PyCharm is designed to support the full range of modern Python workflows, from web development to data and ML/AI work, in a single IDE. An essential part of these workflows is Jupyter notebooks, which are widely used for experimentation, data exploration, and prototyping across many roles.

PyCharm provides first-class support for Jupyter notebooks, both locally and when connecting to external Jupyter servers, with IDE features such as refactoring and navigation available directly in notebooks. Meanwhile, Google Colab has become a key tool for running notebook-based experiments in the cloud, especially when local resources are insufficient.

With PyCharm 2025.3.2, we’re bringing local IDE workflows and Colab-hosted notebooks together. Google Colab support is now available for free in PyCharm as a core feature, along with basic Jupyter notebook support. If you already use Google Colab, you can now bring your notebooks into PyCharm and work with them using IDE features designed for larger projects and longer development sessions.

Getting started with Google Colab in PyCharm

Connecting PyCharm to Colab is quick and straightforward:

1. Open a Jupyter notebook in PyCharm.
2. Select Google Colab (Beta) from the Jupyter server menu in the top-right corner.
3. Sign in to your Google account.
4. Create and use a Colab-backed server for the notebook.

Once connected, your notebook behaves as usual, with navigation, inline outputs, tables, and visualizations rendered directly in the editor.

Working with data and files 

When your Jupyter notebook depends on files that are not yet available on the Colab machine, PyCharm helps you handle this without interrupting your workflow. If a file is missing, you can upload it directly from your local environment. The remote file structure is also visible in the Project tool window, so you can browse directories and inspect files as you work.

Whether you’re experimenting with data, prototyping models, or working with notebooks that outgrow local resources, this integration makes it easier to move between local work, remote execution, and cloud resources without changing how you work in PyCharm.

If you’d like to try it out:

• Download PyCharm 2025.3.2
• Learn more about Google Colab

Artificial intelligence has continued to enter our daily lives, minimizing its presence in laboratories and traditionally viewed as a component of applications and tools. Large language models (LLMs) are at the core of this change and now power products that can produce text, respond to queries or even direct workflows. Python frameworks have enabled this jump by providing developers with pre-built methods to integrate LLMs into the real world. 

However, this brings up a significant issue, which is whether these frameworks are merely wrappers of the existing models, or they are redefining the way we design and develop modern software. Outside laboratory settings, LLMs have transformed the industries in regard to automation, individualization and data-driven decision-making. Since the beginning of their use by startups to interact with the customers and the enterprises automating documentation, AI products impact nearly every area. The change of development is not only technical, but strategic to make the cycle of innovations faster and the distance between an idea and its implementation shorter.

Learn how to integrate TX Spell .NET with the Document Editor on a Linux server using ASP.NET Core. This guide covers setup, configuration, and best practices for seamless spell checking functionality.

In the previous post, you added environment-scoped variables to customize the message displayed in each environment. In this post, you’ll add an environment-scoped step to prompt for manual approval before deploying to production.

Prerequisites

• An Octopus Cloud account. If you don’t have one, you can sign up for a free trial.
• The Octopus AI Assistant Chrome extension. You can install it from the Chrome Web Store.

Creating the project

Paste the following prompt into the Octopus AI Assistant and run it:

Create a Script project called "03. Script App with Manual Intervention", and then:
* Add a manual intervention step as the first step in the deployment process, scoped to the Production environment only, with the instruction "Please approve deployment to Production".

You can now create a release and deploy it to the first environment. Progress the deployment through to the Production environment to see the Manual Intervention step in action.

Before the deployment to Production can proceed, you will need to approve the manual intervention step. This step is often used to enforce a business approval process before deploying to production.

What just happened?

You created a sample project with:

• A Manual Intervention step that only runs when deploying to the Production environment.

What’s next?

The next step is to add retry logic to the steps.

Agile in Construction: The DOWNTIME Strategy—Eliminating Waste Before Adding Process With Felipe Engineer-Manriquez

Read the full Show Notes and search through the world's largest audio library on Agile and Scrum directly on the Scrum Master Toolbox Podcast website: http://bit.ly/SMTP_ShowNotes.

 

"My first rule is that I will do no harm. And if something goes wrong, I will take full responsibility with leadership. My neck is literally on the line." - Felipe Engineer-Manriquez

 

Felipe shares his change strategy for introducing Lean and Agile into construction projects, and it starts with an unexpected principle borrowed from Hippocrates: do no harm. He explicitly tells teams this promise, putting his neck on the line to build trust. But the real magic happens in what comes next: instead of adding new processes, Felipe first helps teams stop doing things. Using the DOWNTIME acronym (Defects, Overproduction, Waiting, Transportation, Inventory, Motion, Excess processing), he identifies wasteful activities that don't add value. In construction, 60-80% of every dollar doesn't add value from the customer's perspective—compared to manufacturing (above 50% value) or agriculture (90% value). Felipe's approach: eliminate waste first to create excess capacity, then introduce new processes. On a project that was 2 years behind schedule with lawyers already engaged, he spent just 5 minutes with the team defining a visible milestone goal on a whiteboard. Two weeks later, they met their schedule and improved by 4 days—the first time ever. The superintendent said, "Never in the entire time I've worked here have we ever met a schedule commitment." The secret? Free up capacity before adding anything new.

 

In this episode, we refer to the 8 wastes video by Orbus and WIP limits.

 

Self-reflection Question: Before introducing your next process improvement, what wasteful activity could you help your team stop doing to free up the capacity they need to embrace change?

 

[The Scrum Master Toolbox Podcast Recommends]

🔥In the ruthless world of fintech, success isn't just about innovation—it's about coaching!🔥

Angela thought she was just there to coach a team. But now, she's caught in the middle of a corporate espionage drama that could make or break the future of digital banking. Can she help the team regain their mojo and outwit their rivals, or will the competition crush their ambitions? As alliances shift and the pressure builds, one thing becomes clear: this isn't just about the product—it's about the people.

 

🚨 Will Angela's coaching be enough? Find out in Shift: From Product to People—the gripping story of high-stakes innovation and corporate intrigue.

 

Buy Now on Amazon

 

[The Scrum Master Toolbox Podcast Recommends]

 

About Felipe Engineer-Manriquez

 

Felipe Engineer-Manriquez is a best-selling author, international speaker, and host of The EBFC Show. A force in Lean and Agile, he helps teams build faster with less effort. Felipe trains and coaches changemakers worldwide—and wrote Construction Scrum to make work easier, better, and faster for everyone.

 

You can link with Felipe Engineer-Manriquez on LinkedIn.

 

You can also find Felipe at thefelipe.bio.link, check out The EBFC Show podcast, and join the EBFC Scrum Community of Practice.

Download audio: https://traffic.libsyn.com/secure/scrummastertoolbox/20260128_Felipe_Engineer_W.mp3?dest-id=246429

It is review season, and you might be finding yourself confused: you received high ratings and "exceeded expectations," yet the promotion you expected didn't happen. In this episode of the Career Growth Accelerator, I break down exactly why high performance doesn't always lead to promotion, helping you identify the structural roadblocks and strategic shifts necessary to move from senior individual contributor to staff, principal, or leadership roles,.

• Understand why your performance review is never conducted in a vacuum and why your manager’s peers—not just your manager—are the "voters" you need to convince with clear evidence,.

• Learn why high ratings often fail to translate into a promotion if you haven't demonstrated specific impact on the company's strategic goals rather than just your own deliverables.

• Discover the first major roadblock: Structural limitations where the role you want simply doesn't exist because the business context or organizational pyramid doesn't currently support it,.

• Explore the concept of "Outer Layers" of scope—moving from self-focus to team-focus, and finally to business-strategy focus—to unlock the next stage of your career,,.

• Identify the "indispensable trap" where performing too well at your current inner-layer responsibilities makes you terminal in your role rather than promotable.

🙏 Today's Episode is Brought To you by: Unblocked

There’s a good chance you’ve already tried a few AI code review tools — and you’re probably ignoring most of their comments.

Not because AI can’t review code, but because it’s missing context. Most AI reviewers focus on surface-level issues: style nits, obvious refactors, or restating what’s already clear from the diff. Meanwhile, the things you actually care about, like whether a change violates an earlier architectural decision or quietly duplicates existing logic, go unnoticed.

That’s the problem Unblocked is built to solve.

Unblocked’s AI code review is grounded in decision-grade context, prior PRs, design discussions, documentation, and system-level constraints, the same context senior engineers rely on when reviewing code.

Teams using Unblocked report fewer comments, higher signal, and automated reviews they actually trust — enough that many have turned off other AI review tools entirely.

Even if you’ve already written off AI code review, Unblocked is worth a look.

Get a free three-week trial at getunblocked.com/developertea.

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