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I have an existing conda environment with python 3.8.

How would you recommend installing ghpythonremote?

If this means that I must downgrade python. Can I keep two python versions in one environment e.g. 2.7 and keep 3.8 or not really?

A python virtual environment is basically just a folder where one python.exe executable is kept, along with its standard library and any user-installed packages. All the versions of these have to be compatible with each other, in particular it is not possible to have two different python.exe in the same environment.

Python Download Remote File

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The best way to install GHPythonRemote for you is to create a new virtual environment in Conda, based on the latest python 2.7. This procedure is explained in the documentation. You will need to install all the other packages you need for your scripts in that env.

If you can, I would completely start over on the CPython side. Uninstall Anaconda, reinstall it with a fresh installer (use Miniconda to save some time, GHPythonRemote does not use the base Anaconda environment anyway) but for just one user this time. Then create the rhinoremote environment from an unelevated command prompt (i.e. NOT running as administrator), and verify that it gets created in your user folder.

Noob to vim here trying to learn to use it for all my text editing needs. Right now, I'm using VS Code as an IDE because it allows remote debugging of Python code, which is necessary to my workflow. Can vim or associated plugins do the same thing? I tried looking this up but everything I could find was about remote code execution, not specifically debugging (ability to set breakpoints, go up and down the call trace to see intermediate variable values, etc.)

To remotely call custom Blueprint Function Libraries with static methods, the object path must point to the Class Default Object (CDO) , which is the one object that a UCLASS maintains. The following sections explain how to build the object path for C++ and Python objects.

I need, however, to be able to execute my code to remote interpreters sometimes (like a docker container on the same machine or a remote server). I read some posts, most of which outdated, which stated that it is not possible yet, so I was wondering if something has changed until now or if there are any projects working on this.

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To get started download the remote extension pack, check out the Visual Studio Code Remote documentation, and dive right in! Check out the video below for a quick tour and keep on reading to learn more!

The ability to work with WSL and remote Python interpreters have long been the top requested features on our Python Extension GitHub page. We have heard from our Python users many different reasons why they need to work in remote workspaces: in the case of SSH their code needs access to large amounts of data, compute, GPUs, or other resources; with Docker they need to be able to create and switch between development environments with complex dependencies; and with WSL they may need tools and packages that are only available in a Linux environment.

Once you open a dev container, Visual Studio Code will create the docker image(s) and then installs a light-weight remote server and voil, you are now coding inside of the dev container! The remote server allows Visual Studio Code to run extensions remotely, such that almost all functionality works just like it does in your local environment.

We are working on remote development in Visual Studio for C# and C++ but have no plans to share on Python at this time. You can read more about early previews for other languages here: -productivity-and-collaboration-from-anywhere/

Tried this. Still remote containers not showing up through remote-containers or remote-ssh extension.

Installed the docker extension, and the remote containers became visible, but only a shell can be attached to the containers on the host machine, it gives an error on attaching vs-code to any container.

Any ideas how to proceed?

I found various posts on python module dependencies, most of them related to OneAgent plugins and direct dependencies. I'm trying to build a AG remote plugin where the python module that the plugin depends on (ExasolDatabaseConnector) has another dependency to the pyodbc module.

thanks! I didn't think about that! Switching to python3.6 was the solution. I've switched my build docker container to 3.6 and that worked fine. Maybe that dependency is worth a note in the AG plugin documentation, since many distros are already switching to more recent versions of python. Especially since the documentation recommends to build directly on Activegates this might not be obvious to people.

By default, the debugger uses the same interpreter selected for your workspace, just like other features of Python extension for VS Code. To use a different interpreter for debugging specifically, set the value for python in launch.json for the applicable debugger configuration. Alternately, select the named interpreter on the Status Bar to select a different one.

Note: Be aware that when you specify a host value other than 127.0.0.1 or localhost you are opening a port to allow access from any machine, which carries security risks. You should make sure that you're taking appropriate security precautions, such as using SSH tunnels, when doing remote debugging.

In the terminal, start Python with the script, for example, python3 myscript.py. You should see the "Waiting for debugger attach" message that's included in the code, and the script halts at the debugpy.wait_for_client() call.

Remote debugging allows you to step through a program locally within VS Code while it runs on a remote computer. It is not necessary to install VS Code on the remote computer. For added security, you may want or need to use a secure connection, such as SSH, to the remote computer when debugging.

The following steps outline the general process to set up an SSH tunnel. An SSH tunnel allows you to work on your local machine as if you were working directly on the remote in a more secure manner than if a port was opened for public access.

Create an SSH tunnel by running ssh -2 -L sourceport:localhost:destinationport -i identityfile user@remoteaddress, using a selected port for destinationport and the appropriate username and the remote computer's IP address in user@remoteaddress. For example, to use port 5678 on IP address 1.2.3.4, the command would be ssh -2 -L 5678:localhost:5678 -i identityfile user@1.2.3.4. You can specify the path to an identity file, using the -i flag.

In your VS Code workspace, create a configuration for remote debugging in your launch.json file, setting the port to match the port used in the ssh command and the host to localhost. You use localhost here because you've set up the SSH tunnel.

This starts the package myproject using python3, with the remote computer's private IP address of 1.2.3.4 and listening on port 5678 (you can also start the remote Python process by specifying a file path instead of using -m, such as ./hello.py).

Local computer: Only if you modified the source code on the remote computer as outlined above, then in the source code, add a commented-out copy of the same code added on the remote computer. Adding these lines makes sure that the source code on both computers matches line by line.

Local computer: start the VS Code debugger using the modified Python: Attach configuration and the Start Debugging button. VS Code should stop on your locally set breakpoints, allowing you to step through the code, examine variables, and perform all other debugging actions. Expressions that you enter in the Debug Console are run on the remote computer as well.

Provides the fully qualified path to the python program's entry module (startup file). The value ${file}, often used in default configurations, uses the currently active file in the editor. By specifying a specific startup file, you can always be sure of launching your program with the same entry point regardless of which files are open. For example:

If not specified, this setting defaults to the interpreter selected for your workspace, which is equivalent to using the value ${command:python.interpreterPath}. To use a different interpreter, specify its path instead in the python property of a debug configuration.

I trying to run python3 that is on my raspberry pi. I am currently using rsub and can edit the files on my pi with no problems. I would like to run the remote files with the python on the pi vs the system python on the host machine. Is a remote python build system possible?

If the file on the remote end is in your home directory, then this should work out of the box I think; the ssh command should default to your home directory on the remote end. If not you can either try to modify the command to first cd into the appropriate place or, if you know the appropriate place, add that as an absolute path in front of the $file_name portion.

There is a Python API (nisyscfg) for NI-System Configuration, which is the driver for NI MAX. Unfortunately, there is not much documentation and examples on how to add a remote cDAQ chassis programmatically. You have to figure it out. 17dc91bb1f