible in customization, too. For example, once as I was using NumPy, it recommended me to allow the scientific mode so it is as if PyCharm actually understands your needs and makes great recommendations. It has nice shortcuts, for example, CTRL + Q explains the pointed function. It contains a lot of plugins and themes, integrated web framework Django, interactive console and virtual environment. It's also great for students since PyCharm provides 1 year of student license for them.
Vetted Review
PyCharm
2 years of experience

A powerful and good-looking IDE for Python

Rating: 8 out of 10
Incentivized

Use Cases and Deployment Scope

As a Data Science team in our company, we often need to perform different analyses using Python programming language. However, it is used not only in our department but also throughout the whole organization. It helps to address various business problems such as tasks related to Machine Learning and Artificial Intelligence as a whole, implementation of the backend part for internal applications, etc.

Pros

  • Single time analyses in terms of Data Science projects. PyCharm Professional provides users with a special Scientific View which allows gaining a better feeling of the application.
  • Debugging of applications is well-designed: it is simple to follow changes in variable values and to evaluate expressions.
  • Subjective: the application is quite stylish and pleasant to work with in comparison with its competitors.

Cons

  • Indexing and skeleton building has to be improved. It takes some time even with SSD inside the machine. If one has an HDD and also wishes to use a full-fledged Anaconda, then indexing will become a nightmare.

Likelihood to Recommend

If you have a powerful machine and want to perform a data analysis job in Python, then this piece of software is for you. However, if you are more of a fan of the script nature of Python, then this IDE is not suited for you, because PyCharm cannot run code by chunks of the single file.
Vetted Review
PyCharm
3 years of experience

Debugging your Python Made Easy

Rating: 9 out of 10
Incentivized

Use Cases and Deployment Scope

PyCharm is used alongside other JetBrains development software specifically for the development of Python-based unit tests and applications. For the most part, PyCharm is used as a stand-alone tool to write and execute these unit tests, but occasionally Visual Studio is also used for this purpose as well.

Pros

  • Excellent Debugging
  • Easy to use UI
  • Very easy to work on multiple files at once

Cons

  • Sometimes code will run when executed within the program, but not when run via shell
  • It takes a long time to close threads when testing code
  • Integrating tightly with Git

Likelihood to Recommend

If you are interested in learning Python, I would highly recommend downloading PyCharm. Coming from more of a systems admin background, I was a little hesitant to jump into coding, but needed more functionality than PowerShell could afford. Using PyCharm to get oriented with Python wound up being the right call for me, and I would not hesitate to recommend it to someone with a similar use case.