The reason why pycharm runs very slowly
Causes that cause PyCharm to run slowly include: Hardware limitations: low CPU performance, insufficient memory, and insufficient storage space. Software related issues: Too many plugins, indexing issues, and large project sizes. Project configuration: Improper Python interpreter configuration, excessive file monitoring, and code analysis features consuming too many resources.

The reason why PyCharm runs slowly
PyCharm is a powerful Python IDE, but it occasionally runs Slowness problem. The reasons for this may vary.
Hardware Limitations
- #Low CPU performance: PyCharm is a resource-intensive application that requires a powerful CPU to run smoothly . If your CPU is slow or under heavy load, it may cause PyCharm to run slowly.
- Out of memory: PyCharm requires a large amount of memory to run. If your computer is low on memory, this will cause insufficient virtual memory and slow down PyCharm.
- Insufficient storage space: PyCharm caches project data and index files, which may take up a lot of disk space. If you are low on storage space, this may cause file operations to slow down, affecting PyCharm performance.
Software related issues
- Too many plug-ins: PyCharm plug-ins can enhance its functionality, but too many plug-ins are installed May affect performance. Disabling or uninstalling unnecessary plugins can free up resources and increase speed.
- Indexing issue: PyCharm will index project files to facilitate code search and editing. If the indexing process encounters problems or is out of date, it can cause PyCharm to run slowly.
- Project size: Large projects contain a large number of files and code, which can put a strain on PyCharm's processor. Breaking large projects into smaller modules can improve performance.
Project configuration
- Python interpreter configuration: Choosing the right Python interpreter and optimizing its settings can improve PyCharm performance. Make sure you are using the correct virtual environment or conda environment.
- File monitoring: PyCharm monitors file changes to automatically refresh the project. Disabling unnecessary monitors frees up resources and increases speed.
- Code Analysis: PyCharm provides advanced code analysis functions, but these functions consume resources. If your project does not require these features, you can disable them to improve performance.
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