PyCharm

This update includes fixes related to port retrieval during debugging with the Docker Compose interpreter - PY-91091. For more details, refer to our release notes.

The highlights of this release include: Productivity-enhancing features

• Develop Python extension modules directly with the Rust plugin.
• Configure external tools faster with the redesigned settings UI for tools running via uvx.
• Standardize your debugging workflow with debugpy enabled by default.
• See inline version hints and quick documentation for your dependencies at a glance.
• Resolve Git conflicts more easily with a streamlined resolution flow.
• Drag and drop files and images straight into terminal sessions.
• Track interactive Docker Compose container statuses right in the editor. Support for new technologies
• Get faster diagnostics through the Pyrefly type engine integration.
• Navigate notebooks with the dedicated Jupyter Notebook minimap layout.
• Work with multi-project setups and uv workspaces by default.
• Speed up workflows on large codebases with TypeScript 7 support.
• Validate infrastructure with the Terraform testing framework integration. AI upgrades
• Generate entire projects from natural language prompts with AI.
• Retain cross-session domain knowledge using the agent skills manager. Visit our What's New page to learn about these and other improvements. Full release notes.

Code insight and type checking

• Evaluate fields marked with @property inside generic objects accurately, as an issue causing the type inference engine to incorrectly expect a raw property type has been resolved - PY-76219. Refactoring tools
• Rename Python modules via the Shift+F6 refactoring action and expect all corresponding project references and imports to update properly across your workspace directories - PY-53274. Full release notes.

Code insight and type checking

• Docstring rendering: Fixed a bug where reStructuredText Python code blocks inside docstrings failed to render - PY-37743.
• Variance inference rules: Fixed a bug where the type checker failed to account for Concatenate expressions during type variance inference - PY-88970.
• Generic type unification: Resolved a type checker regression where an empty list literal incorrectly collapsed generic type unification to Any - PY-89047. Jupyter notebooks
• Staging area comparisons: Fixed an issue where comparing notebook modifications in the version control staging area displayed raw notebook JSON content instead of the formatted file view - PY-78246.
• Markdown table alignment: Fixed a layout bug where columns within Markdown cell tables failed to align properly inside Jupyter Notebooks - PY-85344. LSP and external tools
• LSP diagnostics regression: Resolved a critical regression with the Python plugin in JetBrains IDEs where Pyright and Ruff diagnostics stopped working entirely after a recent update - PY-89795.
• Ruff rule documentation: Added an inline documentation link on hover for diagnostic rules reported by the Ruff plugin - PY-89557.
• Property signature validation: Fixed a false-positive Getter signature should be (self) warning triggered during code analysis - PY-87508. Full release notes.

Update bundled JetBrains Runtime (JBR) featuring Critical Patch Update 21.0.11 from Oracle.

This update focuses on stabilizing the debugpy engine, refining the Jupyter Notebook experience, and improving accuracy for Python type checking and code insight. Code Insight and Editing

• Type checking refinements: Improved accuracy by resolving a false negative when using None as a default value for non-optional parameters (PY-88610) and addressing false positives for UUID types (PY-89479).
• Decorator support: Enhanced parameter inference for functions wrapped in decorators (PY-79204) and ensured class decorated functions resolve to the instance of the class (PY-51321).
• F-string selection: Select an entire string by double-clicking the f-string quote character (PY-88398).
• Enhanced syntax highlighting: Added specialized syntax highlighting designed for f-string format specifiers (PY-88215).
• Advanced type system precision: Added comprehensive type checker support for managing bounds and variance inside type variable tuples and parameter specifications (PY-88277).
• Smarter inlay hints: Read and evaluate numerical structures smoothly with a newly added inlay hint for automatic number promotions (PY-88319). Jupyter and Data Science
• Output customization: Change the color of error messages in Jupyter output to better suit your theme (PY-73455).
• Remote development stability: Resolved issues where ipywidgets and interactive matplotlib plots were not rendered correctly during remote sessions (PY-87083, PY-78563).
• Graph rendering: Fixed a regression that prevented Bokeh-generated graphs from displaying within notebooks (PY-87867).
• Table accuracy: Corrected the missing values count in the Pandas DataFrame preview (PY-78601). Debugger
• Dataframe visualization: Restored the View as DataFrame option for evaluated dataframes when using the debugpy engine (PY-88817).
• Variable inspection: Fixed a major issue where Python type renderers were not functioning in the Variables view (PY-75762).
• Network reliability: Resolved connection failures for custom CA signed TLS certificates when using the debugger (PY-89519). Environment and Frameworks
• Remote execution: Fixed issues where uv run failed to work for remote targets (PY-89538).
• Legacy support: Resolved an ImportError related to machinery affecting behave support in Python 2.7 (PY-89460).
• Project management: Automatically exclude venv folders from indexing to improve performance (PY-71286).
• Plugin integration: Fixed a BootstrapMethodError in the Databricks plugin that occurred after the 2026.1 update (PY-89029). Full release notes.

For more details, refer to our release notes.

SSI support in the built-in web server has been disabled. For more details, refer to our release notes.

PyCharm 2026.1.1 focuses on improving the developer experience within large-scale workspaces, providing more granular control over environments and a more stable debugging workflow. Advanced workspace and environment management

• Per-folder environment control: You can now activate specific Python interpreters or virtual environments on a per-file or per-folder basis, allowing for more flexible configurations in complex projects - PY-66254.
• Flexible project structures: PyCharm now supports Poetry-based environments even when the pyproject.toml file is not in the root directory, facilitating better support for nested monorepos - PY-57652.
• Zero-config SDK setup: When opening new projects, compatible environments are detected and configured as the project SDK automatically, or the IDE will suggest creating a new uv environment if none is found - PY-82581. Debugger and engine reliability
• debugpy stability: Several critical regressions in the debugpy engine have been resolved, including issues where environment variables from .env files were not injected (PY-88628) and process crashes during code updates (PY-88880).
• Path mapping: The debugger now supports multiple path mappings, ensuring that your local and remote file structures stay synchronized during a session - PY-88840.
• Full IDE sessions from explorer: When opening files directly from your system file explorer, PyCharm now launches a fully functional IDE session instead of the limited LightEdit mode - PY-84031. Refined code insight
• Type checking refinements: Multiple false positives have been addressed, such as incorrect unhashable type warnings for sets (PY-87206) and errors regarding Path definitions (PY-89082).
• Tool stability: A fix has been implemented for a regression that prevented users from editing or creating new run configurations and Python tools - PY-88807. Full release notes.

PyCharm 2026.1 rethinks how you build, debug, and scale Python projects. Key updates:

• debugpy engine option: Fast and stable debugging with DAP and native PEP 669 support.
• Remote uv support: Synchronize environments and packages via SSH, in WSL, or inside Docker.
• ACP Registry: One-click installation for agents from Cursor, Claude Agent, and many others.
• Free web tools: Essential JavaScript, TypeScript, and CSS tools for all users. Productivity and Data Science:
• Project-free Jupyter notebooks: Open .ipynb files directly from your file explorer without creating a project.
• Google Colab: Power your Jupyter notebooks in PyCharm with professional IDE features designed for larger projects and longer development sessions.
• Dev Containers: Open projects natively from containers using a high-performance agent-based architecture.
• Django 6 and Celery: Full support for template partials and a new dedicated Celery Run configuration. Discover all updates on our What's New page.

PyCharm 2025.3.4 focuses on critical stability for legacy projects, interface clarity for Jupyter workflows, and reliability in update settings. Core Stability and IDE Reliability

• Project Indexing: PyCharm now handles project indexing reliably even for older Python versions like 2.7, ensuring a stable experience without recursion-related crashes - PY-87549.
• Update Preferences: Users can now correctly manage their update settings as the "Show Early Releases" option properly respects user choices in the interpreter settings - PY-86346. Jupyter and Interface Refinements
• Toolbar Visibility: The Jupyter Editor Toolbar now displays correctly without blending into the Main Toolbar, ensuring buttons and icons are distinct and easy to use - PY-87430.
• Notebook Editing: Drag-and-drop operations within Jupyter notebooks now render correctly, preventing cells from appearing duplicated at the bottom of the file - PY-86709. Full release notes.

This update focuses on strengthening environment synchronization, resolving critical Jupyter regressions, and improving integration with command-line tools. Environment & Sync Fixes

• SDK refresh: Resolved a critical regression where the Python SDK located in a module/.venv would fail to refresh automatically - PY-87104.
• uv: Fixed an issue where pyproject.toml would not reflect the current environment state after adding packages via the command line using uv - PY-86163.
• Tool recognition: Tool installations are now correctly recognized on the settings page even when added directly from the command line - PY-85780.
• Poetry: Fixed a bug that made it impossible to create a Poetry interpreter using a lower version of Python - PY-87199. Jupyter & Data Science
• Variables: Fixed an issue where environment variables were not available in Jupyter notebooks when running via the IDE Management Server - PY-86474.
• Workflow stability: Resolved a bug preventing the drag-and-drop of CSV files directly into a Jupyter notebook - PY-86694.
• Data viewer: Fixed a bug in PyDataViewer.apply where Numpy was incorrectly reported as unavailable - PY-87345. Code Insight
• LSP integration: Resolved an issue where the IDE failed to show usages when the ty tool was enabled - PY-86340.
• UI: Removed an unnecessary trailing space from function return type inlay hints - PY-84939. Full release notes.

In this version, we've introduced several bug fixes. For more details, refer to our release notes.

Release highlights:

• Google Colab support for running Jupyter notebooks - PY-66172
• Added support for running PEP 723 scripts in uv environments - PY-79638
• Core Stability: Fixes for if TYPE_CHECKING logic and Pydantic type recognition (including AwareDatetime) - PY-50642 and PY-77435
• Regressions resolved: Restored Jupyter notebook source root availability, Git hook virtualenv usage, and Pytest compatibility with Python 2.7 - PY-85114, PY-86181 and PY-86545 For more details, refer to our release notes.

This update includes fixes related to project settings behavior when working with WSL. For more details, refer to our release notes.

In this version, we've introduced several minor updates and bug fixes. For more details, refer to our release notes.