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This article mainly explains "how to debug and run Pycharm code". The content of the article is simple and clear, and it is easy to learn and understand. Please follow the editor's train of thought to study and learn how to debug and run Pycharm code.

1. Preparatory work

(1) Python version 2.7 or higher

(2) A Python project has been created and content has been added. For more information: Getting Started tutorial

2. The first step is to run the code

Open the previously written Solver.py file, right-click in the edit box, and select the "Run 'Solver'" option on the shortcut menu.

The script file runs normally and the output value of the program is displayed in the debug tool window:

Next, we will explain the details of these two steps in detail.

3. What is the Run/Debug mode

Each script file that needs to be run / debugged requires a special configuration file to specify its script name, directory, and other important running debugging information. Pycharm has integrated this profile to prevent users from creating it manually.

Every time you click the Run or Debug button (or do the same in the shortcut menu), the current run / debug configuration file is actually loaded into the current debug model.

If you look closely at the first picture, you will find that there is no information about run/debug in the combo box until they appear in the second picture. This means that the run/debug configuration file for the Solver script is automatically generated when the run / debug command is executed, as shown now.

At this point, the Run (green arrow button) and Debug (green Beetle button) buttons in the main toolbar become available:

At the same time, the two icons are still translucent, which means that they are temporary, that is, created automatically by Pycharm.

OK, click the drop-down arrow to view the currently available command actions:

If you have set up more than one run/debug configuration scheme, they will all be displayed in the drop-down list here. Click to select one as the run/debug configuration file for the current project.

4. Save run/debug configuration information

In the drop-down list in the figure above, click the Edit configuration option to open the run/debug configuration editing window:

Two nodes will appear in the left directory: Python and Default. There is a single configuration option 'Solver',' under the first node directory and a lot of configuration information under the second option.

What does that mean?

Under the Default node, you can only see the name of the framework or the schema name. If you create a new Run/Debug profile, it will be created under the selected mode branch. If you change the settings under the Default node, all the corresponding configuration files will be changed.

For example, if you want to replace the Python interpreter used in Pycharm with a remote or local interpreter, you can change the interpreter settings under the Python page so that all new debug configuration files will use the new interpreter.

Under the early Python node, only a single configuration option, 'Solver', which belongs to the Python type configuration, is different from the Python mechanism under the Default node. It uses a non-transparent icon to indicate the saved state of the current configuration file. When you save the configuration file, the icon becomes non-transparent. For example, we create a new configuration file for the current Solver script under the Python type, named 'Solver1'.

If you make any changes to an existing configuration file, these changes will only be applied to the corresponding script area.

5. Official operation

We have been able to run the script in a very direct way, and then we will look for other ways to run the script.

As we know, running a script means loading the current debug configuration file, so running the script mainly follows the following process:

(1) in the main toolbar, click the run/debug group box to confirm the current debug configuration file information

(2) do the following work (choose one of the three):

Click the run button to load the configuration file

Press the Shift+F10 shortcut key

On the main menu, select Run → Run

At this point, we can use the Run tool window. Observe the running results of the program in the window.

6. Run the test program

We are not talking about the importance of code testing here, but how Pycharm can help us accomplish this function.

7. Select a tester

First, you need to specify a tester. Click the settings button on the toolbar, open the Settings/Preferences dialog box, and then click to go to the Python Intergated Tools page (which can be found through the search feature). The default selections are as follows:

Here we select Nosetests, save and close the dialog box.

8. Create a test block

First, let's create an instance of test. Pycharm provides a very intelligent way to create test code: click to select the class name and press the Ctrl+Shift+T shortcut key, or select Navigate → Test from the main menu, if the test program already exists, it will jump directly to the corresponding code, otherwise create it:

Following the prompts, Pycharm displays the following dialog box:

Click the OK button to view the creation result:

At this point, Pycharm has automatically created a test class, of course, this is only a class framework, we need to write test functions manually.

9. Run the test code

When everything is ready, right-click the test class name and select run command from the pop-up shortcut menu:

Observe the output of Test Runner tab in the running status bar:

10. Debug and run

The first thing to do is to figure out why debugging is needed. Suppose our program hits an error while running, how do we locate the location of the error? This requires debugging.

In Pycharm, we can debug the program directly. The only preparatory work we need to do is to add breakpoints where the program is necessary, and then we will introduce it in detail:

11. what is a breakpoint?

A breakpoint marks the location of a line, and when the program runs to that line of code, Pycharm temporarily suspends the program so that we can analyze the running state of the program. Pycharm supports several types of breakpoint types of breakpoints, which can be distinguished by corresponding icons.

Here we take the line breakpoint of Python as an example to introduce

12. Set breakpoints

The method is very simple, just click the blank gray slot on the left side of the code:

Note that the breakpoint will mark the corresponding line of code in red. This color mark cannot be changed by the user at present. We will introduce a solution as soon as possible.

By the way, canceling the breakpoint is also easy, just click again at the same location.

When you hover the mouse pointer over the breakpoint, Pycharm displays the key information, line number, and script properties of the breakpoint. If you want to change the properties of the breakpoint, right-click the breakpoint:

You can try to personalize the breakpoint properties, and then observe the changes in the icon.

13. Code debugging

Next, we officially start debugging the code.

First select the 'Solver' file with the same name from the profile group box as the configuration file for the current debugging, and then click the debug button (green beetle-style button):

Next, Pycharm will do the following:

(1) PyCharm starts running and pauses at the breakpoint

(2) the line of code where the breakpoint is located turns blue, which means that the Pycharm program process has reached the breakpoint, but has not yet executed the code marked by the breakpoint.

(3) the Debug tool window window appears, showing the current important debugging information and allowing users to make changes to the debugging process.

Although the functional information of all the controls in the debugging window is fully provided in the Pycharm user's manual, we still have a brief introduction to them here. We find that the window is divided into two tabs: Debugger tab and the Console tab.

(1) Debugger window is divided into three visible areas: Frames, Variables, and Watches. These windows list the current framework, running processes, and make it easy for users to view the status of variables in the program space. When you select a frame, the relevant variable information will be displayed, of course, these areas can be folded and hidden.

(2) the Console window displays the current console output information. By default, this window is located under Debugger and can be displayed in front of it by clicking its tab.

Of course, we can change the location of these windows, if you don't like the default layout of the program. Specifically participate in the Moving tabs and areas chapter.

The working mode of the Debugger window:

OK, now the program is paused at the first breakpoint, and the Frames window shows the process demo corresponding to line 7 of the Solver script. The related variables a, b, c have been defined, but the variable d has not been defined. Next?

Press F9 (or the green arrow on the left toolbar) and the program will continue to run to the next breakpoint, so that you can run each breakpoint over and over again to observe the changes in the variables.

For more information about Debugger windows, see the software manual: product documentation

The working mode of the Console window:

Why do you need a Console window? When we need to check the error messages given by the program, or do some additional temporary operations, we need to do so in this window.

Click the Console tab to bring it to the front:

Then click the command button in the left toolbar to display the command prompt for Python:

The console mechanism is activated to try to execute some Python commands in it:

Note that the console window provides code spelling hints (Ctrl+Space) and historical memory (Up/Down keys) functions. For more information, see Using Debug Console.

Finally, if you want the Console window to be available all the time, simply move it into a separate window:

14. Run again

After completing this debug run and loading the debug configuration file again, we can run debugging again by clicking the run button on the toolbar.

15. REPL-- debugs the program in the console interface

Finally, if you are more accustomed to working in a console environment, you can also set Pycharm to console mode. Select Tools → Run Python Console... from the main menu To load the console:

The console window is activated and appears as a separate window:

There are a lot of interesting things we can do in this console window, and then we'll show how to import the code from the recently written Solver.py file into the console:

Open the Solver.py file (there are various ways to open it, such as Ctrl+E-View → Recent Files), select all the code contents in the file (Ctrl+A, or Edit → Select All), and then press Alt+Shift+E (or right-click to select Execute Selection in Console from the pop-up shortcut menu):

At this point, Pycharm automatically imports the selected code into the console interface so that we can edit it:

Thank you for your reading, the above is the content of "how to debug and run Pycharm code". After the study of this article, I believe you have a deeper understanding of how to debug and run Pycharm code. Here is, the editor will push for you more related knowledge points of the article, welcome to follow!

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