The JetBrains Blog
Live Stream: From Jupyter Notebooks to JetBrains DataSpell
Join us Tuesday, August 17, 6 pm – 7 pm (CEST) / 12 am – 1 pm (EDT), for our live webinar “From Jupyter Notebooks to JetBrains DataSpell”. In this webinar, Andrey Cheptsov, Product Manager for PyCharm and DataSpell, will preview JetBrains DataSpell – a brand new IDE for data scientists. Over the last few years, PyCharm users have often requested better support for Jupyter notebooks. So a ye
Announcing Datalore Enterprise – The Smart and Secure Jupyter Environment for Data Science Teams
Jupyter notebooks are arguably the most widely used tool in data science. However, when it comes to collaboration, resource management, and security...
PyCharm 2021.1.1: Improved Indexing and Jupyter Notebooks Experience
The first update of PyCharm 2021.1 brings some important bug fixes, including one that addresses an inability to find occurrences in files and in paths. It also provides improvements to the experience of working with Jupyter Notebooks, along with updates to a variety of other features. DOWNLOAD PYCHARM 2021.1.1 Here are the major improvements: The complete list of improvements
Kotlin Kernel for Jupyter Notebook, v0.9.0
This update of the Kotlin kernel for Jupyter Notebook primarily targets library authors and enables them to easily integrate Kotlin libraries with Jupyter notebooks. It also includes an upgrade of the Kotlin compiler to version 1.5.0, as well as bug fixes and performance improvements. pip installConda install The old way to add library integrations As you may know, it was already possible to inte
We Downloaded 10,000,000 Jupyter Notebooks From Github – This Is What We Learned
Here’s how we used the hundreds of thousands of publicly accessible repos on GitHub to learn more about the current state of data science.
Datalore Pro: Online Jupyter Notebooks with GPU Access, Hosted by JetBrains
We have some really exciting news for you – we’ve introduced a new Datalore plan, called Datalore Professional. This new plan comes with increased processing power and added storage for even faster calculation of bigger datasets.
Datalore by JetBrains: Online Jupyter Notebooks Editor With PyCharm’s Code Insight
If you work with Jupyter Notebooks and want to run code, produce heavy visualizations, and render markdown online – give Datalore a try. It comes with cloud storage, real-time collaboration, notebook publishing, and PyCharm’s code insight. In this blog post we’ll give you a quick introduction to what you can do in Datalore. Try Datalore Jupyter notebooks in the cloud Once you register a Datalore
Kotlin Kernel for Jupyter Notebook, v0.8
Hi folks! Today we have released a new version of the Kotlin kernel for Jupyter Notebook, and if you are experimenting with data — give notebooks with Kotlin kernel a try. One of the great things about Jupyter Notebook is its interactive nature. It allows you to quickly get familiar with your data, try out some ideas, and run some experiments. Kotlin kernel helps you iterate over your ideas ev
Jupyter, PyCharm and Pizza
Hi there! Have you tried Jupyter Notebooks integration in PyCharm 2019.2? Not yet? Then let me show you what it looks like! In this blog post, we're going to explore some data using PyCharm and its Jupyter Notebook integration. First, of course, we'll need said data. Whenever I need a new dataset to play with, I typically head to Kaggle where I'm sure to find something interesting to toy with. Thi
How We Did the New Jupyter Support: Interview with Anton Bragin
Data science and Jupyter Notebooks are obviously super-big in Python. PyCharm has had Jupyter support for several years but we needed to do a re-think, to better align our “IDE for Python Professionals” mission with Jupyter workflows. PyCharm 2019.1 delivers that re-think with completely re-implemented Jupyter Notebook support. We’re proud of it and decided to interview Anton Bragin, our lead d
New in Datalore: Kernel Changes, New Automatic plots, Tutorials, and More
We have been busy this month laying the foundations for future features. This work will enable us to take some big steps with Datalore over the coming year.