Positron [.py files] lags during code autocompletion

[tenFnAN]

I am experiencing a very frustrating issue with Positron's IntelliSense functionality. Occasionally, in .py files, autocomplete suggestions are not displayed. Below are some observations and examples, along with screenshots for reference.

### Key Observations:
The issue occurs for various objects:

• Data objects like df (DataFrame).
• Python class instances (OOP objects).
• Aliases such as pd (pandas).

No issues in .ipynb files: Autocomplete works quickly and reliably there.

Analogous issue with "Go to Definition": Sometimes this functionality is also unresponsive.

File-specific behavior:

• For example, I experienced a situation where autocomplete worked in the console but not in the .py script, even when tested simultaneously.

Project context:

• I am working on a computer vision project involving many files (images + videos).

• The scripts are not overly complex but import several libraries.

Timing and patterns:

• The issue often starts after some time working in the project on a given day.

• It resolves temporarily, but then reappears after I write more code.

Environment context:

• I don’t keep large files in memory within my environment.

• The issue seems to behave as if "something gets clogged."

### My Questions:

1. Are there any settings or options I can tweak to resolve or mitigate this issue?
2. Are there any best practices for optimizing IntelliSense performance in larger projects?
3. Can I provide logs or any other information to help diagnose the problem?

Environment Details:

Positron Version: 2025.01.0 (Universal) build 159
Code - OSS Version: 1.95.0
Commit: bc8820b
Date: 2025-01-09T23:29:00.471Z
Electron: 32.2.1
Chromium: 128.0.6613.186
Node.js: 20.18.0
V8: 12.8.374.38-electron.0
OS: Darwin arm64 23.4.0

I would be very grateful for any suggestions and assistance!

[sharon-wang]

Hey @tenFnAN, thank you for the initial context you've provided. Let's grab some Python kernel logs to further diagnose the problem you're seeing.

Could you please do the following the next time you reproduce this issue:

1. Open up the Command Prompt with Cmd + Shift + P
2. Search for Output: Show Output Channels... and select that option in the Command Prompt dropdown
   
3. In the Output pane that opens, click the dropdown and select the Python Kernel output, which looks something like Python [VERSION] ([ENV]): Kernel; example:
   
4. Make sure Debug is selected as the log level, by clicking the settings cog icon in the Output pane; example:
   
5. Please copy the full text from the Python Kernel output and share it here!

[tenFnAN]

Thank you for your response. Please find below a copy of the content.

If I understand correctly, the cause of my delays is the fact that I have many notebooks open? And is this the only reason? I’m asking because, apparently, I haven’t yet developed good practices for working with Python in Positron.

2025-01-17 16:25:31.840 [info] ** Begin kernel log for session Python 3.10.15 (Poetry: .venv) (python-2864196a) at 17.01.2025, 16:25:31 **
2025-01-17 16:25:31.840 [info] Streaming kernel log file: /var/folders/mx/94qf794j5578bws9qx889h300000gn/T/kernel-6ntsgH/kernel.log
** Begin kernel log for session ___video_quality.ipynb (python-1f5051dd) at 17.01.2025, 16:25:40 **
** Begin kernel log for session raport_image_pca.ipynb (python-389e161f) at 17.01.2025, 16:25:40 **
** Begin kernel log for session tmp.ipynb (python-3ddf7634) at 17.01.2025, 16:25:40 **
** Begin kernel log for session 01_files_conversion.ipynb (python-27580a44) at 17.01.2025, 16:25:40 **
** Begin kernel log for session 03_action_detection.ipynb (python-03eaf432) at 17.01.2025, 16:25:40 **
** Begin kernel log for session 06_training.ipynb (python-789014b8) at 17.01.2025, 16:25:40 **
** Begin kernel log for session 01_compare_hist.ipynb (python-515b2854) at 17.01.2025, 16:25:40 **
** Begin kernel log for session raport_video_counts.ipynb (python-efad078c) at 17.01.2025, 16:25:40 **
Streaming kernel log file: /var/folders/mx/94qf794j5578bws9qx889h300000gn/T/kernel-FVnEZq/kernel.log
Streaming kernel log file: /var/folders/mx/94qf794j5578bws9qx889h300000gn/T/kernel-v7sLNt/kernel.log
Streaming kernel log file: /var/folders/mx/94qf794j5578bws9qx889h300000gn/T/kernel-3JJjqq/kernel.log
Streaming kernel log file: /var/folders/mx/94qf794j5578bws9qx889h300000gn/T/kernel-k3vb7H/kernel.log
Streaming kernel log file: /var/folders/mx/94qf794j5578bws9qx889h300000gn/T/kernel-CcPV8a/kernel.log
Streaming kernel log file: /var/folders/mx/94qf794j5578bws9qx889h300000gn/T/kernel-krEUMo/kernel.log
Streaming kernel log file: /var/folders/mx/94qf794j5578bws9qx889h300000gn/T/kernel-NWMqxz/kernel.log
Streaming kernel log file: /var/folders/mx/94qf794j5578bws9qx889h300000gn/T/kernel-sSClC3/kernel.log
NOTE: When using the `ipython kernel` entry point, Ctrl-C will not work.



To exit, you will have to explicitly quit this process, by either sending

"quit" from a client, or using Ctrl-\ in UNIX-like environments.



To read more about this, see https://github.com/ipython/ipython/issues/2049





To connect another client to this kernel, use:

   --existing /var/folders/mx/94qf794j5578bws9qx889h300000gn/T/connection_python-2864196a.json

NOTE: When using the `ipython kernel` entry point, Ctrl-C will not work.



To exit, you will have to explicitly quit this process, by either sending

"quit" from a client, or using Ctrl-\ in UNIX-like environments.



To read more about this, see https://github.com/ipython/ipython/issues/2049





To connect another client to this kernel, use:

   --existing /var/folders/mx/94qf794j5578bws9qx889h300000gn/T/connection_python-efad078c.json

NOTE: When using the `ipython kernel` entry point, Ctrl-C will not work.



To exit, you will have to explicitly quit this process, by either sending

"quit" from a client, or using Ctrl-\ in UNIX-like environments.



To read more about this, see https://github.com/ipython/ipython/issues/2049





To connect another client to this kernel, use:

   --existing /var/folders/mx/94qf794j5578bws9qx889h300000gn/T/connection_python-789014b8.json

NOTE: When using the `ipython kernel` entry point, Ctrl-C will not work.



To exit, you will have to explicitly quit this process, by either sending

"quit" from a client, or using Ctrl-\ in UNIX-like environments.



To read more about this, see https://github.com/ipython/ipython/issues/2049





To connect another client to this kernel, use:

   --existing /var/folders/mx/94qf794j5578bws9qx889h300000gn/T/connection_python-389e161f.json

NOTE: When using the `ipython kernel` entry point, Ctrl-C will not work.



To exit, you will have to explicitly quit this process, by either sending

"quit" from a client, or using Ctrl-\ in UNIX-like environments.



To read more about this, see https://github.com/ipython/ipython/issues/2049





To connect another client to this kernel, use:

   --existing /var/folders/mx/94qf794j5578bws9qx889h300000gn/T/connection_python-03eaf432.json

NOTE: When using the `ipython kernel` entry point, Ctrl-C will not work.



To exit, you will have to explicitly quit this process, by either sending

"quit" from a client, or using Ctrl-\ in UNIX-like environments.



To read more about this, see https://github.com/ipython/ipython/issues/2049





To connect another client to this kernel, use:

   --existing /var/folders/mx/94qf794j5578bws9qx889h300000gn/T/connection_python-1f5051dd.json

NOTE: When using the `ipython kernel` entry point, Ctrl-C will not work.



To exit, you will have to explicitly quit this process, by either sending

"quit" from a client, or using Ctrl-\ in UNIX-like environments.



To read more about this, see https://github.com/ipython/ipython/issues/2049





To connect another client to this kernel, use:

   --existing /var/folders/mx/94qf794j5578bws9qx889h300000gn/T/connection_python-3ddf7634.json

NOTE: When using the `ipython kernel` entry point, Ctrl-C will not work.



To exit, you will have to explicitly quit this process, by either sending

"quit" from a client, or using Ctrl-\ in UNIX-like environments.



To read more about this, see https://github.com/ipython/ipython/issues/2049





To connect another client to this kernel, use:

   --existing /var/folders/mx/94qf794j5578bws9qx889h300000gn/T/connection_python-27580a44.json

NOTE: When using the `ipython kernel` entry point, Ctrl-C will not work.



To exit, you will have to explicitly quit this process, by either sending

"quit" from a client, or using Ctrl-\ in UNIX-like environments.



To read more about this, see https://github.com/ipython/ipython/issues/2049





To connect another client to this kernel, use:

   --existing /var/folders/mx/94qf794j5578bws9qx889h300000gn/T/connection_python-515b2854.json

[sharon-wang]

Thanks @tenFnAN! Was there any further output? For example, when I try to trigger autocomplete in a .py file, my Kernel output includes several lines like the following:

[Python] [positron_ipykernel._vendor.pygls.protocol.json_rpc] Received b'{"jsonrpc":"2.0","id":19,"method":"textDocument/completion","params":{"textDocument":{"uri":"file:///Users/sashimi/qa-example-content/workspaces/python-plots/plotly-example.py"},"position":{"line":2,"character":2},"context":{"triggerKind":1}}}'

@seeM could having multiple large notebooks open affect autocomplete in .py files (but not the Console or other ipynb files)?

[seeM]

I think the python.languageServerLogLevel setting also needs to be set to debug to get the kernel debug logs. (We could consider simplifying that.)

@sharon-wang I don't think so... Each notebook starts its own kernel and has its own language server so there shouldn't be any interaction there. Might be worth monitoring CPU and RAM usage when these lags happen and see if anything is maxing out?

EDIT: And notebook kernels/language servers are also separate from the Console's.