JetBrains makes PyCharm, a Python IDE that analyzes your code while you type. Completion, refactoring, debugging, testing, and environment management all sit in the same window.
Python developers use it for scripting and web development, and for data science too. In the Python Developers Survey 2024 (JetBrains and the PSF, 2025), 25% named it their main editor. VS Code came first at 48%.
The edition setup changed with version 2025.1. JetBrains dropped the two-edition model and now ships one unified product. A free core, Jupyter Notebook support included, handles everyday work, and a paid Pro subscription adds web framework, database, and remote development tooling (JetBrains Help documentation, 2026).
What Is PyCharm?
JetBrains, a Czech company, released PyCharm 1.0 on October 13, 2010 (JetBrains press release, 2010), aimed at Python and Django developers. It’s built on JetBrains’ IntelliJ Platform.
The start date depends on who you ask. Wikipedia lists February 3, 2010 as the initial release, but its own history section puts the beta in July 2010 and version 1.0 three months later.
JetBrains’ documentation says PyCharm is built for general Python scripting. Web development and data science get their own tooling on top of that.
Python itself, meaning the language and its interpreter, comes from python.org. PyCharm is the tool where you write, run, and analyze code in that language. A project won’t run until at least one Python installation exists on the machine, which trips up a surprising number of first-time users.
For reference, the basics look like this:
- Made by JetBrains
- Version 1.0 shipped on October 13, 2010
- One unified product since PyCharm 2025.1 (April 2025)
- Python 2.7 and 3.9 through 3.15 are supported (PyCharm 2026.2 Help)
- Major versions arrive three times a year (JetBrains blog, 2025)
Is PyCharm Free? What the Core and Pro Split Means
Mostly, yes. Core PyCharm is free for commercial and non-commercial work, and a paid Pro subscription adds web framework, database, and remote development tooling.
What changed in 2025
PyCharm used to come as two products, the free Community Edition and the paid Professional Edition. With PyCharm 2025.1, JetBrains merged them into one unified product (PyCharm 2026.2 Help).
Community 2025.2 was the last standalone version, and from 2025.3 Community users move to the unified build. So anyone reading about the feature gaps between the old Community and Professional editions is reading about a split that no longer exists as two downloads.
The open-source parts of the codebase stay public on GitHub, and JetBrains still provides release builds that contain only those components (JetBrains blog, 2025).
What stays free
Every install starts with a 30-day Pro trial, and each new major release brings another one.
Once the trial ends, the core keeps working without a subscription. That covers the editor, completion, inspections, and refactoring, plus the debugger, test runner, Git, terminal, and Docker tooling (JetBrains editions page). Jupyter Notebook support is in there too, with running, debugging, and output rendering. Since PyCharm 2026.1 (March 2026), the JavaScript, TypeScript, and CSS tools are free as well.
What needs Pro
Pro adds the tooling that targets web frameworks, databases, and remote machines.
| Capability | Core (free) | Pro |
|---|---|---|
| Web frameworks | JavaScript, TypeScript, CSS, Vite generator | Advanced Django, Flask, FastAPI support |
| Notebooks | Run, debug, render output | Remote notebooks, dynamic tables, SQL cells |
| Remote work | Local interpreters | SSH, Docker, Docker Compose, WSL interpreters |
| Databases | Not included | Database tool window for querying and managing |
| Version control | Git, Mercurial, Subversion | Adds Perforce |
Some third-party download guides list Django, Flask, and FastAPI support as free. JetBrains’ editions page and Help (as of PyCharm 2026.2) place advanced support for all three in Pro.
For pure Python, scripts, and notebook work, the core is enough. Django with a database, or code that runs on a remote server, is where Pro pays off.
Pro is sold as a JetBrains subscription for individuals and organizations, and current prices sit on JetBrains’ buy page.
How Does PyCharm Help You Write Python Code?
PyCharm runs code analysis continuously, so completion, error detection, and fixes appear while you type instead of after you run the file.
Basic completion finishes names as you type, and smart type-matching completion narrows the suggestions by context. Inspections flag unused code, endless loops, and likely errors, and you set the severity per inspection. Press Alt+Enter on the lightbulb to apply a fix, or a change to code that’s already correct. Alt+Insert creates symbols from usage, and live templates (Ctrl+J) expand whole constructs.
Navigation follows the same logic. Find Usages sits on Alt+F7, go to declaration on Ctrl+B, and Search Everywhere on a double Shift.
PyCharm applies code refactoring across the whole project, so a rename reaches every file that uses the symbol. The founder of Astral, the company behind Ruff and uv, says in a testimonial on JetBrains’ site that this lets him refactor with confidence across complex projects.
PyCharm 2026.2 (July 2026) adds an editor minimap and integrates the Pyrefly type engine for faster type insight on large codebases (JetBrains blog, 2026).
AI assistance in PyCharm
With 2025.1, JetBrains made its AI features free in Pro. Some, such as code completion and local models, have unlimited use, while others run on limited credits (JetBrains blog, 2025).
Core PyCharm gets a free 30-day AI Pro trial through a plugin, per JetBrains’ editions page.
Since 2026.1, PyCharm describes itself as an open platform where you bring the AI agents you prefer. The 2026.2 release adds project generation from a prompt on the Welcome screen, which requires a JetBrains AI license.
How Do Running, Debugging, Testing and Version Control Work in PyCharm?
Every run, debug, and test action starts from a run/debug configuration, and PyCharm creates a temporary one the first time you run a file. You can save it as a permanent configuration later.
To run a script, right-click in the editor and choose Run, or click the gutter icon next to a __main__ block. Remote run, debug, and test, plus deployment to a server, need Pro.
Debugging
debugpy became the default debugger in PyCharm 2026.2, after shipping as an optional backend in 2026.1 (JetBrains blog, 2026).
Click the gutter to set a breakpoint, press Shift+F9, then step through the code, evaluate expressions, and add watches. This guide to debugging in PyCharm walks through a full session.
Since 2026.1, the debug console and expression evaluation also work inside async code, which matters for FastAPI and aiohttp apps.
debugpy doesn’t cover everything yet. Interpreters on remote targets (SSH, Docker, Vagrant) and Attach to Process still sit outside it, along with Sphinx doctest, Scrapy, remote Jupyter notebooks, and manage.py tasks other than the Django server and tests. In those cases, switch to pydevd under Settings | Python | Debugger, or use Attach to DAP for remote setups (PyCharm 2026.2 Help).
Testing
PyCharm supports unittest, doctest, nose, and pytest, and each one gets its own run/debug configuration.
Results land in the test runner tab of the Run tool window, and a failing test can be debugged like any other file. Setup details for the most common framework are in this walkthrough on running pytest in PyCharm.
Version control
Git, Mercurial, and Subversion work in core. Perforce is Pro only (PyCharm 2026.2 Help).
Local History runs next to version control and is always on. It tracks source and refactoring changes, so you can review them, revert them, or create a patch without making a commit.
How Does PyCharm Manage Interpreters and Environments?
PyCharm runs every project on a configured Python interpreter, either a system interpreter or a virtual environment made of a base interpreter and its installed packages (PyCharm 2026.2 Help). The environment types it knows about:
- Virtualenv, new or existing, on a base interpreter you choose
- pipenv, which manages packages through the Pipfile instead of pip
- Poetry, which PyCharm can install through pip if it isn’t detected
- uv, where you pick the Python version from a list and the uv executable is detected automatically
- Hatch, using an environment from the project’s own Hatch environments
- Conda, new or existing, through Anaconda or Miniconda
Which manager fits depends on the project, and this comparison of venv, conda, and Poetry lays out the trade-offs.
One base executable can back several interpreters. JetBrains’ own example is a Python 3.12 environment for Django apps and a second one on the same Python 3.12 for scientific libraries.
Switching takes one click in the status bar selector, or Settings | Python | Interpreter. The full procedure for adding a Python interpreter in PyCharm is covered separately.
Remote interpreters
Interpreters on SSH, Docker, Docker Compose, and WSL (Windows only) need Pro.
When you add one, PyCharm copies its helpers to the remote host and brings library sources and skeletons back to your machine, so completion keeps working locally.
Packages
PyCharm installs packages with pip by default, and with the conda package manager in conda environments. Outdated versions get an upgrade arrow, and you can upgrade several packages at once.
The Python Packages tool window adds search, documentation preview, and repository management. The 2026.2.1 update (August 2026) redesigned it so packages appear in a tree alongside their dependencies.
Where it breaks
- Python has to be installed first, and the interpreter setup needs the path to its executable
- Interpreters for versions PyCharm no longer supports get marked unsupported
- An Invalid environment warning shows up when the Python binary is missing or its version is unsupported
- Multi-project setups for uv, Poetry, and Hatch were still labeled Beta in 2026.2
Which Frameworks and Data Science Tools Does PyCharm Support?
Django and Flask get dedicated project types, template navigation, and run configurations in Pro, while notebook support sits in the free core.
Web development
FastAPI reached 38% usage in the Python Developers Survey 2024, ahead of Django at 35% and Flask at 34% (JetBrains and the PSF, published 2025).
The framework table in PyCharm 2026.2 Help itemizes the two older frameworks:
| Capability (Pro) | Django | Flask |
|---|---|---|
| Dedicated project type | Yes | Yes |
| Completion and inspections | Yes | Not listed |
| Template and view navigation | Yes | Yes |
| Test configurations | Yes | Not listed |
FastAPI is missing from that table, but JetBrains’ editions page lists it next to Django and Flask under advanced support in Pro. Treat the Help table as the detailed feature list and the editions page as the broader claim.
Recent releases added more framework hooks. PyCharm 2026.1 brought coding assistance for Django 6 template partials, a FastAPI dev Run mode, and a native Celery run configuration that reads Django project settings (JetBrains release notes, 2026).
Data science and notebooks
Jupyter Notebook support is free. The Jupyter tool window shows server state, links to the notebook in a browser, and has start and stop controls. The Variables tool window opens on every cell execution and can be refreshed or sorted by name or type. Each notebook gets its own Jupyter console with a Variables tab of its own, and the Structure tool window lists Markdown headings (Python cells too, if you ask for them). Debug Cell starts the debugger on whichever cell is selected.
One documented requirement: the Markdown plugin must be turned on, or notebook functionality does not work properly (PyCharm 2026.2 Help). Setup steps are in this guide to using Jupyter notebooks in PyCharm.
51% of surveyed Python developers work on data exploration and processing, and pandas and NumPy are the most used tools for it (JetBrains and the PSF, 2024 survey). Those libraries install from the Python Packages window, as this walkthrough on installing pandas in PyCharm shows.
Pro covers the scientific side, meaning analysis and visualization of scientific and statistical data. With the R plugin installed, statistical computing in R gets the same coding assistance (PyCharm 2026.2 Help).
The 2026.2.1 update (August 2026) lets AI agents work inside a notebook on a live kernel. It also brings a third-party plugin from the marimo team that opens, edits, and runs marimo notebooks (JetBrains blog, 2026).
How Do You Install PyCharm and What Does It Need to Run?
Install Python first, then PyCharm through the JetBrains Toolbox App or a standalone installer, on a machine with 4 CPU cores, 8 GB of RAM, and 10 GB of disk space (PyCharm 2026.2 Help).
System requirements
PyCharm wants an x86\_64 or arm64 CPU, 8 GB of RAM total with 3 GB of it available to the IDE, and a 1280 x 720 display. Java isn’t needed because JetBrains Runtime (JBR 21) ships with the IDE.
Supported operating systems:
- Windows 10 and 11
- macOS 15 and 26
- Linux, specifically Ubuntu 24.04 and 26.04 LTS, Fedora 43 and 44, Debian 13, and Amazon Linux 2023, with glibc 2.28 or later and Gnome or KDE Plasma
Toolbox App or standalone installer
JetBrains recommends the Toolbox App. It installs several products, or several versions of one product, updates them, and rolls back when something breaks. Logging in to a JetBrains Account activates available licenses automatically.
The standalone installer gives you manual control over the install location and configuration files, which suits policy-driven setups. ARM64 builds are separate, and the Download page carries a SHA checksum so you can verify integrity.
The Windows installer offers four options: a 64-bit launcher icon, Open Folder as Project in the context menu, a .py file association, and a launchers directory on the PATH. This guide to installing PyCharm on Windows walks through each one.
First launch
- Install Python from python.org, since PyCharm needs at least one installation on the machine.
- Install PyCharm through the Toolbox App or the standalone installer.
- Launch it and, in the Import Settings dialog, pick settings from another IDE found on the machine (Visual Studio Code is among the options) or skip the step.
- On the Welcome screen, choose a theme and keymap, then click New.
- Select an interpreter. PyCharm creates an isolated virtual environment for the project.
- Add a Python file and run it.
In the core, PyCharm creates plain Python projects only, while Pro adds web framework project types (PyCharm 2026.2 Help). Details on creating a new project in PyCharm cover each option.
No project is required for quick work. The Notebook and Script buttons on the Welcome screen create a file inside an automatically generated PyCharmMiscProject.
PyCharm or VS Code: Which Should You Use?
PyCharm suits Django or Flask projects, remote interpreters, and anyone who wants an install that needs no extensions. VS Code suits a lighter footprint and a setup you assemble yourself from extensions.
How the two compare
VS Code builds its Python support from the Microsoft Python extension, and an interpreter still has to be installed separately (VS Code documentation, 2026). That extension model is also where its flexibility comes from, as this overview of VS Code extensions shows.
| Criterion | PyCharm | VS Code |
|---|---|---|
| Python tooling | Bundled in the IDE | Microsoft Python extension |
| Notebooks | Jupyter support in the core | Jupyter extension |
| Hardware guidance | 8 GB RAM, 4 cores, 10 GB disk | 1 GB RAM, under 500 MB footprint |
| Debugger engine | debugpy by default since 2026.2 | debugpy via Python Debugger extension |
The hardware row compares a JetBrains requirement with a Microsoft recommendation, so the gap is a floor against a suggestion. It’s still a gap of several gigabytes.
What the survey data says
PyCharm was the main IDE for 31% of respondents in 2023 and 25% in 2024, while VS Code moved from 41% to 48% (JetBrains and the PSF surveys).
ZDNet’s May 2020 coverage of the third annual survey (conducted in 2019) had PyCharm first at 33% and VS Code at 24%, so the lead flipped across editions. Question wording and samples differ between editions, so read the trend as direction, not precision.
The choice is rarely exclusive anyway. 80% of respondents use additional editors next to their main one, and 42% use three or more (JetBrains and the PSF, 2024 survey).
Deciding between them
PyCharm makes more sense when the project is Django or Flask and you want dedicated project types and template navigation (Pro), when code has to run on SSH, Docker, or WSL interpreters (Pro), or when the machine has at least 8 GB of RAM.
VS Code fits better on a machine that sits near the 1 GB RAM recommendation, or if you’d rather assemble tools from extensions than install one IDE.
A feature-by-feature breakdown lives in this comparison of VS Code and PyCharm.
Is PyCharm good for beginners?
Half of the survey respondents, 50%, have under two years of professional coding experience (JetBrains blog, The State of Python 2025), so beginner fit is a fair question.
On first launch, the Import Settings dialog lists settings from other IDEs on the machine, Visual Studio Code included. The Learn button on the Welcome screen opens the IDE feature trainer. No subscription is needed to start, though the 8 GB RAM spec still applies.
When Is PyCharm the Wrong Fit?
It’s the wrong fit on machines below the 8 GB RAM spec, with very large files, on remote setups over slow or shared-filesystem networks, and in configurations JetBrains doesn’t support.
PyCharm runs on the JVM. JetBrains says the default JVM options are optimal in most cases and suggests raising -Xmx, for example to -Xmx2048m, when slowdowns appear (PyCharm 2026.2 Help). Educative’s overview lists slow loading and high memory use as the main cons.
On large files, PyCharm opens anything up to 20,000 KB (about 20 MB) by default and provides coding assistance only up to 2,500 KB (about 2.5 MB). Both limits are platform properties you can raise, at the cost of editor performance and memory (PyCharm 2026.2 Help).
Remote development has its own requirements:
- Local disk or network block storage, so NFS and SMB shares are not supported
- OpenSSH server 7.9p1 or later
- At least 20 Mbps between client and server, with latency no higher than 200 ms
- At least 50 Mbps downstream capacity on the server
Some setups are simply unsupported, including BSD-based operating systems, configurations with a modified JRE or JDK, and installations where distribution files such as plugin files were manually removed or changed.
The Linux snap package carries its own documented problems: performance degradation, trouble debugging JavaScript in Chromium, and delays in file operations. JetBrains recommends the Toolbox App instead.
PyCharm FAQ
Can students and open source maintainers get PyCharm Pro for free?
Yes. Full-time students at accredited institutions get PyCharm Pro through the JetBrains Student Pack, valid for one year and renewable each year while they stay enrolled.
Core contributors and committers on open source projects can apply for a separate free license (JetBrains, 2026).
How do you update PyCharm?
PyCharm checks for updates automatically and usually applies them as a patch that needs only a restart.
Toolbox App installs prompt for updates and offer an Update all tools automatically setting, while snap installs update automatically in the background (PyCharm 2026.2 Help). On Linux, extract a new major version into a clean directory instead of updating in place.
Which keyboard shortcuts matter most?
Learn Ctrl+Shift+A (Find Action) first. After that come Ctrl+E for recent files, Ctrl+W to extend the selection, and Shift+F10 to run.
Find Action also lets you assign a shortcut to any command that lacks one. This overview of PyCharm keyboard shortcuts lists the rest of the defaults.
What is the difference between PyCharm and IntelliJ IDEA?
IntelliJ IDEA is the JetBrains IDE for Java and picks up Python through the Python plugin, while PyCharm is built for Python from the start.
Both now ship as unified products with a free core, IntelliJ IDEA from 2025.3 and PyCharm from 2025.1 (JetBrains). This comparison of PyCharm and IntelliJ IDEA covers the rest.
Is DataSpell still available?
No. JetBrains deprecated DataSpell as a standalone product on May 28, 2026, and converted eligible subscriptions to PyCharm Pro on September 1, 2026 (JetBrains blog, 2026).
DataSpell was built around data exploration, and PyCharm Pro now covers Jupyter notebooks, data analysis, and interactive development.
How do you uninstall PyCharm?
Open the Toolbox App and choose Uninstall for that instance, or remove a standalone install through the operating system.
A standalone removal keeps settings and caches by default, so delete the version folders under %APPDATA%\JetBrains and %LOCALAPPDATA%\JetBrains on Windows if you won’t reinstall.
Knowing When the Free Core Is Enough
The free core covers a project until a Pro-only feature turns into a weekly need. So the 30-day trial belongs to real project work, not to poking around menus.
Major releases come three times a year and each carries its own 30-day Pro trial, which adds up to 90 days of Pro access per year without a subscription.
The trial clock starts at install, so the order matters. Create the project with its own virtual environment first, run your actual workflow during the trial, and pay only if a Pro-only feature turns out to be something you need every week. A guide to setting up PyCharm covers that first step.
The trade-off is a hard stop. SSH and Docker interpreters, for example, are unavailable once the trial ends and only the core remains.
Recheck the Pro list at each major release, because a feature moving into the core would change this advice (verified October 2026 against PyCharm 2026.2 Help).
- Show Hidden Characters, Spaces, and Line Endings in Notepad++ - October 19, 2026
- Military and Defense UI/UX Design Services Firms to Know in 2026 - October 19, 2026
- How to Manage Your Google Play Subscriptions - October 17, 2026
