Yes, this is possible. The license allows installation on multiple PCs as. Long as it's not used on multiple machines at the same time. I recently bought a license for PyCharm but since I ordered a new. Laptop (which should arrive in shortly), I haven't entered the license. In the PyCharm installation on my old laptop. Download the patch file JetBrains- agent.jar 2. Double click pycharm-professional-2019.3.exe to install pycharm If you just downloaded pycharm, you need to click “evaluate for free” in the activation window for free trial, and then create an empty project, so you can go to pycharm’s work page 3. Create project 1) After entering the.
These instructions show how to configure PyCharm Professional for SKA control system development using the SKA Dockerimages. PyCharm can be configured to use the Python interpreter inside a Docker image, which allows:
- Copy the corresponding binary file of the license server to a permanent directory, such as “ C: license-server ” or “ /opt/license-server/ “ Then, on Windows: Run a CMD as administrator; Enter the folder where you put the license server by using “cd” command.
- Download and install the latest version of PyCharm Professional from official site Copy the universal agent (jetbrains-agent.jar) file to installation folder, like “ C:Program FilesJetBrains “ Run program, select ‘ Evaluate for free ‘ option in the “ PyCharm License Activation ” window, and click ‘ Evaluate ‘.
development and testing without requiring a local Tango installation;
the development environment to be identical to the testing and deployment environment, eliminating problems that occurdue to differences in execution environment.
Follow the steps below to configure PyCharm to develop new code and run tests for the tango-example project using theDocker images for the project.
Make sure that the following prerequistes are met:
Docker is installed, as described on the page Docker Docs.
PyCharm Professional must be installed. PyCharm Community is not sufficient!
You have basic familiarity with PyCharm. If this is the first time you have used PyCharm, follow the First Stepstutorials so that you know how to use PyCharm to develop, debug, and test a simple Python application using a localPython interpreter.
Clone the tango-example project¶
PyCharm allows you to check out (in Git terms clone) an existing repository and create a new project based on the datayou’ve downloaded.
From the main menu, choose VCS Checkout from Version Control Git, or, if no project is currently opened, chooseCheckout from Version Control Git on the Welcome screen.
In the Clone Repository dialog, specify the URL of the tango-example repository (you can click Test to make surethat connection to the remote can be established).
In the Directory field, specify the path where the folder for your local Git repository will be created into whichthe remote repository will be cloned. The dialog should now look similar to this:
Click Clone, then click Yes in the subsequent confirmation dialog to create a PyCharm project based on the sourcesyou have cloned.
Build the application image¶
With the source code source code checked out, the next step is to build a Docker image for the application. This imagewill contain the Python environment which will we will later connect to PyCharm.
Begin a terminal session in the cloned repository directory and build the image:
The last lines of terminal output displays the name and tags of the resulting images, e.g.,
In the example above, the image name is tagged as nexus.engageska-portugal.pt/tango-example/powersupply:0.1.0-65c0927 andnexus.engageska-portugal.pt/tango-example/powersupply:latest. Take a note of the image tagged as latest as you will needit when configuring the remote interpreter.
Configure the remote interpreter¶
Following the official PyCharm documentation, configure Docker as a remote interpreter using the image you justcreated. The ‘Add Python Interpreter’ dialog should look similar to this:
As a result, the Python interpreter Preferences dialog should look something like this:
Click ‘OK’ to apply your changes.
It is recommended to use the remote interpreter in the image tagged as :latest rather than the image tagged with agit hash, e.g., :0.1.0-65c0927. The :latest version will always point to the most recent version of the image,whereas the hash-tagged image will be superceded every time you rebuild.
You can now navigate through the project. As an exercise, open the source code for the PowerSupply class, which isdefined in powersupply/powersupply.py. Notice that the IDE notifications and intellisense / code completion are nowbased on information gathered from the remote Docker interpreter. Below an import statement, try typing
fromtangoimport and activate code completion (ctrl+space). Notice how the tango packages installed in theDocker image are suggested to complete the statement.
Whenever you change the Python environment, for example by adding or removing dependencies in Piplock, after rebuildingthe Docker image you should regenerate the project skeletons to make PyCharm aware of the changes. To do this, selectFile Invalidate Caches / Restart… from the main menu.
Running unit tests¶
The tango-example project illustrates two types of unit test:
Self-contained unit tests that execute within the confines of a single Docker container. These tests use the Tangoclass DeviceTestContext, which provides a mock connection to a Tango database. In the tango-example project, thesetests are found in tests/test_1_server_in_devicetestcontext.py.
Unit tests that exercise a device in a real Tango environment, with connections to a Tango database and otherdevices. utilise require a connection. In the tango-example project, these tests are found intests/test_2_test_server_using_client.py.
This tutorial illustrates how to run the self-contained unit tests described in 1.
From the main menu, choose Run Edit Configurations… and click on the ‘+’ button to add a new configuration. Make catalina boot usb terminal. From themenu that appears, select Python tests pytest to add a new pytest test configuration. The menu selection looks likethis:
Change the Target radio button to ‘Module Name’. Click ‘…’ to select the target, choosingtest_1_server_in_devicetestcontext as the module to be tested.
Select ‘Project Default’ as the Python interpreter for this configuration.
If you change the project default interpreter to another configuration then you may want to revisit this run/debug configuration and explicitly select the Docker :latestinterpreter rather than use the project default.
The configuration dialog should look like similar to this:
Pycharm License Server Free
Click ‘OK’ to accept your changes.
From the main menu, choose Run Run…, then from the Run dialog that opens, select the configuration you just created.The unit tests will execute, with the results displayed in PyCharm’s Run panel. The results will look like this:
Pycharm Professional License Server List
The coverage module is not compatible with the PyCharm or Visual Studio Code debugger and must be disabledbefore any debugging session. Do so by editing setup.cfg, commenting out the
addopts=.. line of thetool:pytest section so that it looks like this:
PyCharm has a debug mode that allows breakpoints to be added to code and the runtime state of the device examined.Refer to the official PyCharm documentation for comprehensive documentation onhow to add breakpoints and run in debug mode.
The steps in the official documentation can also be used to debug and interact with ah Tango device, using theconfiguration set up in the previous section as the basis for the debug configuration. However, full breakpointfunctionality requires some workarounds. Breakpoints set outside device initialisation code (i.e., outside
__init__() and init_device()) only function if the Tango device uses asyncio green mode. In non-asynciomodes, Tango creates new Python threads to service requests. Unfortunately these threads do not inherit the debuggingconfiguration attached by PyCharm.
For working breakpoints, there are two solutions:
the device must be converted to use asyncio green mode;
pydevdto your Piplock as a project dependency, rebuild the Docker image and refresh the projectskeletons, then add
pydevd.settrace()statements where the breakpoint is required. For example, to add abreakpoint in the
PowerSupply.get_current()method, the code should look like this:
SegmentationFaults when using DeviceTestContext
Unit tests that create a new DeviceTestContext per test must run each DeviceTestContext in a new process to avoidSegmentationFault errors. For more info, see:
Errors when mixing test types
Running DeviceTestContext tests after test that use a Tango client results in errors where the DeviceTestContext getsstuck in initialisation. One workaround is to set the filenames so that the DeviceTestContext tests run first.