Run and debug Jupyter notebook code cells
You can execute the code of the notebook cells in many ways using the icons on the notebook toolbar and cell toolbars, commands of the code cell context menu (right-click the code cell to open it), and the Run commands of the main menu. Note that when you work with local notebooks, you don’t need to launch any Jupyter server in advance: just execute any cell and the server will be launched.
Run code cells
Use the following smart shortcuts to quickly run the code cells:
Ctrl+Enter: Runs the current cell.
Shift+Enter: Runs the current cell and select the cell below it.
When executing one cell at a time, mind code dependencies. If a cell relies on some code in another cell, that cell should be executed first.
In case of any errors, expand the Traceback node to preview the complete error message.
To execute all code cells in your notebook, click on the notebook toolbar or press Ctrl + Shift + Alt + Enter.
When you stop the server and change the server or kernel, you have to execute all cells with dependencies again, because execution results are valid for the current server session only.
When you execute your notebook, you can preview variables in the Variables tab of the Jupyter tool window.
By default, variables are loaded asynchronously. To change the loading policy, click in the Variables tab, select Variables Loading Policy, and select one of the available modes. See Managing Variables Loading Policy for more details.
You can click the link to the right of the variable to preview its values in the tabular form.
In addition to previewing values of the variables in the Variables tab, you can watch the values of the variable usages in the editor. Note that variable assignments are not shown.
To enable this option, select Show inline values in the editor in project .
Once you’ve executed the cell, its output is shown below the code. You can save the results or clear the output.
If your notebook cell involves any code that plots charts, you can save the chart as an image: right-click the output and select Save As from the context menu.
You can invert the plotted image for better readability. Select the Invert images in dark themes checkbox on the Jupyter page in the project Settings/Preferences (Ctrl+Alt+S) and restart the editor to apply the changes.
When any data frames are built, you can preview them in the tabular form. To open a data frame in an editor tab, right-click the cell output and selectmenu item.
You can copy the selected fragment or all cells of the table. To save the output in the *.csv format, select the menu item form the context menu and specify a filename. By default, the table is saved in output.csv.
You can sort data in a column by clicking its header. You can also copy a column header or all headers of the table to the clipboard. Just right-click any table header to get the context menu and select the target command.
You can manage the length of the notebook by expanding and collapsing cell outputs. Click an arrow nearby a cell counter to expand or collapse the cell output.
With PyCharm you can always quickly preview reference documentation for a particular variable, type, or argument.
Preview reference documentation
To view reference information for any element of a particular code cell, place the caret within the target code cell and type
? <type/variable/argument>. (in this example, you will preview documentation for
plt.scatter). Note that a code element should be accessible within the code cell.
Execute the cell. The Introspection tab opens in the Jupyter tool window.
Preview reference documentation in the Introspection tab.
Note that the Introspection tab shows documentation for the latest requested code element. Even though you proceed with executing other code cells, restart the server, or delete the line with your request, this information will be shown.
PyCharm provides the full-functional Jupyter Notebook Debugger.
Debug code in Jupyter notebooks
Set the breakpoints in the selected cell and press Alt + Shift + Enter for Windows or ⌥⇧↩ for macOS. Alternatively, you can right-click the cell and select from the context menu.
The Jupyter Notebook Debugger tool window opens.
Use the stepping toolbar buttons stepping toolbar to choose on which line you want to stop next and switch to the Debugger tab to preview the variable values:
Debugging is performed within a single code cell. However, if your code cell calls a function from any cell that has been already debugged, you can step into it. The related breakpoints will also work. Note that the cell with the function must be debugged not just executed.
Similarly, you can step into a function called from a Python file that is located in the same project.
Proceed with the debugging steps to complete the execution of the cell.
Tooltip and Shortcut
Action available on the Debugger toolbar.
Click this button to execute the program until the next line in the current method or file, skipping the methods referenced at the current execution point (if any). If the current line is the last one in the method, execution steps to the line executed right after this method.
Click this button to have the debugger step into the method called at the current execution point.
Click this button to have the debugger step out of the current method, to the line executed right after it.
Additional stepping actions available by clicking on the Debugger toolbar.
Force Step Over
Steps over the current line of code and takes you to the next line even if the highlighted line has method calls in it. If there are breakpoints in the called methods, they are ignored.
Smart Step Into
Smart step into is helpful when there are several method calls on a line, and you want to be specific about which method to enter. This feature allows you to select the method call you are interested in.
Run to Cursor
Click this button to resume program execution and pause until the execution point reaches the line at the current cursor location in the editor. No breakpoint is required. Actually, there is a temporary breakpoint set for the current line at the caret, which is removed once program execution is paused. Thus, if the caret is positioned at the line which has already been executed, the program will be just resumed for further execution, because there is no way to roll back to previous breakpoints. This action is especially useful when you have stepped deep into the methods sequence and need to step out of several methods at once.
If there are breakpoints set for the lines that should be executed before bringing you to the specified line, the debugger will pause at the first encountered breakpoint.
Force Run to Cursor
Continues the execution until the position of the caret is reached. All breakpoints on the way are ignored.