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PyCharm

PyCharm is an (IDE) specifically designed for programming, developed by , a software company headquartered in , . First released on October 13, 2010, as version 1.0 with initial support for development, it has evolved into a comprehensive tool for professional developers, offering intelligent , on-the-fly error checking, quick-fixes, and an integrated . Built on JetBrains' IntelliJ platform, PyCharm provides a consistent cross-platform experience on Windows, macOS, and Linux, including features like version control integration with Git, database tools, and support for scientific computing libraries such as NumPy, SciPy, and Matplotlib. It also excels in web development with built-in support for frameworks including Django, Flask, and FastAPI, as well as data science tools like Jupyter notebooks, Conda environments, PyTorch, TensorFlow, and Hugging Face models. Historically offered in two editions—a free, open-source Community Edition under the 2.0 for pure development, and a paid Professional Edition with advanced capabilities like support and database integration—PyCharm underwent a significant change in April 2025 with the release of version 2025.1. This update unified the editions into a single product, where all users start with a free one-month trial of features; afterward, core functionality remains free, while advanced tools require a subscription starting at $109 annually for the first year for individual developers. The unification aims to simplify access while maintaining , with the final standalone Community Edition released as version 2025.2 in August 2025.

Overview

Purpose and capabilities

PyCharm is a cross-platform (IDE) designed specifically for professional development, offering a consistent experience across Windows, macOS, and operating systems. It serves as a comprehensive toolset for programmers, supporting diverse use cases such as scripting, with frameworks like and Flask, workflows, and scientific computing applications. This focus on Python-centric development enables developers to handle complex projects efficiently, from initial code authoring to advanced analysis and modeling tasks. At its core, PyCharm provides key capabilities that enhance productivity in Python-based projects, including intelligent that suggests context-aware code snippets, automated refactoring tools for safe code restructuring, seamless integration with systems like , and robust features for organizing dependencies and environments. These elements streamline the software development lifecycle by facilitating code writing, review, collaboration, and maintenance within a unified interface, reducing the need for multiple disparate tools. Additionally, PyCharm extends its utility to mixed-language projects by offering built-in support for related technologies such as , , and CSS, particularly in contexts where Python backends integrate with frontend code. As of 2025, PyCharm is a unified product that provides core functionality for free and advanced features via subscription, catering to a range of user needs while maintaining ' emphasis on high-quality tooling.

Development and ownership

PyCharm is owned and developed by , a software company founded in 2000 in , , by developers Sergey Dmitriev, , and Eugene Belyaev. Originally started as IntelliJ Software by three Russian developers, has grown into a leading provider of integrated development environments (IDEs), with flagship products including , on which many of its tools are based. The company maintains headquarters in and operates offices worldwide, emphasizing high-quality developer tools without significant shifts in ownership structure. Development of PyCharm began in 2009 as a specialized IDE for Python, drawing inspiration from the modular architecture of IntelliJ IDEA to address the need for robust Python tooling. The first official release, PyCharm 1.0, arrived on October 13, 2010, marking JetBrains' entry into Python-specific development environments and focusing initially on Django support alongside general Python productivity features. This initiative was led by developer Dmitry Jemerov, motivated by the growing popularity of Python and the limitations of existing editors at the time. JetBrains has committed to cross-platform compatibility for PyCharm, ensuring seamless operation on Windows, macOS, and distributions since its inception. The IDE's core is built using , leveraging the (JVM) for its runtime environment, which enables this portability while benefiting from Java's stability and ecosystem. As of 2025, PyCharm's ownership remains stable under , with no major acquisitions or mergers impacting its development or direction.

Editions

Community Edition

The PyCharm Community Edition was the free and open-source variant of the PyCharm (), released in September 2013 under the Apache 2.0 license to promote accessibility for development. Developed by , it provided essential tools for writing and managing code without requiring a subscription or payment, making it suitable for non-commercial use and contributing to its adoption in diverse programming contexts. The standalone version was discontinued after 2025.2, released in August 2025, with source code remaining available for building. As of PyCharm 2025.1 in April 2025, the editions were unified into a single product where the core functionality equivalent to the former Community Edition remains free. This edition included core functionalities focused on fundamental development, such as an intelligent code editor with , , and on-the-fly error analysis to enhance productivity during editing. It supported seamless integration with interpreters, including virtual environments via virtualenv, along with built-in tools for running tests and debugging locally. Additionally, version control integration was provided for systems like , Subversion (SVN), , and , enabling efficient collaboration and code management directly within the . Designed primarily for individual developers, students, educators, hobbyists, and open-source contributors, the Community Edition targeted and those engaged in scripting, , or educational , offering a robust into professional-grade tooling without advanced framework-specific features available in the Professional Edition. Users download the unified PyCharm from the official website or through the JetBrains Toolbox App, which includes the free core features and simplifies , updates, and across platforms like Windows, macOS, and , with no subscription needed for ongoing access to these features.

Professional Edition

The Professional Edition refers to the feature-rich, subscription-based access within the unified PyCharm , with the current model introduced in version 2025.1. This edition builds on the free core features, such as essential code editing, local debugging, testing frameworks, and Jupyter Notebook support, to deliver comprehensive capabilities for demanding development environments. Key additional capabilities in the Professional Edition include scientific mode, which enhances Jupyter notebooks with interactive data visualization, variable explorers, and inline plotting for streamlined workflows. Remote development via SSH enables seamless coding, running, and on distant servers, virtual machines, or cloud environments, supporting distributed teams and resource-intensive computations. Designed for professional teams, data scientists, and web developers tackling large-scale applications, the Professional Edition emphasizes scalability and productivity in enterprise settings. It provides in-depth support for SQL through bundled database tools for querying, navigation, and refactoring across systems like and . handling is deepened with integrated frontend development features, including bundled plugins for framework support and code intelligence akin to WebStorm.

Core Features

Code editing and intelligence

PyCharm's code editing capabilities are centered around intelligent assistance that leverages static analysis to enhance developer productivity. The provides context-aware , which suggests keywords, classes, methods, and variables based on the current scope and code context, activated via shortcuts like Ctrl+Space. This feature is particularly robust for , incorporating static analysis to infer types and provide accurate suggestions, including support for type hints as defined in PEP 484, which allows annotations for function parameters, return types, and variables using the typing module. By analyzing type comments and annotations, PyCharm offers completions that respect Python's dynamic nature while promoting type safety, such as suggesting methods specific to hinted types like lists or dictionaries. Refactoring tools in PyCharm enable safe and efficient restructuring without altering functionality, crucial for maintaining large codebases. The rename refactoring allows developers to update variable, , or names across the entire , automatically adjusting all references to ensure consistency. Extract refactoring identifies a and transforms it into a reusable , improving by reducing duplication and enhancing . Safe delete verifies that a element is unused before removal, preventing unintended breaks, and all refactorings include a preview dialog to review changes before application. Navigation aids streamline movement through code, especially in complex projects. The go-to-definition feature, invoked by Ctrl+click or Ctrl+B, jumps directly to the declaration of symbols like functions or classes, facilitating quick understanding of code dependencies. Find usages searches the project for all references to a selected element, displaying results in a navigable tool window to reveal how code is employed across files. For handling large files, collapses expandable regions such as functions, classes, or custom blocks, allowing developers to focus on high-level structure while expanding sections as needed for detailed editing. Error detection is powered by on-the-fly code inspections that perform static analysis to identify issues like unused imports, undefined variables, or potential type mismatches, highlighting them directly in the editor. These inspections draw from Python-specific rules to catch common pitfalls early, with severity levels configurable for warnings or errors. Quick-fixes, accessible via Alt+Enter, offer one-click resolutions, such as automatically removing unused imports or adding missing type hints, integrating seamlessly with the IDE's to resolve problems without disrupting workflow.

Debugging and testing tools

PyCharm provides a robust built-in that facilitates interactive runtime analysis of , allowing developers to identify and resolve issues efficiently. The supports both 2.7 and 3.8 through 3.14, enabling seamless debugging across these versions without changes. Key features include setting breakpoints to pause execution at specific lines, inspecting values in through the tool , and evaluating expressions in the integrated console for on-the-fly testing. This process involves attaching the to a run , stepping through line-by-line or over calls, and examining call stacks to trace program flow. For testing, PyCharm integrates natively with popular Python unit testing frameworks such as , , and , streamlining the creation, execution, and management of test suites. Developers can run tests directly from the editor or via dedicated configurations, with results displayed in the Test Runner tool window for easy navigation and failure analysis. Coverage analysis is supported through on-the-fly line coverage measurement, generating reports that highlight executed (green) and unexecuted (red) code lines in the editor, along with percentage summaries in the Coverage tool window. These reports can be merged across multiple runs to track cumulative coverage, helping ensure comprehensive test validation with minimal runtime overhead. Remote debugging extends PyCharm's capabilities to distributed environments, such as SSH-connected or applications running on remote hosts. By configuring a remote interpreter or debug , users can attach the to processes on external machines, inspecting variables and stepping through code as if executing locally. This is particularly useful for , where breakpoints can be set in server-side code and debugged over SSH without disrupting production-like setups. Performance tools in PyCharm enable detailed analysis of CPU and usage to optimize efficiency. The integrated profiler, leveraging libraries like cProfile, yappi, or vmprof, attaches to run configurations to collect runtime data, presenting it through visualizations such as flame graphs for call hierarchies, call trees for method interactions, and statistics tables for metrics like time spent per function. highlights allocation patterns and potential leaks via snapshots, while CPU visualizations identify bottlenecks, allowing developers to refine based on empirical runtime behavior.

Advanced Features

Framework and database support

PyCharm (with Pro subscription for advanced framework support) provides comprehensive built-in support for popular web frameworks, enabling developers to streamline setup and execution. For , the offers dedicated templates that automatically configure the , including settings for models, views, and URLs, along with specialized run configurations for managing development servers and administrative interfaces. Similarly, Flask integration includes a dedicated type, support for the built-in Flask , and (CLI) tools for tasks like running applications and handling blueprints. support, introduced for 3.6 and later, facilitates development with features such as automatic generation of run configurations, for route definitions, and integration with dependency injection systems. These capabilities extend to frontend-backend workflows, allowing seamless handling of , , and related technologies alongside frameworks. The IDE's database tools, available with a Pro subscription, offer robust management features for relational databases, including schema navigation, query execution, and dialect-specific support. Users can connect to databases via JDBC drivers, with PyCharm providing visual schema introspection, SQL code completion, and execution plans for optimizing queries. MySQL integration supports schema browsing, data editing, and dialect-aware SQL formatting, enabling direct query testing within the IDE's console. For , PyCharm allows file-based connections for lightweight databases, with tools for viewing tables, running ad-hoc queries, and exporting data, making it suitable for embedded or prototyping scenarios. Overall, these tools support over 40 SQL and databases, emphasizing intuitive data exploration and integration with code. PyCharm enhances scientific through native with key libraries, focusing on data manipulation and . The Data View tool window displays arrays and DataFrames in a tabular format, supporting sorting, filtering, and inline editing for interactive analysis. For , allows inline plotting within the Scientific Mode, with automatic figure rendering and support for customizing plots directly in the editor. These features, combined with Jupyter notebook support, facilitate workflows in and by providing code insights and execution environments tailored to numerical . Support for template languages in PyCharm includes and for Jinja2 and , aiding template-driven development in web projects. Jinja2 templates receive full language injection, enabling context-aware completion for variables, filters, and macros within or standalone files. templates benefit from similar highlighting and assistance, with support for directives, inheritance, and Python embedding, though legacy aspects may require configuration in older projects. This integration ensures templates integrate smoothly with framework-specific views, such as those in or Flask.

Integration with external tools

PyCharm extends its functionality through the JetBrains Plugin Marketplace, which provides an extensive collection of extensions to customize the development environment. These include themes for visual personalization, linters such as and SonarLint for code quality checks, and AI-powered tools like the AI Assistant, introduced in the 2023.2 release to offer in-IDE code generation, explanations, and chat-based assistance. Recent updates in PyCharm 2025.2 include the AI Toolkit and AI Agents Debugger for enhanced AI development workflows. The IDE features robust version control system integration, supporting , , and directly within the interface. Users can perform commits, pushes, and pulls via the VCS Operations Popup, while the tool window enables visual comparisons, branch creation, merging, and history tracking for efficient repository management. For deployment, PyCharm supports containerization and orchestration tools like and through built-in run configurations and plugins, allowing developers to build, run, and debug containerized applications locally or remotely. Integration with cloud platforms includes the AWS Toolkit for managing EC2 instances, S3 buckets, and functions, as well as Google Cloud Code for deploying to Google Engine (GKE) and Cloud Run. PyCharm maintains compatibility with other JetBrains IDEs, such as and WebStorm, by sharing the IntelliJ platform architecture, which facilitates seamless project import and export across tools. Settings synchronization via a Account or the Toolbox App ensures consistent configurations, keymaps, and plugins when switching between IDEs for polyglot development.

History

Early development and initial releases

PyCharm was announced by on January 29, 2010, as a dedicated (IDE) for and web developers, particularly those working with , entering a public preview phase with version 1.0 planned for mid-2010. The development aimed to bring the advanced productivity tools from JetBrains' established IDEs, such as for , to the Python ecosystem, where existing editors often lacked comprehensive code intelligence and refactoring capabilities comparable to those in mature language tools. This initiative addressed key gaps by providing Python-specific features like on-the-fly code analysis, error highlighting, and automated refactoring built on the IntelliJ platform. The first stable release, PyCharm 1.0, arrived on October 13, 2010, after a beta in and a release candidate in September, introducing core support including a smart code editor, integrated debugger, and integration. This version marked PyCharm's entry as a complete toolset for , , and development, emphasizing reliability and ease of use for professional workflows. Early development relied heavily on JetBrains' Early Access Program (EAP), which began with previews for version 1.1 in November 2010 and continued for subsequent iterations, allowing users to test builds and provide feedback to refine functionality. Community input through EAP and forums drove iterative enhancements, culminating in PyCharm 2.0's release on December 13, 2011, which incorporated user-reported issues and expanded support for technologies like , Jinja2, and while improving overall code inspection and debugging tools. These feedback loops ensured that early versions evolved to better meet diverse development needs, including performance optimizations in indexing and navigation reported by early adopters.

Major updates and recent versions

In 2013, JetBrains introduced the Community Edition of PyCharm with version 3.0, providing a free and open-source alternative to the existing Professional Edition, which retained advanced features for enterprise use. This split allowed broader accessibility for individual developers and educators while maintaining premium capabilities in the paid version. PyCharm's updates have consistently responded to evolutions in the ecosystem, such as the of async/await syntax via PEP 492 in Python 3.5. Support for this feature was integrated in PyCharm 5.0, released in 2015, enabling better handling of asynchronous programming patterns through improved code inspection and completion. In PyCharm 2016.1, further enhancements included full compatibility with Python 3.5's type hinting and inspection tools, alongside improvements to the debugger and integration, reflecting the growing emphasis on modern Python standards. By the late , PyCharm adopted an annual major release cycle using the 20XX.Y numbering format, facilitating predictable updates and rollouts. For instance, 2020.1 introduced enhanced remote interpreter configurations, laying groundwork for more robust remote workflows. This trend continued with a focus on and ; PyCharm 2023.1 added native support for remote Jupyter notebooks, allowing seamless connection to external servers for interactive computing and . Recent versions have emphasized AI integration and performance optimizations aligned with Python's advancements. PyCharm 2023.3 began supporting Python 3.12 features, including improved f-string parsing and error messages, with subsequent releases like 2024.3 enhancing -assisted code generation through the JetBrains AI Assistant for tasks such as docstring creation and context-aware completions. As of November 2025, the latest major release is PyCharm 2025.2 (August 2025), which introduces the AI Toolkit for AI engineering workflows and provides Jupyter notebook enhancements, marking the final binary support for the standalone Community Edition. The unification of the Community and Professional editions into a single product began with version 2025.1 in April 2025. These updates underscore PyCharm's shift toward -driven productivity and comprehensive support for data-intensive and collaborative development environments.

Licensing and Distribution

Licensing models

Following the unification of PyCharm editions in April 2025 with version 2025.1, the is now distributed as a single product under the JetBrains User Agreement (EULA, version 2.0, effective April 16, 2025). This agreement grants users a non-exclusive, non-transferable license for the software, with retaining all intellectual property rights. Core functionality remains free indefinitely, incorporating open-source components distributed under the Apache License 2.0, which permits free use, modification, and redistribution while requiring retention of notices. Advanced Professional features, such as enhanced framework support and database tools, require an active subscription. The open-source codebase for the core features is maintained in a public repository, allowing community contributions under 2.0 terms. Contributors grant a perpetual, to integrate submissions, supporting ongoing development without obligating acceptance of all changes. Both free and subscribed usage incorporate third-party libraries and components, such as and runtime elements, subject to their respective . Users must provide appropriate attribution, including notices and statements, as detailed in product and third-party notices. Compliance with controls and regulations is required for all distributed components. In the unified PyCharm, a one-month trial of features is available with each major release (three times per year), granting full access during the period and managed through the Account system. The final standalone Edition, version 2025.2, was released in August 2025.

Pricing and

PyCharm is distributed in a unified edition that includes core features available for indefinitely, along with advanced features accessible via subscription after an initial one-month trial. The version can be downloaded directly from the official website without any account requirement. The Professional subscription for individuals is priced at $199 per year as of 2025, providing access to all features including AI tools and framework support. Team licenses for organizations are available at $499 per user per year, with options for volume discounts. Discounts of up to 50% are offered for students, educators, startups, and non-profit organizations upon verification. Subscriptions can be purchased and managed through a JetBrains account on the official website, the JetBrains Toolbox App for easy installation and updates, or bundled all-in-one packs that include PyCharm alongside other JetBrains IDEs starting from $289 per year for individuals. Active subscriptions include free access to all minor updates and bug fixes released within the subscription period, major version upgrades, and a perpetual fallback license for the subscribed version. Pricing is adjusted for regional variations, displayed and billed in local currencies where available, with applicable or sales taxes included in the listed amounts for supported countries.

Limitations and Criticisms

Performance and resource demands

PyCharm's system requirements specify a minimum of 2 of free , any modern CPU, and 3.5 of available disk (SSD recommended), while recommended specifications include 8 of total system , a multi-core CPU such as an i5 or equivalent, and an SSD with at least 5 of free to ensure smooth operation, particularly when using advanced features. These guidelines apply across supported operating systems, including 64-bit versions of or later, macOS 12 or later, and the two latest stable LTS versions of . Despite these baseline needs, PyCharm often demands significant resources in practice, especially when handling large codebases where indexing processes can consume substantial —sometimes exceeding several gigabytes—and cause temporary slowdowns or unresponsiveness. The addition of multiple plugins exacerbates this, as each can introduce overhead during code analysis and background tasks, leading to increased CPU utilization and lag during editing or navigation in complex projects. Such issues are particularly noticeable on systems with limited , where frequent garbage collection interrupts workflow efficiency. Additionally, the integration of features in versions 2025.1 and later, such as the AI Assistant and coding agent Junie, has been noted to increase CPU utilization and consumption during code analysis and generation tasks. To address these challenges, users can optimize PyCharm by disabling unused code inspections, which reduces the computational load from real-time ; for instance, navigating to Settings > Editor > Inspections allows selective deactivation of non-essential checks like unused imports or style warnings. Employing an SSD for the project directory accelerates indexing and file operations compared to traditional HDDs, potentially halving load times for large repositories. Additionally, adjusting the JVM size via Help > Change Memory Settings—typically setting it to 50-75% of available RAM, such as 4-6 GB on an 8 GB machine—helps prevent out-of-memory errors and smooths performance during intensive tasks. Recent releases from 2024 onward have incorporated platform-level enhancements inherited from the base, including refined memory allocation for code analysis to minimize garbage collection pauses and improved indexing algorithms. These updates, combined with better plugin compatibility checks, have notably alleviated resource strains for users working with expansive applications or workflows.

Compatibility and platform issues

PyCharm offers comprehensive cross-platform support, compatible with Microsoft Windows 10 version 1809 (64-bit) or later, including (64-bit) or later; macOS 12.0 or later; and Linux distributions such as the two most recent stable LTS releases (e.g., 22.04 and 24.04) or compatible alternatives providing .deb and .rpm packages, like , , or . Native support for processors on macOS has been available since version 2020.3, enabling optimal performance on ARM-based hardware without emulation. Despite this broad compatibility, users encounter specific challenges on certain configurations. On Linux systems using the display server, occasional UI glitches arise, including scaling inconsistencies on high-DPI screens, blurry text with fractional scaling, and temporary unresponsiveness during project indexing—issues partially addressed by experimental support introduced in version 2024.2, though full native support is still in development as of 2025, with some glitches persisting. When integrating with (WSL), Python virtual environments may fail to create or detect automatically via the IDE, necessitating manual configuration of the interpreter path or environment activation in the terminal. Additionally, some third-party plugins exhibit incomplete ARM compatibility, particularly on , where native builds may not load or function correctly without updates or 2 fallback. Regarding Python runtime compatibility, PyCharm supports versions from 2.7 (legacy) to 3.14, with support for Python 2.7 effectively deprecated following its upstream end-of-life in January 2020, though basic functionality persists for existing projects; the features automatic detection and configuration of interpreters to streamline setup. To mitigate platform inconsistencies, PyCharm bundles the Runtime (a customized distribution) as its Java environment, ensuring uniform behavior across operating systems without reliance on external JRE installations. Users can access community-reported workarounds and fixes for hurdles through the official issue tracker, where developers often provide patches or configuration tweaks.

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