PyCharm Reviews & Product Details

Almost every feature and the overall experience are awesome. I’d especially like to highlight the IDE interface: it has some of the best themes and icon sets, and the plugin set that comes with the IDE is great too, including tools for big data, Docker, and Kafka.

The IDE can handle a lot of processes running at the same time. The pricing tiers are also great; they offer free trials as well as student discounts, so students can afford it.

My first experience using it has been very positive. It’s simple yet direct, and there are plenty of FAQs available to help whenever I get stuck.

The AI integrations from different providers are a nice addition, and the AI-powered code auto-suggestions are more than good enough. Review collected by and hosted on G2.com.

One thing I often dislike is that it can crash during a memory overflow when a process exceeds the available system memory. This should be fixable, and processes should be limited so that, at the very least, the IDE doesn’t get killed. Review collected by and hosted on G2.com.

What I love the most is the debugger. When running applications inside Docker, outside Docker, remotely, locally, and any other combination possible, there is a way to configure the debugger easily, allowing you to find bugs in the code or simply evaluate how your code is doing. The way to manage breakpoints, the variables evaluator, and even run little scripts in the middle of the execution is simply amazing. The way to integrate with Docker and external resources for debugging is great. Is good to have the plugins for different AI's like Claude and Gemini, that's the new way to build software, so is a must have and PyCharm has it. Even though with all the plugins and connections in place, the software is super fast, the only way that my computer crash, is if I deal with tons of data, that's an easy way to demostrate that is a lightweight software that does not harm you computer performance, it simply does the job with great results Review collected by and hosted on G2.com.

Maybe this is a little bit contradictory to what I like, but I would like to have a better integration with AI harnesses. The classic integration with CLI is the basic setup, but to have a better experience when you use the chat, manage multiple sessions and agents, it could be better; other solutions like VS Code do a better job in this area Review collected by and hosted on G2.com.

I love that all that I need is in one place. Even without AI subscription I can have AI suggestion for autocomplete and it's just so easier to do some repetitive job. Working with DB? You can execute SQL snippet inside your code. Working with pandas? You can open dataframe as table. Working with Django/FastAPI/Flask? Here are endpoints connection. Working in team, but your project is non-standard? Here are shared templates that you can define yourself. And PyCharm is becoming better each year. They implements support for current stack (like using conda/uv/uvloop/etc). I'm using PyCharm Pro for 8+ years and I totally recommend it for all Python projects Review collected by and hosted on G2.com.

There were a lot of crashes years ago. There are still some issues, but it's not critical. For example, after updating PyCharm to latest stable version, some plugins (including plugins by JetBrains) are not supported and there is no backward compatibility, so you have to just turn off them. It's a little annoying Review collected by and hosted on G2.com.

PyCharm has been my go-to IDE for all my Python backend development. I really like the debugging features, especially being able to set breakpoints and step through the code to figure out what's going wrong. The code suggestions, auto-completion and easy navigation between files are also quite handy. I also like how it handles virtual environments and dependencies. Overall, it's easy to work with and has pretty much everything I need for my day-to-day development. Review collected by and hosted on G2.com.

PyCharm can be a bit heavy sometimes, especially when working on larger projects. It takes a while to load and index files, which can be annoying. Also, setting up Python interpreters and virtual environments isn't always straightforward, particularly when switching between projects. Some settings are also quite difficult to find, and I end up spending more time than I'd like figuring out where things are. Review collected by and hosted on G2.com.

The deep, intelligent code completion, refactoring tools, and built-in visual debugger make writing Python effortless and fast. Out-of-the-box support for virtual environments, Docker, and remote development eliminates endless configuration headaches. The unified Git integration and database tooling turn it into a complete, standalone development environment. Review collected by and hosted on G2.com.

It is notoriously resource-heavy, consuming significant RAM and causing noticeable battery drain on laptops. Initial startup, background indexing, and project loading can be frustratingly slow, especially on larger codebases. Additionally, the full professional feature set is locked behind a paid subscription, which is steep for independent developers. Review collected by and hosted on G2.com.

I am working as a software engineer (backend) for a medium sized tech company. For our primary Django backend, API endpoints, and data processing scripts, we rely on PyCharm Professional as our go-to tool for development and maintenance.PyCharm Professional is our daily companion for developing and maintaining our main Django backend, creating API endpoints, and running data processing scripts. I use it to write code, to manage local database connections and for Git merge management, all in one window. I like PyCharm because everything that I need is there right out of the box; I don't have to spend hours looking for it, or figuring out how to configure it, just to run a simple script. The visual debugger is without doubt the best in the business. The ability to set breakpoints, evaluate expressions instantly and have access to a dictionary with complex structures to look at without having to print out all the data is amazing. Its project-wide refactoring tools are also very useful. If a core function or a database model needs to be renamed, PyCharm will do so safely, updating the model and function throughout the repository but not randomly breaking my imports. Review collected by and hosted on G2.com.

The most significant negative is that the software is very heavy and consumes a lot of resources. Opening a medium to large sized repository involves it re-indexing all the files and virtual environments, which is 100% taxing my CPU and causes the editor to lag for a couple minutes. You are going to have a really hard time running this along with Docker and a browser if your work laptop does not have at least 16GB of RAM. It is very slow to boot up, so when I only need to open a single python file to edit a small typo, it feels like I'm using a washing machine that is too oversized. Typically would use a lighter text editor if I wanted to make quick edits. Review collected by and hosted on G2.com.

I learned coding using this IDE only, it gives multiple options to do multiple tasks. The most prominent feature is intelligent code assistance. The autocomplete understands my project’s structure, catches errors as I type, and suggests fixes before I even run the code, which saves a lot of debugging time. The built-in debugger is another big upside. Review collected by and hosted on G2.com.

It is slow compared to other IDE's available in the market. It is resource heavy, uses lot of memory and can feel slow to start up, especially large projects Review collected by and hosted on G2.com.

PyCharm Professional provides the most comprehensive environment for machine learning workflows. The built-in Scientific mode acts as a specialized view that includes a variables panel, a plots gallery, and an interactive console, making data exploration highly efficient. The native Jupyter Notebook integration allows for opening, creating, and running .ipynb files directly within the IDE without switching contexts. For training large models, the ability to connect to remote interpreters on SSH servers or Docker containers is invaluable. This architecture enables writing and debugging code locally while executing heavy training jobs on remote GPU instances. Furthermore, the robust code intelligence, advanced debugger, and built-in database tools are fully configured out of the box, ensuring that complex machine learning repositories remain well-structured and maintainable. Review collected by and hosted on G2.com.

The IDE is incredibly memory-intensive and heavy on system resources, particularly when indexing massive machine learning repositories or parsing large datasets. Because the core data science capabilities—like Jupyter integration, the DataFrame viewer, and remote interpreters—are locked behind the Professional Edition, the subscription price can be steep for individual practitioners. Additionally, the sheer volume of integrated tools and deep configuration menus presents a significant learning curve compared to lighter text editors. Review collected by and hosted on G2.com.

What I like most about PyCharm is its intelligent code completion and strong debugging tools. The IDE catches errors as I write and offers helpful suggestions that speed up development. Its interface is clean and well organized, which makes it easier to manage larger projects without feeling overwhelmed. I also appreciate the convenient integration with Git and virtual environments, since it lets me manage version control and project dependencies in one place. Overall, PyCharm boosts my productivity by cutting down on repetitive tasks and making code navigation much smoother. Review collected by and hosted on G2.com.

One drawback of PyCharm is that it can be resource-intensive, especially when working on larger projects or on systems with limited memory. Startup time can sometimes feel slower compared to lighter code editors. There is also a learning curve for new users because of the large number of features and configuration options available. While the Community Edition is useful, some advanced features are only available in the paid version, which may not be ideal for individual developers or students. Review collected by and hosted on G2.com.

PyCharm makes Python development effortlessly efficient, its intelligent auto completion, powerful refactoring tools, and top-tier debugging capabilities are absolute lifesavers. Having Git integration, virtual env management, and terminal tool built directly into one clean workspace saves so much time. Review collected by and hosted on G2.com.

It's resource heavy, leading to high RAM and CPU usage that slows down older machines. Initial setup and project indexing takes time. Review collected by and hosted on G2.com.