Mohy Elden

I saw it [here](https://github.com/radis/radis/issues/53) as a todo in performance section and thought it could be beneficial. But honestly even if its safer, the process feels slower with it, I see...

With auto chunksize (chunksize value became 30.000)  When chunksize is set to 1e7:  Without chunksize option:  I think it is for better memory handling as mentioned [here](https://github.com/radis/radis/blob/ada5c335c2bc53922232240a88dbc6a39e84f93d/radis/lbl/broadening.py#L2666)

Sure, I'll try a larger one like CO₂. It will take some time since my internet isn't great.

I don't see a reason to keep it as you mentioned. I tried CH4 with: - No chunksize option → Max resident set size : 578412 kB - chunksize =...

Execute the following code twice once with the option ``chunksize`` and once without using this command: ```bash /usr/bin/time -v python file.py ``` ```python from radis import SpectrumFactory, plot_diff sf =...

I am not a mentor, but you can find the code in this repository: [here](https://github.com/nightwatchjs/nightwatch-docs) in /nightwatch-docs/src/includes/footer.ejs at line 154, It's an iframe from Substack, so I am not sure...

done @erwanp

Sure We have two approaches 1. **Using the most common ones and passing them to the appropriate function** (similar to the current approach): ``` trace_kwargs = { k: kwargs.pop(k) for...

Cool I will go with this

Both solutions look great to me we can wait for @erwanp to share his thoughts.