PyCharm 2022.2: Support for Python 3.11, Improved HTTP Client, and UX Enhancements

The Early Access Program for PyCharm 2022.3 has started! Participate to check out what’s new for version 2022.3.

We’ve just released the second bug-fix update for PyCharm 2022.2. You can update to this version from inside the IDE, by using the Toolbox App, or by using snaps for Ubuntu. You can also download it from our website. In this minor release, we’ve included major improvements for Python dataclass support.  For the attrs package, PyCharm now recognizes modern APIs such as attrs.define, attrs.mutable, and attrs.frozen, which are treated in the same way as attr.s, as well as  attrs.field, which is treated in the same way as attr.ib. PyCharm recognizes references to class at

Join the webinar by Christopher Trudeau to get started with Django Ninja.

Read an interview with Adam Symington, author of the PythonMaps project, concerning geospatial data visualization and the Python tools used in it.

In this Flask tutorial you will learn how to create a simple Flask application in a few minutes. By providing simple Flask web app example we will demonstrate how to get started with a Flask project and run your Flask app in PyCharm.

You can get the new build from our website, via the free Toolbox App, or by using snaps for Ubuntu.  To familiarize yourself with the most notable updates in v2022.2, browse the PyCharm 2022.2 EAP section of our blog. This release candidate also delivers some updates we haven’t previously covered, so read on for the latest news.  New action to generate tables of contents in Markdown files It’s now possible to easily generate tables of contents in Markdown files based on the document headers. This new action is available from the Insert and Generate popup menus that you can i

Easy access to relevant, safe data is a major bottleneck hindering developers and data scientists. But what if you could generate your own accurate, privacy-protected, shareable data?  Synthetic data can provide an inexpensive alternative to real sets of data that can’t be used due to its sensitivity or regulations. Such data is used for training machine learning models, testing, and performing quality assurance.  In this webinar with Mason Egger, we'll learn about using Synthetic Data, and we’ll learn how to get started creating our own Synthetic Data. Join us on July 2