PyCharm, a JetBrains IDE

Setting up a Python monorepo shouldn’t be this complicated. PyCharm 2026.1.1 removes the friction right from the start: • Automatic detection and setup of your uv workspace. • A single virtual environment for the entire workspace. • Automatic installation of the correct Python version via uv. • Interpreter configuration handled for you. And that’s just the beginning – the same workspace then lets you navigate, refactor, and run code across all packages in one place. Watch how it works and try it yourself: 🔗 youtube.com/watch?v=h_LiJj… 🔗

#PyConUS is underway – and PyCharm is at booth 421, from May 13–19! Come say hi to the PyCharm team, check out live demos, take the Python quiz, grab coffee, and create a 90s-style bracelet! Chat with us about Python, PyCharm, data science, web development, community, and more. Don’t miss Artem Trofimov’s talk: “Text2SQL: From Academic Benchmarks to Self-Service Analytics”. See you at booth 421!

Feeling like you don’t belong as a beginner? Imposter syndrome isn’t something you “fix”; you learn to work with it. What actually helps: • Code is a tool, not the goal Focus on the problems you care about, not just the code itself. • Get mentors early Progress is much faster when someone guides you. • Ask questions before you feel ready Waiting until you’re “good enough” only slows you down. • Use AI, but don’t trust it blindly It can help, but always validate and get feedback. ▶️ Watch the full talk by Travis Oliphant (@teoliphant) on why people and community matter more than ever in the age of AI: youtu.be/opzIYSWWZ3E

Longtime PyCharm user Johannes Rüschel has reported 1,264 issues to PyCharm’s tracker and nearly 50 more to the IntelliJ Platform’s. Why? “I have this small kid in me who wants to break things.” In our interview, Johannes shares: • Why great engineers spend more time understanding problems than writing code. • Why reading code can be harder than writing it. • Why contributing to open source is more than just PRs. • How Junie helped him contribute to PyCharm without deep knowledge of Kotlin. • What reporting PyCharm issues taught him about developer tools. • Why programmers should think more like doctors. Watch the conversation on improving the tools we use every day: 🔗 youtube.com/watch?v=HHRrKl… 🔗

Most comparisons of #PyTorch vs. #TensorFlow stop at the features. In practice, the decision usually comes down to constraints: • Deployment target Shipping to mobile or edge devices? TensorFlow Lite is still the most mature option. • Team experience New to ML or iterating fast? PyTorch’s Pythonic workflow removes a lot of friction. • Project phase Research and prototyping → PyTorch Production pipelines and MLOps → TensorFlow (TFX, Serving) • Infrastructure Need TPUs or deep GCP integration? TensorFlow has the edge. Switching isn’t impossible – tools like ONNX let you move models between frameworks when needed. Before choosing, ask yourself: “What constraints am I optimizing for?” Full guide and decision matrix: jb.gg/pytorch-vs-ten…

You don’t become an expert in programming overnight, and that’s normal. Even Travis Oliphant (@teoliphant), creator of NumPy, says he’s been coding for 30+ years and is still learning. What you should do instead: • Ask questions early (don’t wait until you “feel ready”). • Find people who are slightly ahead of you. • Get feedback on what you build. • Accept that confusion is part of the process. Feeling like you don’t know enough isn’t a blocker; it’s the starting point. 👉 Watch the full talk: youtu.be/opzIYSWWZ3E

#AI is making Python easier… and harder at the same time. • Experienced developers are moving faster than ever. • Beginners risk relying on AI too early and missing the fundamentals. Watch the full video recap of our Python conference for more insights and the hosts’ top picks of the talks: 🔗 youtube.com/watch?v=eBc1dA… 🔗

This might be the simplest way to start a #TensorFlow project 🤖 A robot breaks it down into four steps: • Clone a repo with starter examples • Modify the code for your use case • Set up a virtual environment • Install dependencies If you’ve been stuck on “where do I even begin?” with computer vision projects, watch the full video by @iuliaferoli: youtube.com/watch?v=F8uUIe…

Installing random AI Agent Skills from GitHub? Risky move ⚠️ Skills can run scripts under the hood – so the source matters. Check out JetBrains' curated skills repository: github.com/JetBrains/skil…

Looking for a clear overview of what’s happening in #Python right now? We turned 13 Python expert talks into a list of insights you can use to: • Understand how AI is changing development, from learning Python to agentic coding. • See what’s happening to open source as AI increases contributions (and pressure on maintainers). • Decide where to focus next, from Django and data tools like Polars to open-source AI. It’s designed to help you explore the Python ecosystem more efficiently, whether you’re learning, building, or just keeping up with the changes. Read the blog post: 🔗 jb.gg/pytv-takeaways 🔗

#JupyterHub was rolled out to 1,000+ users, and no one knew if it would survive. You can’t fully predict how people will use your system, especially at scale. Real-world usage will always break your assumptions. Watch the full talk by Carol Willing on problem-solving with Jupyter and AI: youtu.be/Wg99AGQcohY

Why work with a single AI agent when you can use multiple? The new ACP Agent Registry lets you install and manage AI agents inside your IDE. ✔️ Choose from agents like Cursor, Claude, and Gemini ✔️ Install in seconds from AI Chat ✔️ Add custom agents via acp.json All your AI tools, one seamless workflow. Explore What’s New in PyCharm 2026.1 → jb.gg/pcwn

What’s actually happening in #Python right now? We recently hosted a free online conference featuring 13 expert talks on AI, data science, web development, and open source. Don’t have time to watch it all? Here are some of the most useful insights: • Python isn’t “just for beginners”; it powers serious AI and production systems. • Learning tip: Tutorials aren’t enough – you have to build real projects without over-relying on AI. • AI is changing how developers work, from agentic coding to new workflows. • Open source is under pressure, with more AI-generated contributions and fewer maintainers. • New trends include Polars, Django evolution, open source AI, and better LLM data handling. • Python’s real strength is its global community, not just the language. Want the full picture? ▶️ Watch the “Python Unplugged on PyTV” recap by conference hosts Jodie Burchell, Cheuk Ting Ho, and Will Vincent: youtube.com/watch?v=eBc1dA…

Multi-agent vs. RAG vs. single agent 🤔 When can you use a single agent, and when is that not enough? The choice isn’t about trends or complexity. It’s about stakes. If the stakes are high, don’t hand over decisions to an LLM. The key question is “how much risk can you afford?” Watch the full talk: youtu.be/4QYA2X6Zlqg

“I’m feeling impressed… and excited to see it in action.” 🤖 That’s a robot reacting to its *own* vision system. Behind it is a #TensorFlow model running live, recognizing the world through a camera and responding in real time. The interesting part is not the model itself, but what happens when you connect it to something physical. If you’ve ever wondered how to go from “it works in a notebook” to “it works in the real world”, this is exactly that step. Watch the full video by @iuliaferoli to learn how you can build, adapt, and deploy your own real-time object detection app using PyCharm and AI tools 👇 ▶️ youtube.com/watch?v=F8uUIe… #ReachyMini is made by @pollenrobotics and @huggingface.

Why didn’t AI alone solve this problem? A researcher reduced a simulation from weeks to under a day, but not by just throwing AI or GPUs at it. The real breakthrough? Breaking the problem down first. The key insight: Better thinking is more valuable than more computing. Watch the full talk by Carol Willing to learn how to approach #AI and #Python more effectively: 🔗 youtu.be/Wg99AGQcohY 🔗

Python monorepos can break your flow fast. Multiple virtual environments. Dependencies drifting out of sync. Jumping between projects just to run a test. PyCharm 2026.1.1 changes that with uv workspaces support: • One workspace-level virtual environment – no more juggling interpreters. • Consistent dependency management at the workspace or package level. • Navigation, refactoring, and execution across subprojects in one place. • Smarter package management that updates the right `pyproject.toml`. It’s a cleaner way to work with complex Python projects – whether you use #uv, #Poetry, or #Hatch. Download PyCharm now for free. ▶️ And watch the deep dive by Paul Everitt to see how it works: youtube.com/watch?v=h_LiJj…

How do you choose an agent framework today? Tuana Çelik (@tuanacelik) from @llama_index explains why the criteria have changed 👇 🧠 Before, the choice was about developer experience, maintenance, and framework features. ⚡ Now: • The barrier to entry is lower. • Framework differences matter less. • The tooling around them matters more. 🔎 What to focus on: Look at the ecosystem and what it helps you build. 🧭 The key takeaway: It’s not about the “best” framework anymore – it’s about what you can build with it. ▶️ Watch the full talk: youtu.be/4QYA2X6Zlqg

If you’re still choosing between #PyTorch and #TensorFlow based on “which is better”, you’re asking the wrong question. In 2026, the real difference is where each one wins: • PyTorch: dynamic graphs, Pythonic API, more natural debugging • TensorFlow: production-first ecosystems Where each is used: • NLP: PyTorch dominates (Hugging Face, faster iteration) • Computer vision: split between research (PyTorch) and mobile/edge (TensorFlow) • Reinforcement learning: PyTorch for experimentation, TensorFlow for production Performance is similar for most workloads. The real gap is in deployment, tooling, and workflows. The frameworks aren’t mutually exclusive – teams often combine them depending on the stage. 👉 Get a full comparison and decision matrix: jb.gg/pytorch-vs-ten…

uv in your remote environment? Done. PyCharm 2026.1 brings seamless uv support for your remote projects. 👀 No more manual syncs or environment issues. ✔️ WSL, SSH, and Docker support ✔️ `uv` as your remote interpreter ✔️ Fully synced project environment ✔️ Seamlessly install and run packages All in PyCharm 2026.1. Explore What’s New in PyCharm 2026.1 → jb.gg/pcwn