Third PyCharm 4 EAP: NumPy array viewer, IPython notebook improvements, and more

Posted on by Dmitry Filippov

Today we’re glad to let you know that the third PyCharm 4 EAP build 139.354 is ready for your evaluation. Please download it from our EAP page.

Just as always, this EAP build can be used for 30 days after its release date and it doesn’t require any license.

Comparing to the previous EAP builds, this one mostly includes a consolidation of fixes for various bugs and problems, and improvements for recently added features. For the detailed list of notable changes and improvements, please check the Release Notes.

The most notable brand-new feature in this build is the NumPy array viewer which is available from the debugger and the integrated Python console:

numpyarrays

To view a NumPy array, run your project in a debug mode and find the NumPy array in the variables list shown in the PyCharm`s graphical debugger. Right-click it and select “View as Array”.

To follow the scientific mood of this PyCharm 4 EAP build, we also added the support for matplotlib in the integrated python console.

This build also brings a lot of improvements to the recently announced IPython Notebook integration:

ipynb2

PyCharm now works better with cells of different types. We’ve fixed issues with cell rendering and some bugs related to wrong PyCharm behavior inside ipynb cells. Now PyCharm starts the IPython notebook automatically when running a ipynb file or separate cells in it.
When working with IPython notebook files, PyCharm now provides well-known shortcuts: for example you can press Shift+Enter to run a cell or Ctrl+Shift+Down to move a cell down. See the list of IPython notebook shortcuts here and try them in PyCharm.
The full list of IPython notebook improvements can be found in our issue tracker.

The new “Attach to process” feature introduced with the previous build is now available under the Mac OS platform!

Please take PyCharm 4 EAP build 139.354 for a spin! We hope that there will be no major issues, however, should you encounter any problems, please report them to our public tracker.
No patch update for this EAP build will be available from within the IDE. Please download the full installation source for your platform and install it along the previous installations of PyCharm.

Stay tuned for PyCharm 4 release announcements, follow us on twitter, and develop with pleasure!

-PyCharm team

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12 Responses to Third PyCharm 4 EAP: NumPy array viewer, IPython notebook improvements, and more

  1. Frank says:

    November 6, 2014

    What a release tempo! Viewing numpy arrays is a most welcome addition to an already amazing product! I will take the new version for a test drive later today… my first experiments with existing notebooks were not very fruitful, but I am certain all will work in due time. Thank you!

  2. santi says:

    November 7, 2014

    The array viewier is snappy, even with large arrays… congrats! What about pandas dataframes? A wild guess, it would not be too hard to support them, since they are just numpy arrays with some deco…

  3. Heikki Arponen says:

    November 7, 2014

    Nice!! Yeah, Pandas viewer would be extremely nice!

  4. Dmitry Filippov says:

    November 7, 2014

    We’ve created a feature request for Pandas viewer here: https://youtrack.jetbrains.com/issue/PY-14330
    please comment and vote for this ticket.

  5. Alexey says:

    November 9, 2014

    When Pycharm 4 will be released?

    • Dmitry Filippov says:

      November 10, 2014

      We plan to release it in a few weeks by the end of November.

  6. Hans says:

    November 15, 2014

    Hey

    Wonderful news!

  7. Pawel says:

    June 17, 2015

    Great news! However, can we expect to see a Matlab-style of the variable viewer for PyCharm? The pressure is high especially more and more people uses numpy or pandas and an ability to view values of variables speeds up writing the code.

    The competition (Spyder, Rodeo) already included that piece of IDE.

    Thank you!

    • Dmitry Filippov says:

      June 18, 2015

      Thank you for the suggestion. We’re currently working on improvements to matplotlib, numpy and pandas support.

  8. Craig says:

    November 22, 2015

    Nice one with the view as array functionality as that really helps. Only thing is that it would be much better if the view updated as the data in the array updates.

    Thanks a lot.

  9. ikku100 says:

    December 24, 2016

    I totally agree with Craig, it would be great if the view on the array would update. Great functionality already though.

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